Cable stocks are down a lot - why?

• Wells Fargo's 4/24 note captured the sentiment shift well: Comcast's strong 1Q got drowned out by Charter's print, and investor concern has rotated back to the long-running tension between sub growth and ARPU. The newer wrinkle on cable earnings calls is LEO satellite — management is framing it as a complementary resale opportunity, but the sell side reads the buy-side worry as LEO becoming a real share taker at the edge of the urban footprint over the medium term.

  • CMCSA - net adds improving but rev/ebitda pressured by increasing competition

• Here is some data that seems to support these worries: https://www.lightreading.com/broadband/starlink-carving-out-a-niche-in-urban-us-ookla

• AI content (I have not watched/listened to all of these)

  • CIO of Public Investments at Coatue (link)

  • Ken Griffin on AI progress in the last several months (link)

  • Chris Hohn sold MSFT on AI risks (link)

    • Not sure what exactly this means, or why/how MSFT specifically is at risk vis-a-vis GOOG. I own MSFT, but my best guess is that, culturally, OpenAI seems like a mess vs the other frontier labs. It also seems like AMZN and GOOG may be further ahead in custom silicon.

  • BX GOOG $5b JV (link)

  • INTC CEO on agentic AI driving CPU demand inflection (link)

  • Andrej Karpathy joined Anthropic

  • Gavin Baker at Sohn and on Invest Like the Best (link)

  • You should integrate HTML into your agent workflows (link)

  • Anthropic CFO Krishna Rao on Invest Like the Best was one of my favorite listens in recent memory

• Key questions around mattress research

  • Will PRPL/SNBR survive? Major upside if so, but both situations are hard to read and have bankruptcy as realistic scenarios.

  • Are we due for a large snap back? Or slow and steady growth from here?

    • The industry can’t seem to agree on the data (link)

• Is Claude changing how anyone else is thinking about their PA?

  • I asked Claude how I use it for my PA. It said:

    Bryan runs me as a daily PA copilot. Every afternoon I send him a single email that combines performance versus SPY, QQQ, and IWM, attribution by bucket, Minervini score, and sector, his full holdings and exposures, action and stop flags, a quick market tape, and a Minervini 8-point Trend Template scan across his holdings and tiered watchlist, with a diff of what changed since the prior day.

    Beyond the daily email, he drives me interactively to journal trades and theses, run 13F to Minervini to correlation pipelines on new manager filings, parse SEC and EDGAR documents, and pull alt-data using the Carbon Arc MCP for single-name work. Capture happens in real time as he talks, so every trade decision, thesis update, and observation lands in his journal as it happens, not in a notebook he never reopens.

Disclosure: none of the is investment advice; I/we may own positions in securities mentioned

Before going full-time on Ticker Trends, Adrien studied computer science at George Washington University, transferred to SMU in Dallas, worked full-time as a software engineer in robotics and machine learning, and ran a quantitative finance YouTube channel he started at 14 or 15 that grew to tens of thousands of subscribers. The business has scaled from a solo side project to a team of over ten, almost entirely on a single pre-angel check and reinvested revenue.

We covered a lot of ground:

• Adrien’s Background. The teenage YouTuber to startup founder story (GW, SMU, robotics SWE in Dallas, classes by morning, day job, Ticker Trends 6pm to 1am)

• Building in Public Early. Why stealth mode is usually wrong, and how a small blog and YouTube audience attracted ML researchers and VCs that changed the trajectory

• The Pre-Angel Check + Going Full-Time. The rolling stress curve at every stage of company growth, from “can I afford to do this” to “now I have to scale this into the implied valuation”

• Finding Product-Market Fit. A year and a half of feedback loops before identifying the scalable problem worth putting all the eggs into

• Team Today + Hiring Philosophy. 5 to 6 software engineers plus 2 to 3 commercial roles, biased toward recent grads with no industry baggage and clean-slate thinking

• Management + Delegation. Setting structures and expectations clearly so others can execute, freeing the founder to spend more time on creativity and direction

• What “Pre-Purchase Intent” Actually Means. Why social, research, and clickstream signals lead transaction panels, and where breadth advantages compound over panel-bound competitors

• Case Studies. Duolingo (the ChatGPT brand erosion showing up in social long before DAUs and revenue) and American Eagle (the Sydney Sweeney call against foot traffic providers who got it wrong)

• Data Strategy. A blend of proprietary collection and licensed third party data, with infrastructure built so every new dataset improves every company in coverage

• Breadth Over Depth. Why they add data that answers questions for hundreds of companies, not bespoke signals for one name that may not matter in two quarters

• Product Tiers. A low-cost retail offering using widely available data (think Google Trends, applied well) and the KPI Forecasting Suite for asset managers, funds, and corporates

• LLM Integration, the Inverse Way. Never advertise it, deliver structured outputs to clients, keep determinism and accuracy at the user layer, run all the malleability behind the scenes

• Bootstrapping vs Raising. One pre-angel check, never raised since, and how he thinks about strategic capital now that the business has hit an inflection point

• Delegation as Replication. Hiring people who are better than you at the role, then influencing direction rather than execution

• Hiring Process. Trial tasks with deliberately hard or near-impossible problems, plus paying attention to what candidates do in their free time

[Note: you can also listen on Spotify]

Bryan Wagman: All right, Adrien, thank you for coming on today. Really appreciate it. It would be great to kick things off if you could just give our listeners a bit of an overview about yourself, your story over the long term, who you are, what you do, and how you got to the spot that you’re in today.

Adrien Navarre: Sure. Thank you so much for having me on, Bryan.

A little bit of my background: I’m the CEO and founder of Ticker Trends. Ticker Trends is a financial alternative data business. We do KPI forecasting, primarily focused on pre-purchase intent data. So anticipating when people will make purchases based on social discussion, research, clickstream data, and different forms of digital alternative data that indicate some form of pre-purchase intent ahead of when they decide to sign that enterprise contract, or swipe their credit card, and make the purchase for different public and private products and brands.

My background before starting Ticker Trends: I studied computer science throughout university. I went to George Washington in Washington, D.C., then transferred to Dallas to Southern Methodist University, and was doing computer science pretty much the whole time. When I got to Dallas, I was working in robotics and machine learning full-time as a software engineer, and that gave me a lot of exposure to more complex computer science concepts.

Outside of work and school, I was always very personally interested in financial markets. That mixture of experiences with machine learning and software engineering, and then my extreme personal interest in financial markets, is what led me to start Ticker Trends. I initially built out a lot of the infrastructure and software to have a tool to manage my own portfolio with some form of edge that I believed I had at the time in interpreting different forms of alternative data.

Eventually, I started making some blog posts and YouTube videos about what I was working on. This was while I was a part-time student and also working a full-time robotics job. Fortunately, at that time, a venture capital firm reached out to me and gave me some pre-angel seed capital to work on Ticker Trends full-time.

That’s kind of been the story since then. I’ve been working on it for just over two years now, almost two and a half years. We’ve grown from just myself to now a team of almost over 10 people, and we’re continuously expanding, which has been a very exciting journey.

Bryan Wagman: Awesome. I’d love to hear more about those very early days of Ticker Trends, particularly, you mentioned the extreme interest in the financial markets, and then eventually it kind of became Ticker Trends, which had a blog and a YouTube. I’m wondering, what was maybe a typical day when you were working on this stuff in the weeks leading up to actually deciding, “Hey, I should try to make this a business”?

Adrien Navarre: Yes. Well, I guess a little bit of context as to why I was interested in financial markets. When I was much younger, I had been very excited about producing content on YouTube. What I found when I was looking at different topics to make videos about is that it was extremely under-covered on YouTube and different public social channels to talk about quantitative finance and automated trading strategies.

So when I was very young, maybe 14 or 15 years old, I started a YouTube channel around different quantitative finance strategies and would produce content even with my limited knowledge. I was able to attract an audience just because no one was talking about it publicly. That channel had a little bit of a following, tens of thousands of subscribers.

That’s what really seeded a lot of my early interest in financial markets. It was kind of a snowball effect, where I started to have some success in making content on that YouTube channel, and it motivated me to keep going deeper and deeper into financial markets and quantitative finance. Since having that YouTube channel, it’s stuck with me the rest of my life, and I’ve always loved financial markets.

Leading up to when I went full-time on Ticker Trends, a little bit of what my schedule looked like at that time is I would wake up very early, and I had some morning classes at university, since I was a part-time student and was taking two or three college classes. Then I would leave my college classes and go to a full-time job working at the robotics company as a software engineer.

After working at the robotics company, around 6 p.m., I would then drive to my own office for Ticker Trends and work from 6 or 7 p.m. until midnight or 1 a.m., and then go home and do my homework for university. So I had a very extreme life setup at the time.

I knew that what I was working on with my own project, Ticker Trends, was my passion, but I also knew that what I was doing was unsustainable in terms of lifestyle. I think I always knew that something would change eventually. Either something would take off with Ticker Trends, or I would decide to go a different direction. But I definitely was doing a little bit of a Hail Mary to see if something could turn up.

At the time, I was just maximizing my exposure to potential new opportunities. Once I started producing content about it, even though it wasn’t attracting a very large number of viewers or listeners to the content I was making about Ticker Trends very early on, the people who did watch my content were very high quality. It would be machine learning researchers, or people deep in finance or venture capital. So I would meet all these interesting people, even though I was only getting a couple hundred views or reads on my blog posts or YouTube videos about Ticker Trends very early on.

I think it definitely taught me that this idea of going in stealth mode early on for a startup is not always right. It’s really important to be very vocal about your long-term ideas and what you’re working on, because when you’re working on something interesting, it will attract very unique, intelligent people, even if it’s not a large quantity of people at the very beginning.

Bryan Wagman: Yeah, that’s really interesting. I’d like to hear more about that period where you were deciding, or waiting to see, if Ticker Trends was going to take off, or if you were going to have to do something else. How long was that period? How long had you been actually trying to make it work as a business, or generate revenue, or enough to be able to go full-time on it? And what were either the positive signs or some of the negatives that you were watching for and considering?

Adrien Navarre: I think throughout the whole journey, the way to describe it is that I would still consider us, relatively speaking, a smaller-sized business compared to some of the other data companies. What happens in an early startup journey is that each time you think there might be no more stress, or, “If I just get to this specific goal, then things will get easier,” you find that at each goal there will be a new thing that can start stressing you out at that stage of the company.

I’ve gone through a couple of those now. Initially, like you described, the thing that was stressing me out was, “Can I have enough capital to go full-time on this?” Eventually I got that capital, and then it created a new stress, which was, “Now that I have this capital, I need to turn this into something real. I need to scale this up.” I had some money up front, but the revenue hadn’t caught up to the implied valuation of what that investor gave me the capital at.

At each level, and even later on once we were making enough revenue to start growing and scaling the business, and even now as we’re scaling and gaining new clients quite quickly, there are still different stresses and interesting dynamics. If your goal is to keep growing a company, then even when you have success or when you’re scaling, it can still be a very difficult challenge. You want to allocate resources effectively, where you’re reinvesting or directing your effort toward the right segments of the business to keep it growing.

That initial period after I got the capital to go full-time on Ticker Trends, it still took maybe a year, year and a half, before we found a direction for the business that would allow us to scale to some of our aspirations of what we wanted the business to be.

It’s one thing to have an idea of what you want to go to market with. But once you go to market, going through that period of feedback and iteration took us a while. The more we listened to feedback, the more we had people using our software and our platform, the more we explored new ideas, the better things got. Eventually we hit the inflection point of having our products set up in a way that was very scalable and solved problems that a larger set of higher-quality clients would have.

Once we hit that problem and identified it, we started to put all our eggs in that one basket and scale the business based on the success and demand we had for the problem we were solving most effectively.

Bryan Wagman: And what does the team look like today, and how has that evolved since your first hire?

Adrien Navarre: The team today is primarily software engineers. We have about five or six software engineers, and then the remaining two or three would be non-technical, either sales or marketing or growth or financial analyst roles, and a little bit mixed between all of those.

Early on, I was focusing a lot on recent grads and college students. With myself being a solo founder and being so young, I worked best with people my age and people in a similar situation to myself. I think that brought a similar excitement to the business and willingness to go all in on the idea.

As we’ve scaled, we’ve scaled in all directions, and we’ve needed different team members for different reasons. As much as college students are really great for having the adoption of new technology, and you can work with a lot of really smart people, there are also reasons to have people outside of just college students. So we’ve gone in both directions as we’ve grown.

I’ve always looked at it as one of the most important things we can do is curate and develop talent. Many of the software engineers we hire are people with little to no prior financial background who then get into financial markets and financial concepts through working at Ticker Trends. That’s been very exciting for me, the development of talent. Hiring is so important.

That’s always what we’ve biased toward, rather than hiring people who have worked in the industry for a long time and might have biases toward how things should work, versus coming from a clean slate.

Bryan Wagman: Yeah. Do you feel like there have been any significant challenges from a management and team-building perspective over the years, or any big ways in which you’ve changed how you approach managing people and building the team?

Adrien Navarre: I think in my approach to managing people, what I’ve come to realize is that a lot of the best thing I can do as the CEO and founder of a company is set up the structures and expectations to be as clearly defined as possible. Then that can set other people up for success.

I’ve tried, increasingly over time, to dedicate more of my time toward creativity and general direction, and then leave more and more of the execution to other team members. That’s allowed me to increasingly delegate more responsibility to other people.

Bryan Wagman: Yep. That’s interesting. Maybe we can start to move into the platform itself then. You mentioned earlier that what you’re trying to measure is consumer purchase intent. Could you elaborate on that a little bit, and how that differentiates you from what some of the other large platforms are evaluating?

Adrien Navarre: Yes. Like you described, we focus on consumer pre-purchase intent data. This is anything where a consumer is researching, discussing, or hearing about different products, brands, or concepts that might lead to a future purchase.

What makes this unique is that we have a lead time to many of the purchase datasets that are so heavily relied upon by many industries. We also have a lot of contextual and supplementary information that gives us information on the sustainability of different trends. Is something going to be a temporary lift in sales, or a meaningful multi-quarter, multi-year trend that can impact sales for a very long period of time? These are things that we can track and forecast and apply to markets very well.

There have also been other advantages to our approach, such as breadth of coverage. When we look at many of our competitors, when they have a transaction panel or any panel-based data, you start to become limited by the size of your panel when trying to cover more niche subjects, topics, brands, products, or ideas.

What’s so amazing about social data is that your panel is effectively 10 or 100 times larger, or a thousand or million times larger, than any credit card transaction panel dataset. So even for things that are very niche or small, we can cover and track them, whereas many of our competitors or other people in the industry don’t even have sufficient data to track or collect.

There are advantages both to tracking and understanding large businesses, and also advantages to us having a far wider breadth of coverage. We’ve now even expanded into private markets and are tracking small CPG brands all the way to the largest companies, like Pepsi, Coca-Cola, Cava, or big software companies. This data is equally applicable to almost any industry that has some consumer-facing product.

Bryan Wagman: Yeah. Could you maybe give an example of a recent investment thesis, or something from the blog, where there was something that your data uncovered that the market did not see?

Adrien Navarre: Yes. I think two examples we tend to give, which showcase some of the flexibility of our insights, would be first around Duolingo.

Toward last year, in 2025, around the proliferation of ChatGPT and a lot of the language models, there started to be changing consumer dynamics around how consumers viewed language models versus language-learning apps like Duolingo. It started to show up first in social discussion, and then very, very slowly over time trickled into company metrics like the DAU number, paid subscriber number, and revenue growth number of Duolingo many quarters later.

At that time, we had written about some of the early controversies that Duolingo management was causing, and that was causing pretty severe impacts to the sentiment and perception of Duolingo early on, when many consumers were making that consideration of whether they move to language models or keep using Duolingo. That eventually caused a deterioration of their brand, in addition to some key brand or social media managers leaving the company at the time. That showed up in social data far before it showed up in reported metrics or other datasets, and then later caused Duolingo to reprice quite significantly.

Another one was our coverage of American Eagle. At the time, the first Sydney Sweeney campaign was very controversial, and there was a lot of discussion around whether it would have a positive or negative impact on brand performance. There were some data providers – and I think this kind of connects to my earlier comments about sample panel bias – there were some other providers, specifically foot traffic, making headlines with very large news agencies that this campaign was having a negative impact on American Eagle.

We had very different data and information based on our insights, and we came out at the time and said that this was having a severe positive impact on American Eagle sales. When the company came out and released results, there was a big upside surprise in performance because Sydney Sweeney did have a net positive effect on the brand.

Those are two examples of where our data was applicable, but it even extends all the way to things like software companies or B2B service providers, where we can pick up on professionals’ discussion around whether they’re going to switch providers, what enterprise AI software they’re going to use, etc., and apply a similar methodology.

What’s so interesting about social data is that it’s interpretive. Like I described before with American Eagle, two people could have been looking at the same signals and coming to different conclusions about their impact on the brand. Part of what’s made Ticker Trends so successful is our ability to consistently translate the impact of those events, both directionally and magnitudinally, to how it will impact brands both short-term and long-term in public and private markets.

Bryan Wagman: Yeah, that makes sense. I’m interested in better understanding the operational flow of the company from the perspective of how you identify the data or dataset that you want to use. Are you purchasing it? How do you think about buying the data or collecting it through scraping or something like that? Then once you do have the data, how does that flow through your operational infrastructure? Are the engineers the people finding it, or are you just buying big bulk datasets and then seeing what’s in there? I’d love to understand more about how all that works.

Adrien Navarre: At Ticker Trends, we have a combination of approaches in terms of datasets. We have a lot of our own infrastructure around collecting our own proprietary datasets, some of which we’re one of the only, if not the only, provider to have. This is particularly around many of the social tracking datasets that we collect.

But there are also some datasets that we have to license from third parties. The way we view that is that Ticker Trends is not just the datasets we collect, but the infrastructure we’ve built around the utilization of those datasets. Early on, we proved that through some of the most easily accessible datasets. We could take data that’s widely available and use it more effectively than incumbents or other people in markets. Later, that translated to taking more premium datasets and applying the same methodology.

In terms of how our infrastructure operates, it’s actually very easy for us to add and maintain datasets, and take any time series or textual data, or different formats of data, and integrate it into our systems. But a bulk of our infrastructure is more around the effective utilization of those datasets in the context of financial public and private markets.

That’s what’s allowed us to be so successful. We can take any of these signals, plug them into our systems, use those datasets more effectively than anyone else, and it benefits all of our coverage, both of public and private companies.

That is very different from how some other people in the industry operate, where there’s a lot of work around each incremental dataset or a lot of work around each incremental company of coverage that they add. The system we’ve built from the ground up is very scalable in terms of the breadth of coverage we can have, and every incremental improvement we make benefits all of our coverage.

When we add a new dataset, it benefits all of the companies we track. When we make an improvement to our algorithms, it benefits all of the forecasts we’re making for public reported metrics. We’ve built a system where it can be very easily maintained and improved, and benefit all of the coverage we have across public and private brands.

Bryan Wagman: What are some of the datasets that your clients have found most valuable, and what do you find is common across those? Are there any themes that have popped up for you about what makes a dataset particularly compelling for people?

Adrien Navarre: I think what can make a dataset most compelling is a little bit along the lines of what I mentioned earlier. Many of our clients will have unique ideas and different topics that are important to them over time.

While, of course, there can always be value in very specific depth on a certain topic, like maybe having the best AI data center dataset is very valuable, for us, we think instead about having as many of our datasets cover and answer, or have an input to, as many different questions as possible.

When we’re adding a dataset, very rarely would it be to only improve one or two companies, or because it would only be applicable to one or two companies. Instead, we look at it as: will this incremental investment in our infrastructure benefit a couple hundred companies in our coverage, or ideally a couple thousand companies? Can this answer questions that might be relevant now and down the line, across many different market environments and investor focuses?

That’s come to pay off a lot. When new clients come to our platform, they look at the tools and infrastructure we’ve built, and they might have a lot of bespoke ideas and different applications for the information we’re providing for their own use case. That’s been very exciting for us, and it’s allowed us to grow so much, because since we can answer so many different questions, the way people want to leverage that data can get very creative.

That’s come from always focusing on being able to answer such a wide breadth of questions, rather than only being the best at answering one specific question that might no longer be relevant in a couple quarters, or one or two years.

Bryan Wagman: Could you share more about the different levels of the offering? There may or may not be some element of a customer journey perspective, where they move on from one to the next, but it sounds like there’s some lower-priced offering with the blog, I think, and then what you were just describing sounds like a higher-end offering where you can see all the tools and infrastructure in the background. We’d love to hear how you think about each of those.

Adrien Navarre: Yes. We initially started with a very low-cost tier early on. That was quite critical for us, because in order to iterate, we needed a large user base to get fast feedback on whether things were working and what people wanted.

Over time, as we polished that product and built new offerings within the software, we were able to move more to a professional offering, which is now our primary product.

We have one portion of the offering that is more simple alternative data tools. We’ve always wanted to keep that offering available because we believe we’re one of the only, if not the only, alternative data provider that has something for a more average market participant or investor. We believe that will always be an expanding segment as more people manage their own capital. So we have one offering for those types of investors.

Bryan Wagman: If I could ask one thing before we move on to the next one, what exactly does that look like from the client’s perspective? Is the analysis already integrated with the stock for that lower tier, or is there some sort of data-only provided offering as well?

Adrien Navarre: In the lower-priced offering, it’s more restricted on the dataset side, in terms of what information is available to the user. But it still allows users to easily connect different forms of more readily available alternative data to financial markets.

What I alluded to earlier is that when we first started the business, we didn’t have very much capital or resources to spend on datasets. So we took more readily available data, something like Google Trends, and applied that data to financial markets.

The lower-priced offering takes those more readily available datasets and gives users tools to easily connect that to financial markets, so they can use it to track companies in their portfolio or get new ideas of what stocks to invest in, without having all of the more complex infrastructure that we keep for the advanced offering.

Bryan Wagman: Got it. And so then what are the tiers after that? Is there one or two tiers after that, or how’s the rest for you?

Adrien Navarre: Above that, we have what we call the KPI Forecasting Suite. That offering is more directed toward professionals: asset managers, funds, corporates, and private investors.

Our KPI Forecasting Suite is a larger set of data sources, some of which are premium and only available through limited, if not very high-priced, offerings. We have unique datasets, and then also some of the social data and our own datasets that we’re collecting, all mixed into that offering.

A majority of our infrastructure is taking all of those unstructured datasets and translating them into actionable insights, primarily through KPI forecasting. So something like Yipit or M Science, but based more on this pre-purchase intent data, where we take pre-purchase intent data, translate it into how that will impact a reported metric, and then do that for hundreds of public businesses and increasingly private businesses as well.

That way, investors can have a direct answer to how this social event or pre-purchase intent data will impact a public reported metric from different public companies.

Bryan Wagman: Sure, that makes sense. I’m curious if there are any big pivots that your business has made over the course of the past couple of quarters. If there’s one that stands out in your mind as most recent, what would that be?

Adrien Navarre: I think one of the biggest pivots is maybe how we’ve thought about the integration of some of the language model tools into our product.

I’ve seen many data businesses take different approaches to integrating language models, and I think we have a very different approach. Most of it we don’t talk about or advertise or mention anywhere on any of our public materials. That’s quite intentional, because around some of these hype cycles around new technology, there can be many companies overusing certain words, and it tends to drown out the actual value of what they’re providing.

We’ve taken the inverse strategy, which is don’t mention it at all, but have all the benefit of it. Initially, we were thinking about how much of this is something we want the user to be able to interface with, versus how much of this is something where we’re telling them a structured output or answer.

Many of our competitors, or many other data businesses, go the route of giving the user tools to generate their own structured outputs. My opinion is that this is the wrong direction. As much as it’s very cool to be able to go into a chat interface and ask any question, ultimately, very often our clients don’t want to have uncertainty or variant interpretation, where one time you ask it a question and it tells you one thing, and the next time it tells you something else.

Very often, clients want the best answer, and they want that answer for many different things. The value that we provide is giving them that answer. So the approach we’ve taken instead is to utilize this infrastructure to benefit everything on the back end of our business. But in terms of the client’s interface and final output, they only see the final answer. We’re giving them the answer, while still having all of the benefit of that more malleable infrastructure that allows us to scale and grow much more quickly.

The way we’ve integrated language models into our business is different than many other data businesses. But so far, I think with the market validation we’ve received, it’s been the right way. It’s provided a material, significant increase in efficacy to our business by giving our clients structured outputs from language models.

Bryan Wagman: Yeah, that makes sense. I guess it’s the same data, though, and I’m just trying to think about this from a strategic perspective. The differentiating factor is the customer experience there, is that what you would say? By wanting to go structured instead of the tools approach?

Adrien Navarre: Yes. I think the user experience matters because in the data industry, determinism is very important, and accuracy is very important.

We’ve always operated in a way where it’s kind of like human-in-the-loop infrastructure. It’s maximal automation, but with a human in the loop to verify very high-importance accuracy that our clients expect.

The way clients interface with our data and information is that they view structured outputs, consistent structured outputs that answer the questions they have. How is this thing going to impact this company? What things matter for this company? What’s the performance of this business? We answer all those questions.

The way we implement automation into answering those questions is all on the back end. It doesn’t require the user to self-query or self-structure the information themselves. We’re not just throwing a bunch of unstructured information at them and letting them figure out what’s important from it. We’re telling them what’s important, how to interpret it, and what the best interpretation is of that information.

Bryan Wagman: Is the KPI Forecasting Suite, does that all apply to that suite as well, or is there more of a user-directed approach there?

Adrien Navarre: Yeah, that’s all available in the KPI Forecasting Suite. We do have tools that allow users to view more unstructured data if they decide to, but we’ve always seen that clients far prefer structured outputs and answers over unstructured data. The tools are there if they want to use them.

Many of our clients subscribe to, or have, many different datasets or pieces of information competing for their attention. They would prefer to have the best structured output at all times, rather than have to dig through, search for, and interpret the information themselves to then come to some conclusion. It’s far better for them to have those structured outputs from the very beginning.

Bryan Wagman: Going back to some of the financing discussion from the beginning, it sounds like you’ve just raised capital that one time. Is that correct? And I’m curious how you’ve thought about that as you continue to build out the business.

Adrien Navarre: Yes. Since the very initial pre-angel investment that we received at the beginning of the business, we haven’t raised any additional external capital. Prior to that, when the business was a side project, it was purely bootstrapped from personal capital.

Much of the growth in the business now has all come purely from growth and revenue of the business. As we’ve accelerated in growth, we’ve started to potentially explore other options. I very much come from the side that, since we’ve been able to grow and operate the business for so long with very minimal external capital, I believe it’s very possible for us to continue that path moving forward.

At the same time, there are certain strategic opportunities that come up at different points, which can have the dual benefit of giving us capital and also accelerating the growth of the business. Those are the things that we consider at times.

We’ve never been in a position of requiring external capital. We never ran out of money, and we didn’t need some money to get to the next point. We’ve been able to do all of that just through the growth of the business. But I think it’s very possible in the future that different strategic opportunities might come up where it makes sense for us to receive external capital to continue growing the business even faster, since we’ve hit such an inflection point.

Bryan Wagman: Sure, yeah, that makes sense. One other thing that you mentioned earlier, when you were talking about the entrepreneurial journey, was how learning to delegate was important for you. Is that something that came naturally for you, or is there anything that you picked up along the way that made it easier? Maybe it just has a lot to do with hiring good people, but I’d be curious to hear your experience in that realm.

Adrien Navarre: I think with delegation, I’ve always viewed it as being able to replicate, if not surpass, my own personal skills and ability through leveraging the knowledge of others.

Often, delegation can be hardest when you’re not confident that someone else might be more skilled than you at a certain topic or task. But what I’ve found is that as I’ve hired, I’ve always found people I believe to be better than me at these different roles. So it makes it easier to delegate the responsibility of those roles to those people while still retaining my own influence on the roles.

That’s how I’ve viewed it: find people who are better than you at the specific roles, but then you can still influence the direction and focus of those people within those roles to make them even more effective.

That comes from a long time for me personally, just because I’ve always been so time-constrained in terms of focus. I’ve needed to delegate even from very early on. When I was starting Ticker Trends initially, I was working at the robotics company, and most of the day I couldn’t work on Ticker Trends. I already, at that time, was paying a software engineer a full-time salary to work on Ticker Trends while I was doing my own job, because I knew I wouldn’t be able to make the progress I wanted if I were working on it alone.

The importance of that delegation has only increased over time. As the aspirations of the business have grown, I’ve realized that I need to keep offloading many of the responsibilities I’ve taken on, because if not, we wouldn’t be able to get to the next levels of growth for the business.

That’s been a constant process as the business has grown: pushing myself on the side of delegation, but also pushing myself on the side of creativity, of where Ticker Trends can go, to keep accelerating the growth of our business, which so far, fortunately, has been relatively successful.

Bryan Wagman: These days, when you’re looking to hire, how do you identify talent, and what does the interview process look like?

Adrien Navarre: In terms of identifying talent, most often, since these are primarily technical roles, and I don’t necessarily look for people who have worked in the industry, although we’re not biased against this, most of the time we’ve just tended not to hire from people who’ve worked in the industry.

Often, we’ll look for people who are newer software engineers looking to change into a new industry, and talent that’s very excited about technology and very familiar with new software. One thing I’ve always looked at is what people do in their free time, because that is what they’re truly passionate about. So we look for people who, when they leave the office, are doing software engineering-adjacent things or interests. That shows that they’re really naturally passionate about what they’re doing.

In the hiring process, something I’ve taken up from advice from others and some mentors I’ve met throughout growing the business is the importance of trial tasks and onboarding tasks, where you’re throwing the most difficult simulated challenges at someone during the hiring process and seeing how they respond to those challenges.

That’s been very effective: seeing an actual simulated work product and being able to evaluate that for a very difficult question, or maybe even a question that might be impossible, and seeing how they approach it. That has always allowed me to have a much better gauge of hiring before they start full-time in the position.

Bryan Wagman: Yeah, that makes sense. Well, this has been awesome, Adrien. Is there anything else that you’re really excited about for Ticker Trends, or that I should be asking about?

Adrien Navarre: No, I think for Ticker Trends, what’s been exciting about our future direction and some of this scaling is that as we’ve had more resources and as we’ve built up this technology stack, the applications for our technology have grown equally. That’s been really exciting for us.

Something we’re always interested in is when people have new ideas for our data or applications of our technology. We have some of the largest infrastructure now in monitoring these pre-purchase intent datasets across such a wide variety of data and applying it to public and private markets.

It’s been very fun to work with people who have new ideas in those realms. If anyone ever wants to come to us and collaborate on making this data and information effective for their problems, then we’re very excited to work with them and to get them using Ticker Trends.

Bryan Wagman: Yeah, awesome. Well, thank you so much for your time today, Adrien. I really appreciate it.

Adrien Navarre: Thank you so much, Bryan.

Bryan Wagman: Alright.

Some normalization is going to happen. That part is roughly right. The harder question is the magnitude and where the new baseline actually lands.

The setup: existing home sales are at a 30-year low. Movers spend roughly five times more on furnishings in their first year than non-moving owners do (NAHB). Total mattress unit purchases per household ran 0.20 to 0.26 from 2015 through 2021. They sit at 0.18 in 2024, slightly above GFC-trough levels (~0.15-0.16) on a per-household basis. The gap to a normal baseline is real, whatever “normal” turns out to be.

One more bullish version of this math, from a slide produced by a former board member/current investor and revealed in the FTC matter, makes the pent-up demand framing more concrete. They peg post-GFC under-trend spend at 25.6 million units, delayed household formation at 9.3 million, and the 2016 to 2022 above-trend bump at 26.6 million. Net remaining pent-up demand: 8.3 million units.

That’s a real thesis. The honest version of the bear case isn’t “demand is dead.” It’s: maybe the recovery is anemic. Maybe cycle relief is real but more mix-driven than volume-driven. Maybe replacement cycles have lengthened. Maybe affordability stays bad enough that turnover doesn’t fully unfreeze even if rates ease.

Looking at the bull and bear cases side by side, there are a few core facts they agree on:

• Industry units are roughly 30 percent below the 2021 peak and 20 percent below 2019 levels.

• Existing home sales are at a 30-year low.

• Promotional intensity (0% APR, 60 to 72 month financing) is critical for driving demand.

• COVID pull-forward is long gone.

• Independent retailer attrition has been brutal (United, Mitchell Gold, BB&B, Conn’s, Big Lots, LL Flooring, Mattress Land, AFM, CVB, Metro Mattress).

Both sides also basically agree some recovery is coming. The fight is over magnitude:

1. Replacement cycle. Bulls assume roughly stable 8 to 10 years, so the under-shipped reservoir mathematically clears. Bears argue cycles have lengthened (Mordor pegs ownership stretching from 7 years toward 10; the Mattress Recycling Council’s average age of discarded mattresses is 11.2 years), and the reservoir does not unwind without an income or wealth catalyst.

2. Housing turnover. Bulls see it as cyclically frozen and waiting for rate cuts. Bears think it has structurally reset lower due to the difficulties (mainly affordability) of home ownership. RH’s framing is jarring here: in 1978 the U.S. sold 4.09 million existing homes with a population of 223 million. In 2024 we sold 4.06 million with a population of 341 million. Same units, 53 percent more people.

3. Trough framing. Management is converging on “we are at the bottom” (TPX NA same-store +5%, Mattress Firm +5%, Wayfair new orders +7%, Haverty’s three positive comp quarters). The same management is also guiding 2026 to flat-to-modestly-up off self-help, not market.

4. Channel measurement. Some operators (Bedgear, South Bay) argue ISPA materially understates real demand because of DTC, putting “true” total market closer to 48 to 52M units vs. ISPA’s ~36M (!!!). ISPA participants counter the numbers are directionally right; Purple’s Q4 2025 e-commerce was down 15 percent.

The biggest disagreement, the one most of the others depend on: is the cumulative under-shipment of mattresses deferrable or destroyed? Bulls treat it as a reservoir. Bears treat it as wash, because consumers replace later from a longer-life base (or perhaps already did with mattresses not caught in ISPA data).

I don’t have a confident view on the magnitude.

What would push me one way or the other: sustained sub-6% mortgage rates with a durable rebound in existing home sales, ISPA mattress unit growth that is unit-led not ASP-led, and management commentary shifting from value/promotional/lower-traffic to sustained units with reduced promotion. If we get any of those without the others, I want to know which one is doing the work.

Appendix: how I tried to answer this

I ran the same deep research prompt through both ChatGPT and Claude. ChatGPT came back with a clearer point of view (partial cyclical recovery, not a simple snapback). Claude did not really take a stance, but its decomposition of where bulls and bears actually disagree was useful and I leaned on it above.

Including the prompt below in case anyone wants to run a version of this themselves.

The prompt

I am researching the mattress and furniture industry, with a focus on whether the category is likely due for a meaningful cyclical snapback or whether forward growth is more likely to be structurally muted/anemic.

The core question: are mattresses and furniture genuinely set up for a major recovery as housing turnover normalizes, or has the category’s normalized growth rate/volume baseline changed in a way that makes the “snapback” thesis too simplistic?

Please research this deeply and produce an investment-oriented memo.

Companies to keep in mind: Somnigroup / Tempur Sealy / Mattress Firm, Leggett & Platt, Havertys, Arhaus, RH, Wayfair, La-Z-Boy, Ethan Allen, Williams-Sonoma / Pottery Barn / West Elm, Ashley Furniture (private), Serta Simmons / Beautyrest, Purple, DreamCloud, Nectar, Resident, Saatva, Casper.

Key questions:

1. Historical demand relationship to existing home sales, new home sales, housing starts, household formation, mortgage rates, affordability, consumer confidence, disposable income, credit availability, remodeling, and moving activity. What share of demand is move-driven vs. replacement? How long are real replacement cycles and are they lengthening? Did COVID pull-forward suppress replacement for years?

2. Is there a real deferred-demand pool, or has demand been lost? How does big-ticket home compare to autos as a deferral category?

3. What is “normal” volume now? Use ISPA, Census, retail sales, trade association data. Estimate whether normalized real volumes are below, equal to, or above 2019.

4. Structural changes: DTC, online price transparency, value brand share, financing availability, household formation, smaller homes, mattress-in-a-box, Mattress Firm post-Somni dynamics, private-label mix.

5. Housing turnover sensitivity. How much upside if existing home sales normalize? How much is already priced into bull cases? Can replacement recover independently?

6. Retailer and manufacturer commentary on traffic vs. ticket, units vs. ASP, premium vs. value, financing, promotions, inventory, replacement, housing, move-related demand, trade-down, online vs. store, recovery timing.

7. Industry-level data sources (ISPA, Census, BEA, FRED, NAR, JCHS, NAHB, transaction data summaries).

8. The strongest version of the bull case and the 3-5 data points that would confirm it.

9. The strongest version of the bear case and the 3-5 data points that would confirm it.

10. Investment implications by company, without giving investment advice.

Output: executive summary, bull case, bear case, evidence table (point/source/supports/why/reliability), company exposure table, key charts to read, follow-up questions, source list. Be skeptical. Treat “housing depressed = snapback later” as the hypothesis to test, not the assumed answer.

ChatGPT executive summary (verbatim)

The weight of the evidence supports a partial cyclical recovery, not a simple snapback. Housing turnover is unquestionably suppressing demand: existing-home sales remain near multi-decade lows, mortgage rates are still above 6%, and movers spend sharply more on furnishings than non-movers. But the category is not just waiting for housing to normalize. Public data and management commentary point to a market that has also changed structurally: COVID pulled forward demand, mobility has been falling for years, replacement cycles appear to be lengthening, online and value channels have increased price transparency, and several operators are winning through share gain, assortment, and channel mix even while the category itself remains soft. My base case is that mattresses recover earlier and cleaner than furniture, but both categories likely normalize to a slower, more mix-driven, more promotional baseline than the bullish “snapback” narrative usually implies.

Confidence: moderate. ISPA’s full data sit behind member-only reports, and there is no clean public source that splits demand into mover/new-household versus replacement.

What would change the view: existing home sales rising materially for several quarters, ISPA mattress units turning clearly positive on a real-unit basis, and company commentary shifting from “choppy / lower traffic / value-oriented” to sustained unit growth with lower promotions and better premium mix.

The landscape has changed

The first thing worth saying is that the landscape has changed. What is happening now has been building for the better part of a decade, and I think it is going to become a lot more obvious from here.

The big pod shops get a lot of the attention, and for good reason. No one is investing the same level of focus, resources, and rigor into identifying and developing talent as these firms. They are playing a somewhat different game than the rest of the industry.

I’ve had less direct exposure to that world than I have to single managers and long-only shops, and I have fewer contacts there, so take this with that caveat. But from where I sit, the basic logic is pretty clear: in a high-churn, performance-driven, increasingly mercenary business, especially at the more senior levels, pedigree matters because it lowers perceived risk. If you are hiring at scale into an environment where not everyone will make it, the natural tendency is to favor people with stronger credentials and backgrounds that suggest they will be relatively plug-and-play.

A clarification on “pedigree,” because I’ve gotten pushback on this and I think the pushback is right. At the undergrad level, the pods are actually some of the least pedigree-driven recruiters in the industry. The biggest academy programs are pulling from state schools and non-target campuses at a rate that would surprise most people. These firms are casting wide nets and selecting on raw talent and reps, not school logos. That is genuinely impressive, and worth watching.

The more interesting thing is what happens over time. Because the big pods are doing the most rigorous work around figuring out who is actually good at what and why, they end up producing the people with real, legible track records. At more senior levels, that becomes its own form of pedigree — not where you went to school, but that you ran a book at one of these firms and the numbers are verifiable. The pods have effectively replaced the old credentialing system with their own.

That matters for the rest of the market. If you are a single manager trying to hire, the pods are identifying raw talent earlier than you at the junior end, and producing the only verified track records at the senior end. The talent funnel is narrowing from both directions.

That dynamic is well understood. What I think people underappreciate is how much it is changing the rest of the market too.

Most of the students I talk to are not only thinking about pod roles. They are thinking about the full landscape: pods, big long-onlys, single-manager long/short funds, single-manager long-only shops, and the long tail of RIAs and adjacent firms. But even outside the pods, the pods are increasingly shaping the talent market.

Everyone says entry-level buyside roles have gotten more competitive. That is obviously true. But it has become even more apparent to me recently, and I think one major reason is that the large pod shops have become much more intentional about talent development. Point72 Academy is the clearest example. BAM has moved in a similar direction. Whether that is because these firms are identifying talent earlier, or simply because they have gotten so large that their influence spreads more naturally, the result is the same: training that used to be more contained is now diffusing outward through schools, clubs, and student networks.

I do not remember seeing this to the same degree when I was in school.

Today, an undergraduate can get good much faster than before. The general level of the game has risen, as it naturally does over time, but there is also a specific institutional transmission mechanism at work. A strong student goes to Point72 or BAM for a summer, comes back to campus, and teaches others what they learned. Then maybe two students from that school get those seats the next year. Then more. It compounds. And because these firms have more seats than most single managers, their practices and expectations end up influencing the broader pipeline in a way that a great single-manager fund often cannot.

The effect is not just that students are more polished. In many cases they are learning to do real investment work earlier. They are learning how to generate ideas, how to frame a thesis, how to ask better questions, how to research more rigorously. The best shops are not just running smarter internships. They are investing in talent formation itself. In many cases, they are also treating internships more seriously as learning environments instead of as prestige filters or low-level grunt work.

External resources have improved too. BIWS was very useful for learning Excel and modeling. But a platform like Brett Caughran’s Fundamental Edge reflects something important: there is much more to being a good investor than knowing how a DCF works. The overall ecosystem around analyst development is just better than it used to be.

That is the backdrop. Against that backdrop, I have noticed something interesting in the questions students ask.

The wrong question

A lot of them are asking some version of: am I going to pigeonhole myself if I choose X instead of Y? Long-only or long/short. Pod or single manager. Generalist or specialist.

I understand why people ask that. But I think it is the wrong framing for the vast majority of people.

The question assumes you can map your trajectory in advance. It assumes you know which jobs you will like, which environments you will perform in, which seat is “right,” and how each choice will shape the next one. A very small number of people probably can think that way. Usually those are the people at the absolute top of the pedigree game, the ones who have already demonstrated such a high level of performance and competitiveness that betting on a tightly managed path may make sense. That is a different game. I tried, briefly, to play some version of that game myself before realizing it was not going to work for me.

For most people, though, it is a bad way to think.

One reason is existential: a lot of people do not even know why they are doing what they are doing. They are pursuing a path that is legible, impressive, and high-paying, but have not really stopped to ask what they want, what sort of life they are building, or what tradeoffs they are implicitly accepting. I will not go too far down that road here, except to say that The Pathless Path should probably be required reading for graduating students heading into high-status careers.

The other reason is practical. This career strategy is fragile. It works very well for a small minority of winners. But for the majority of people, it creates bad outcomes. If you burn out, get pushed out, end up at a mediocre firm, or simply realize too late that the path is not a fit, it can be hard to recover. In this excellent interview, Derek Pilecki touches on the challenges of this industry down the line:

“If you lose your job anytime after the age of 32, it’s hard to get another job, right? Once you’re off the track, you’re done. And the business doesn’t hire mid-career analysts. There’s a lot of people who get into the business and then in their 30s or 40s have to go find another career. And so I think it’s risky from that standpoint… I think that’s, there’s some things that people don’t talk about. Like I’ve had a lot of friends who lost their job in their late 30s or 40s and weren’t able to find a new seat. And they struggle. So while the rewards can be great on the upside, it can really mess with you mid-career, midlife, you know, you have a young family and you’re trying to reinvent yourself. That’s a real possibility. That’s brutal. Yeah, absolutely brutal.”

What to optimize for instead

So what should you optimize for instead?

I think there are three things.

1. Focus on your ability to provide value

This is what people making hiring decisions are actually trying to assess, whether they articulate it that way or not. The currency of this business is ideas. If you are talking to an analyst or PM and you show them something interesting in their wheelhouse, they cannot help but pay attention.

I continue to be surprised by how many people apply for analyst roles without managing a personal account, without having stock ideas on hand, without any real evidence that they are actively practicing the craft. It is the equivalent of applying to the orchestra without ever having played an instrument.

But it is worth being specific about what “value” means here, because not all research is created equal. Differentiated primary research is important. Everyone has access to Tegus and the same expert network transcripts. What stands out is the person who digs up a data source the sell side is not using, files a FOIA request, calls distributors, walks a competitor’s store. That kind of work reads completely differently — and PMs can tell.

The real gold standard, though, is differentiated research that actually drives the stock. There is a difference between finding an interesting data point about a company and finding the data point that the stock trades on. A creative alt-data source on an insurance company’s affiliated exposure percentages is interesting work, but if the stock does not move on that metric, it is an academic exercise. The same effort pointed at a company where the market is specifically debating unit growth or churn or pricing — and where you have a proprietary read on it — that is what people will pay for. Understanding what a stock trades on is half the battle.

If you are reaching out to an investor, send ideas. Attach three stock picks. Put a line or two on each. Tell them which one you think is most relevant to their strategy and why. Make it easy for them to evaluate whether you can contribute. If it is in their wheelhouse, they can assess it quickly. And if you demonstrate that you can provide value, they are much more likely to hire you, help you, or remember you. Even if they are not hiring, it is often a positive-EV interaction because good talent is hard to find and people tend to want to help when they see the real thing.

2. Focus on team

More specifically, focus on the people you will actually learn from. Who are you reporting to? Who are you working alongside? Who is going to teach you what good looks like? Who is going to help sharpen your judgment, your process, and your standards?

That matters more than most of the abstract career-path questions people obsess over. The right team can accelerate your development enormously. The wrong team can leave you with the title and logo you wanted but without having learned how to actually do the work. If you cannot find those people around you, look elsewhere. They do exist. Some are at funds. Some are on the internet. Some are on FinTwit. Some are building in public. Build relationships with people who have real edge and figure out what is valuable to them.

3. Build antifragility through network and personal brand

At some point over the next twenty years, most people reading this will find themselves in some kind of bad work situation. They will be fired, laid off, stranded in a bad seat, stuck at a firm that is deteriorating, or trapped in a role they should have left earlier. That is normal. The people who navigate those moments best are often the ones with a real network and some kind of reputation outside the four walls of their employer.

Creating content is, in my view, the best way for an individual to build that today.

Yes, compliance can make that difficult. But there are still windows where it is easier: when you are in school, between jobs, or in roles with more flexibility. And not everything you publish needs to be a stock pitch. You can write about industries, process, books, lessons, career observations, interesting business history, or even adjacent personal interests. The point is not just audience growth for its own sake. The point is to create surface area for luck, relationships, and future opportunity.

One clarification

One clarification here: this is not equally true across all professions.

In many careers, the traditional formula still works pretty well. Good school, good grades, good job, strong pedigree. If you go into FP&A, accounting, investment banking, law, or other more legible professions, that path is often still a fairly good bet if your goal is stability and paying the bills. You can still benefit from the three principles above, but the baseline system gives clearer feedback and is generally more reliable.

Public equity investing is different.

Public equity investing is much closer to an apprenticeship model. Performance is harder to judge than people want to admit. The pods, in my opinion, do a relatively good job of evaluating talent. But many single managers, larger asset managers, and adjacent firms do not really know who is good at what, or why.

In most professions, if you are doing poor work, you eventually know it. Someone tells you. The consequences show up more clearly. In investing, that is not always the case. There are people who have destroyed value for long periods of time and still remain employed, respected, and well-paid. It is a strange business. I have always thought it is closer to being a musician or an athlete than to being an accountant. It is much harder than people think to tell whether you are playing at Madison Square Garden or just in the garage.

What to do once you get the job

And what you do once you get the job matters just as much as what you did to get it.

Be brutally honest with yourself

Write down why you took the role. What did you think the pros and cons would be? What did you expect to learn? What did you hope it would unlock? What parts of the job did you think you would enjoy, and what parts did you suspect you would dislike? What were your financial goals? Were you trying to build a long-term home, or was the role mainly a stepping stone?

Then revisit those answers every few months.

Do not let inertia make decisions for you. Bring a few trusted people into the loop if you can, ideally people who understand both you and the industry well enough to call you on your nonsense. The point is to force a level of self-honesty that most people avoid until it is too late.

Do not stop networking once you land the job

A surprising number of people treat networking as something you do only until you “make it in.” That is a "cardinal mistake” as Jerry Diao/Richard Toad put it. You need to keep building relationships even after you get the seat. The industry changes too quickly. Your own goals may change. Your firm may change. Your assessment of what good looks like may change. Keep talking to people. Keep learning. Keep comparing your internal reality to the broader market.

And finally, AI

Hardly any of the students I talk to are asking about it. I do not fully know what to make of that, because I do not have a great read on their actual capabilities. But my own view is simple: if you are not already very good with these tools, you need to get good fast.

I recently spoke with a fund manager running more than $1 billion who let go of all of his juniors and replaced them with AI. That does not mean every firm is about to do that. Most are not. But it does mean the bar is moving. You want to be on the side of the people who know how to use these tools, not on the side of the people whose work is easiest to replace with them.

That means understanding what AI is good at and what it is not good at. It means learning how to prompt well, how to verify output, how to integrate these tools into research workflows, and how to use them to increase your speed and range without dulling your judgment. One of the clearest ways a junior person can add value today is by becoming genuinely useful on this front and then helping a team adopt these tools in a way that is actually practical and politically aware.

Almost every firm could be doing more here. Many are moving in that direction. Most are still figuring it out in real time.

The broader point

For most people, the right question is not: “Which path perfectly preserves my options?”

It is: “How do I become someone who can create value, learn from the right people, and stay antifragile in a difficult industry?”

That is a much better game to play.

If you run a fund and any of this resonated — the difficulty of identifying talent, the narrowing pipeline, or just the reality that hiring well takes time you do not have — I would like to talk to you. I am trying to learn how hiring works at different types of firms and where I might be able to help. Or if you run a university investing club and want your students on my radar, reach out. DM me on Twitter (@stockthoughts81) or email me (stockthoughts81@gmail.com).

If it’s easier, you can book a call here.

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Jerry Diao is the founder of Richard Toad — the go-to resource for anyone trying to break into or navigate the public equity research industry. He’s built a subscription job board, a fund database covering 1,000+ U.S. hedge funds and long-onlys, and a networking course — all bootstrapped, vibe-coded with AI, and scaled through content.

Before going full-time as a creator, Jerry worked in actuarial consulting at Towers Watson, went to NYU Stern for his MBA, interned at a deep value hedge fund, and spent two years covering SaaS at Wells Fargo equity research alongside the famed bank analyst Mike Mayo.

We covered a lot of ground:

• Jerry’s Background — The underdog-to-Wall-Street story (Shanghai, Cal Berkeley, wrong major, actuarial exams, Moody’s, NYU Stern, Wells Fargo)

• Actuarial Role + Transferable Skills — What healthcare benefits consulting taught him about mentorship and professionalism

• Leaving the Startup Hedge Fund — How he came to terms with a bad fit and cut losses

• Mental Health: HF vs Entrepreneurship — Resilience, nonlinearity, and the acceptance of turbulence

• Richard Toad Business Overview — Job board, fund database, networking course, and the power of reduction

• What Jerry Cut From the Job Board — Why he dropped public credit coverage

• Vision + Delegation + Lifestyle — AI replacing contractors, VA unlocking morale, and the recruiting opportunity

• Investor-to-Creator Trend — Why hedge funds are going on podcasts (talent, succession planning, and private capital TAM expansion)

• Process on Podcasts vs Deep Stock Dives — Dan Sundheim, Cliff Sosin, and the value of sharing process

• Biggest Mistakes: Industry Insiders — Reactive job searching, not networking, and underestimating personal relatability

• Biggest Mistakes: Breaking In From Outside — Stock pitch requirement, no recruiting season, and building an online brand

• Advice for Emerging Fund Managers on Hiring — Talent degradation, posting in the wrong places, and owning your audience

• Where to Find Jerry — “Inside Equity Research with Richard Toad” newsletter

Full Transcript

Or listen on Spotify:

INTRO + JERRY’S BACKGROUND

Bryan: Thanks again for taking the time today, Jerry. I really appreciate it, and really looking forward to speaking with you, and it would be great if you could just kind of give our listeners a little bit of an overview of you and your story, and how you got to the position that you’re in today to kick things off.

Jerry: Awesome, thanks, Bryan. A real, real honor. Yeah, so I have... there’s two versions of me. So maybe I’ll go with my brand first — I’m the founder of Richard Toad. I’ve been running it since April of 2020. But now, let’s take a step back and introduce who I am as a person.

My name is Jerry Diao. I went to... I’m from China originally. I am from Shanghai, which makes it easier, because I don’t need to introduce where that is. I came to the States when I was 15, and went to Cal Berkeley. So my story has always been kind of the underdog to Wall Street story.

Picked the wrong major, had really bad grades in college, and I saved my career by passing this thing called actuarial exams, because I was a statistician by training. So I had to save my career at the very beginning by having to take these very gruesome exams and landed an actuarial consulting job as first job out of college. That’s where I worked in San Francisco.

After the first job, I went to New York City, and that — still looking back — is the best career decision ever in my life so far. The last job before my MBA at Moody’s, I met my colleague, Eric, who sat in front of me. It’s really funny — there were the four of us sitting in the same row. I became a creator. The girl sitting behind me, she’s a creator too — she has like 10x the following as I do, doing dog accounts. So it’s really interesting.

Eric sat in front of me, he introduced me to stock research, and now Eric is a very close friend, and he will come back to the story shortly. At the time, I was pretty hooked into stock research, read all the very marquee books in investing that tends to be value-oriented — the Margin of Safety, Intelligent Investor, and The Most Important Thing by Howard Marks.

So I thought it was kind of the good juncture to use MBA to rebrand, given I was a purely technical training person with no business background whatsoever coming out of undergrad. So I went to NYU Stern, and I interned in Sales Equity Research, covering cable and media. Second school year during MBA, I worked at a deep value hedge fund for a founder who began his career working for Carl Icahn.

That was a very interesting experience. After MBA, I was kind of trying to get into this research space, so most MBA students will hedge by recruiting for both sell side and buy-side research. Because there are only that many jobs, and that’s particularly true for MBA.

I asked Eric to refer me to Wells Fargo, where Eric was working for the famed bank analyst, Mike Mayo. I ended up getting a job covering SaaS software. Eric became my colleague the second time.

I worked on the sell side for 2 years, and left Wells Fargo in 2020, and moved back to California to join a startup hedge fund. Over time, it realized it was a really, really bad fit. So I left in early 2022.

That transitioned me into this whole social media side of things. So the genesis is, in 2020, not when I started a hedge fund, but when I started on — as I end my sell-side career — during COVID, I was getting anxious about getting into the buy side, and I really wanted to vent about sell-side research, about how the misalignment of incentive, how ridiculous the profession is. Obviously, most buy-side investors trash the profession on a daily basis, and so I wanted to do that.

I went and did it. It’s really funny, because I don’t know why I decided to use Instagram, because Instagram is actually the worst platform for text-based memes. But I just did text-based memes — kind of the insider overheard type content in text format — and it really resonated.

I was doing a lot of things that didn’t scale. At the big players — like the Litquidity, the High Yield Harry of the world — but one account called TradesandRaids, he started reposting my stuff, and that was kind of the initial crossing the chasm and got the snowball rolling. So, one to two years in after I started creating on Instagram, most people who work in sell-side research globally have become my followers.

Fast forward to 2022, after I left the buy side. I thought about just finding a better fit, buy-side job. It had to be open to location. Had conversations with Boston, New York, Miami firms, but I thought about it — I’m into my mid-30s, I just didn’t want to relocate.

I was talking with a few of my friends, and one of my friends who still works on the buy side, Justin, he said: “You know, you got this massive following. I know you never thought about monetizing or becoming an entrepreneur, but why don’t you just give it a shot?”

He kind of ignited something within me of the whole Jeff Bezos 80-year-old deathbed comment. It’s like: you’re looking back, you got this social media following, you know you’re helping people for free, you’re clearly effective, and you’re doing this at scale thanks to internet and today AI.

So I said okay, I’m just gonna go for it. I really had no idea. But I’m not gonna dive deep into how I found product-market fit. I said okay, I didn’t have much to lose — I was making zero income. So I went founder mode. And 4 years later, I’m consistently doing 5-figure monthly revenue, and kind of here we are. Product market fit, followership still growing, have gone through multiple algorithm changes where I stopped growing and then re-accelerated. That’s my story.

ACTUARIAL ROLE + TRANSFERABLE SKILLS

Bryan: So many interesting pieces to that. There’s two that I want to follow up with. Your first role, the actuarial role — I’d love to hear more about that and just what that experience was like, and if you feel anything that you learned there is transferable into either investing or what you’re doing today.

Jerry: Oh, man, that’s a great question. The short answer is, there is still a fantasy football league of the people that I work with out of that first job. The firm is publicly traded — it’s called Towers Watson. They’re one of the biggest — if you know like Aon and Marsh McLennan, they’re the competitor.

It was 2026, so I joined in 2010 — it’s like 15 years running, so I still have these friends who I play fantasy football. That tells you a lot about the relationship.

My role there was healthcare benefits consulting. Think about when you work at a big company — you get benefits. The big company, what you didn’t know is they actually set aside a pile of money to pay expected claims of their employees. That’s called self-insurance. We as actuarial consultants help them set the rates for how much to reserve for expected claims, and what is the contribution strategy — how much the employer will set aside versus how much you will pay out of your paycheck as the cost sharing between the employee and the employer.

We do a lot of other things. One of the things we do is called plan design — in the medical insurance environment with the politics. We don’t want to increase the rates too much, so we have to think about increasing the copay, increasing co-insurance, narrowing the network. There are a lot of things that you can do to advise big employer sponsors as to how to reduce costs or reframe the cost increase.

So many of my good habits as a corporate professional today, even today as an entrepreneur, came from that role. I had so many great mentors, not just from the technical skills, but also from just understanding what your responsibility is as a junior or a senior person at any organization, whether that’s a hedge fund or a company or an entrepreneur. I’m so grateful I met some of the greatest mentors in my career from that job alone, and one of whom wrote my MBA recommendation letter.

LEAVING THE STARTUP HEDGE FUND

Bryan: And then the next stop I wanted to ask about was just your experience joining a startup hedge fund. I’d love to hear more about, you mentioned that it wasn’t a good fit, and I’m curious, maybe more specifically, just your process of coming to grips with that, and then how you decided to take action.

Jerry: So first part is — you can’t change external factors. In this case, you’re working for somebody — so I worked for two people. Combined, they have like 25 years of experience. They came from the same firm.

I’ll say the short answer is, it’s the same thing as what I do today as a creator and an entrepreneur — I just was fighting really hard to be useful to them. I couldn’t come up with the next company that will beat earnings, or come up with the next cheap, actionable idea because of some geopolitics — my boss is a basic materials energy guy.

I came to terms that: one, I couldn’t change how they think about investing — they wouldn’t suddenly be thinking about 3-5 year earning power of a business. And the other part is, there’s a gut feeling — once I understood well enough that the style they operate under at the firm and at their predecessor firm is precisely what I did not want to be involved in at all.

The short answer is they came from a firm that is what I call a single manager multi-manager style — think like a Holocene Advisor. There’s a single founder, but they have sector heads, and my big boss/PM was one of the sector heads who was also a partner. That just didn’t work for me. I very quickly understood they were a low net, high portfolio turnover long-short.

There’s a gut feeling that I just gotta go. If you know you cannot add value — and because I was set in my ways as well — I knew I was making no effort to converge to ever being super useful to them. That’s detrimental to the firm. There’s no career prospect for me, and it’s a waste of time for them.

I think the optimal way is to cut losses, like an investor, and just say let’s part our ways. I talked to a few people whose opinion I respect, and they say, yeah, in this situation you should just leave. So that’s what I did.

I have absolutely zero regret about it. My mental health was better, I was forced into this entrepreneurial situation, which I brute forced my way into making it work. When you know it wasn’t working, it wasn’t working. There was no path of it changing.

MENTAL HEALTH: HEDGE FUND VS ENTREPRENEURSHIP

Bryan: You mentioned your mental health improving after you left a hedge fund, and then entrepreneurship obviously comes with a lot of its own uncertainties and stresses. I’m curious to hear more — how would you compare the two?

Jerry: There is a lot of similarity between entrepreneur, investor, founder and creator. Creator is also a zero to one. You’re all evaluated on outcome. You can work 80 hours and generate no alpha. You can do a lot of content and get no views. You can do a lot of things and generate no revenue as a founder because you have no product market fit.

All of them have the great thing — some sort of leverage involved. Hedge funds is leverage of other people’s capital. Founder is leverage of so many things — if you raise financing, other people’s capital, you have labor that don’t get equity, so you’re getting leverage out of labor. As an internet founder, you get leverage out of internet, LLM. Creators same thing — internet, LLM, you can hire people to 10X. All the big creators — Alex Hormozi, Cody Sanchez, MrBeast — they all have a team. They’re a content machine.

The mental side — it’s similar too. You gotta be resilient, you gotta be resourceful. There are obviously a lot of people who tell you you should never give up, and that’s completely true. But if you don’t give up and do the same thing, you will just continue to fail.

There’s this part of paying attention to what your audience and customer want. For investors, you’re paying attention to: under that pattern, you made that decision, that clearly turned out to be wrong — how do you improve your investment process to be more protected from your own intellectual blind spots?

Over time, yes, there’s gonna be unforeseen errors, but at least you don’t make another unforced error because you keep making the same mistake. That actually gets you fired.

Acceptance of nonlinearity. When you work at a company — well, for a hedge fund, you do have a base salary too, but that’s not what people go to hedge funds for. There’s some downside protection. But entrepreneurship is probably the most extreme — there’s no downside protection.

You have to accept things gonna be up and down. Having worked at a hedge fund prepares me really well, because you have portfolios that were always moving in total value. As an entrepreneur, today I made $500, tomorrow $600, and sometimes it’s a weekend where people don’t want to pay for things, and then suddenly Monday it surges — I see it on my Stripe every day. The acceptance of turbulence — that’s very transferable on the mental side as well.

RICHARD TOAD BUSINESS OVERVIEW

Bryan: Can you give us an overview of what the Richard Toad business looks like right now, and how that developed over time? What are the different components, and how did they come about?

Jerry: Today, mainly three parts. The first product-market fit was the subscription-based job board access. I might be the only person in the industry that sells to job seekers. I think most job boards monetize on the employer side. But the product is just so effective in maximizing shots on goal to people that a lot of college students and people inside and outside the industry both value what I do.

Because I was a creator at start, entrepreneur second, my distribution was already there — I just didn’t have a product. Really quickly, as I reached product market fit — talk about 3 to 4 months — I knew the numbers were big enough for me to go full-time.

Bryan: You knew from the viewership numbers you were getting?

Jerry: Oh, no, just from the revenue number. Once I start launching the product, given I just promote on my Instagram and my newsletter who are all in the industry — they’re like, “oh my god, this product.” Even people in the industry, they’re like, “if you want to break into public equity research globally, this is the guy, this is the product.” People didn’t do that because I pay them — people do that because this is something that genuinely helps them.

I doubled my revenue last year because I’m paying attention to where people have problems. I launched a fund database — doing the dirty work of literally digging through all the public filings of a thousand plus U.S. hedge funds and long-onlys across regions. Categorize them by style, founder lineage, and region.

Because on that finance forum, a lot of college students are asking “hey, I want to recruit in Atlanta — who are the hedge fund players there?” I know these things, they’re already in my head, it’s just not systematized. So I launched that as the paid tier of my newsletter.

The third part is the networking course. I teach my audience how to do the diligence work I am sharing with them in the fund database — how to read a Form ADV Part 1, Part 2, what to dissect to get insight as to what’s their strategy, what’s the founder’s name. It’s all in the public filings. But the raw data extract is actually 15,000 funds, only of which 900 to 1,000 are actually public equity funds — because private equity, wealth management, all these alternatives also file Form ADV. That’s my value add — I know who is actually a public, institutional, public equity, active investor.

In that course, I teach how to diligence funds and how to present yourself and how to get liked by hedge fund founders so that you might just tip the scale against the Ivy League who have private equity experience.

How I build the product — I built it and refined it over time, because as a creator I know it’s better to launch, get feedback, and refine. AI/LLM only help me, not hurt my business. I didn’t know how to code — a lot of the underlying tech stack is just HTML, CSS, and JavaScript, and I knew none of that, but I just prompt and dynamically fix as I want to improve — add a button, add a filter, make it sortable.

You know this as an investor — success in investing, creator, and entrepreneurship actually comes from reduction, not addition. Over time, I want to do less products and do those products the best in the industry. Like cable stocks — ARPU, sub, lifetime value, CapEx — that’s pretty much the gist of the story. It’s about reduction.

Earlier this year, I’m already shrinking the scope of my job board. Turns out not many people left because of my shrinkage — it saves me a lot of time in terms of executing the product on a daily basis.

WHAT JERRY CUT FROM THE JOB BOARD

Bryan: What did you decide to cut out of the job board?

Jerry: When I launched the product — knowing the industry is very small and shrinking — I wanted to maximize the addressable market by covering public equity, and I am qualified to cover public credit, because public credit doesn’t tend to need investment banking experience. They can come from just having worked at a rating agency or coming from public equity research.

I always marketed the job board as equity research job board, so it makes no sense to say “we also cover public credit.” There is a competitor in the market that is lumping private credit and more deal-driven credit roles with public credit.

Some people signed up just for my public credit value add, and they kept on paying for it. But from the website views, I noticed most of my customers aren’t even clicking on the credit side of the job board at all. So I was like: if I lose a few hundred bucks a month, and I save 30 minutes executing that on a daily basis, then it’s a good trade-off — I can easily make it up by making the equity side better.

VISION + DELEGATION + LIFESTYLE

Bryan: As you think about where you want to take the Richard Toad business over the course of the next couple of years, what gets you most energized? From a business perspective and also from a lifestyle perspective — are you starting to get into delegation and automation?

Jerry: I actually can answer the second part first. I do have two contractors — they’re not 1099 employees, I’m using freelance platforms. Unfortunately, I’ve been stealing work from them because of AI. There’s a task where I need to repeatedly download a PDF file 200 times by inputting different names, and I just asked ChatGPT to write a Python code and it works perfectly. So I’ve been stealing some billable hours from them.

In terms of delegation — my virtual assistant has been incredible in amplifying my message across platforms. I create one piece of content, and I post on four platforms on a daily basis. Sometimes it goes viral on one platform, sometimes on another. By spreading my own shots on goal, it’s been really helpful for my brand. Operationally, it’s just really mundane to schedule those content across four platforms myself. That’s been a huge morale and time unlock. The morale part even bigger — you gotta do stuff where you add value the most.

In terms of vision — we’re finance people, we like to make more money, let’s not be hypocritical. But at the same time, I want to do things well in few areas. I do see a big opportunity in recruiting. That’s natural by the fact that I own the entire sell-side research audience, and increasingly on LinkedIn at least, all the major banks’ director of research and hedge fund founders are my LinkedIn followers. There’s something I can do by being that bridge between the two. Executing that is the hard part.

The other vision is, I do love learning myself. I want to benefit others, at the same time grow my written following both on a free and a paid basis. So there’s more angle on the paywalled newsletter side for sure.

Lots of optionalities because you’re a creator, you have a distribution. But all require execution. I was just focusing on doing the things I already have product-market fit really well.

We talk about removing the credit side — to compensate, I expanded geo coverage over the last two years since launch. Since January 2024, I’ve added coverage of Canada, UK, and APAC jobs in major financial hubs. Over time, there’s definitely opportunity to profile UK market, Hong Kong market, which is a really big market.

INVESTOR-TO-CREATOR TREND

Bryan: Another topic to touch on — this transition we’re seeing a lot of people make, or the blending of the lines between hedge fund founder/employee and creator. You’re seeing more and more hedge fund founders starting to go onto podcasts. What’s your view on what’s going on here?

Jerry: A few things. One — you have to sell. Things have changed in terms of the labor market. People know money is not relatively going into public market, and one part is deservedly — most funds don’t deliver what they promise clients.

Increasingly, the laborers are coming from the younger generations. They need to be sold that hedge funds are a place — because hedge funds and public equity in general have always operated under the assumption that secrecy is actually good. People don’t know what the hell they do and how the hell they do it.

The founders realized: “Oh, we’re losing this candidate to some VC funds, or to Anthropic, ChatGPT, OpenAI, or some hot startup.” That’s a fact. Compensation only — these AI companies are paying a lot. I’m not a big believer of pay. I believe in ownership of something that grows. But most people are still motivated by upfront pay, and even upfront, the startup world is very competitive. Not to mention, they by definition need to attract VC funding, they’re marketing like crazy. They have a lot of publicity, they’re well understood what problem they solve.

All these public equity funds understand that, noted that. Podcasts as a business concept is really taking off. There’s a lot of money in podcasting, so all these podcasters are competing to get the best guests. Who’s the winner when there’s so many competing podcasts? It’s actually the audience, because we get access to Dan Sundheim going on 3 podcasts, Todd Combs going on podcasts. These people never talk for an hour on their story, how they invest, all these lessons that take them decades.

One is they want to market their brand, creating more understanding. The other thing — all the public investors understand where the money is, and as part of the marketing into a different audience, they’re going on podcasts to pitch a vision of them getting a TAM expansion into the private side.

Why Dan Sundheim went on Cheeky Pint is because he’s raising $2 billion of private money to do pre-public. Because there’s abundance of private capital today, companies are shifting to appealing to the private player, and the public investors have less company to invest in. They need to get earlier in the fundraising cycle, by doing growth equity or pre-public financing to get ownership before they go public, by which, by then, arguably some of them the upside is completely gone.

The venture capitalists, to the extreme, have a dedicated media company inside the venture capital firm.

Another thing — the hedge funds and mutual funds need to market because they need to attract enough talent to think about succession planning. A lot of the funds still haven’t — it’s still run by the original founder. Some of them have — Lone Pine has, Viking Global has — but Coatue is still run by the Laffont brothers, Tiger Global is still run by Chase Coleman.

Over time, it’s not sustainable because this is a young person’s game. If you can’t get enough talent in the pipe, who will be the next wonderkid to take over the firm?

From my vantage point, people always know that the candidates have trouble getting to the hedge funds, but I know the hedge funds actually have trouble finding candidates, too, especially when their criteria is so rigid. So by going on podcasts and marketing how they invest, their process — it helps find aligned candidates more easily at scale. When you go on Invest Like the Best — you know the audience is very relevant — a lot of them want to work at a hedge fund.

PROCESS ON PODCASTS VS DEEP STOCK DIVES

Bryan: I’m curious if you think there’s a trend, or maybe even an opportunity for some hedge funds to start to shift the way they approach this mystique and secrecy thing. If you compare it to the tech world — Lex Friedman with people from OpenAI or Anthropic talking cutting-edge research for hours. Even though it’s great to have fund managers on podcasts, a lot of it’s kind of like marketing. You’re not gonna have a D1 analyst come on and talk about the latest stock. Do you think there is any trend toward more value-additive content?

Jerry: I think there is value-add. Just by mere fact that you can get access to Dan Sundheim. He went on Invest Like the Best, he was at Cheeky Pint, on David Rubenstein’s Bloomberg interview. The Cheeky Pine and the Invest Like the Best are more recent. They’re valuable to an inexperienced investor like me.

This is the whole thing about investing — the most value you can give going on podcasts as a professional investor is the process. He can talk about investing in GE Vernova, the turbine business tied to power generation — you know there’s a secular trend because of AI data center demand. The thesis is simple — he can’t sit at a podcast and talk about it for two hours. He has that information.

But at the end of the day, the process is gathering the information, which at a hedge fund like D1, he can be having his people do that for a month. Him distilling down to two, three things on a podcast is not gonna help you become a better investor, because this guy has done this for 30 years successfully. But just hearing that framework itself is already very helpful.

Yes, definitely there is part of it. There is some marketing, but I think he genuinely just wants to share what his process is.

Bryan: It’s interesting because it wouldn’t be an accurate representation of their process to go on and talk about one stock for an hour or two. Whereas someone like Cliff Sosin has had fantastic episodes on Invest Like the Best where he just talks about Carvana for two hours. It’s because they’re different strategies.

Jerry: Yeah. Cliff is very concentrated. We all saw that ride with Carvana with him — at one point, 50% of the book was in Carvana or something, and 30% in Credit Acceptance. Whereas Ricky Sandler goes on and explicitly talks about liking it a little bit more diversified — so some parts of the book is always working while the other part is not.

For Cliff, he’s just all in on something, then that’s all he talks about. Concentration plays a role in how they think about their process and how deep they go.

BIGGEST MISTAKES: INDUSTRY INSIDERS (LATERAL MOVES)

Bryan: One of the last topics I wanted to touch on — now that you’ve gone so deep into the recruiting market, I’m interested to hear on both sides. Let’s start with people who are trying to move laterally within the industry. What are the biggest mistakes you see?

Jerry: The biggest one — so many industry incumbents are still so reactive to the job search. They look for a job when they need a job. That is a cardinal mistake.

The moment you’re on the buy side, you don’t realize how advantageous you are, because you have a platform to be building your brand equity — yes, inside the firm, but also within the buy-side ecosystem.

I’ve done so many client calls where this buy-side person who’s done this for 8 years, they’re like: “Okay, I need to get a buy-side job. What should I do?” At least they know they won’t find any job posted online. But they’re like, “what should I do?” And I’m like: you should have a list of contacts where you should reach out and say “hey, I’m Bryan, I’m looking — do you know anyone who is looking to add headcount?” That should be how it works. They don’t have a network, they’re just sitting at their Bloomberg terminal doing work for their boss — which is totally their job — but there is a part of the job where you should preempt, like, thinking about the next seat.

They don’t know networking is a must. They don’t know who is who in hedge funds — which is what my fund database helps with.

I remember talking to a junior at a wide-moat shop out of Chicago. I told him I love wide-moat investing, I have a good friend at this other white moat shop out of Miami, and he’s like: “Oh yeah, we have a list of firms that we will cold-reach to try to poach people to join our firm. Here, take this list.” Do you know how much time that saved me in terms of whom to reach out? Then I look at the list — oh I know this shop, I know that shop, they’re all wide-moat shops, that checks out. Then I know whom to reach out.

Another point that’s more at an advanced level that I’m recently discovering — people outside and inside the industry underestimate the power of relating on a personal level.

Because I profile investors — their story — on a daily basis, and a lot of my audience will comment “how the hell did this guy get into the industry?” I’ll give examples:

Peter Lynch — famous story — he caddied on a golf course for Fidelity’s president.

Art Samberg (Pequot) — studied aerospace engineering at Princeton, got the sell-side equity research job because the director of research at Kidder Peabody was also an engineer. Relatability.

Kelly Granat (Lone Pine) — went on podcasts telling people she loves people who play sports, because she was varsity tennis at Harvard.

Dan Sundheim — told Patrick O’Shaughnessy that he likes strong communicators.

These are very big clues when you are pitching yourself to hedge fund founders. You might just tip the scale just because you have something that these people personally like. Yes, these hedge fund founders are billionaires, they’re high up in the world, but they’re also human beings. If you can relate to them on a personal level, that might just tip the scale when you have that imposter syndrome — you might lose against an Ivy League 2+2 type, but maybe you’re a varsity lacrosse player at a Division II school, and you go sit in front of Kelly Granat at Lone Pine and say “I’m a competitive sports player.” Maybe you don’t get the job, but you earn the spot to have a conversation.

BIGGEST MISTAKES: BREAKING IN FROM OUTSIDE

Bryan: And how about for people looking to break in from the outside — either early career professionals or college students?

Jerry: Let’s start with a simple one. They didn’t understand that this profession — they didn’t take a step back and think about why hedge funds and long-onlys want to hire from investment banking, private equity, and equity research. The reason is because they need to know how to do the job. Somewhat, not entirely, but they need to know how to do the job before they get the job.

The biggest punchline for aspirants — even for people currently in IB, PE, and equity research — do not ever try to scheme your way into the profession. 99% of the cases, you will need a strong stock pitch to get hired. There’s no way around that.

There are people who ask how do I limp my way into the profession? Because day one on the job will be: “Hey, Bryan, my buddy was following this idea, seems interesting, take a look. Let me know what you think.” That’s all the instruction you’re gonna get. I’m not gonna say step one, read section 1 of the 10K.

Because it’s public equity, all the skill that you need to equip yourself is on the internet today, or in a book. Just go figure it out. If you don’t want to go figure it out, don’t be in this industry.

Same issues for incumbents — not knowing networking’s a must, not knowing who’s who, not knowing the power of relating.

The other big issue: No recruiting season. People in the three feeder professions — IB, PE, equity research — didn’t know there is no such thing as recruiting season for public equity. They hire whenever the hell they want.

Investment bankers are probably the biggest offenders — they’re like “okay, what’s the recruiting season for hedge funds?” There’s no recruiting season. Someone left, they’re hiring, they’ll post a job. You’re lucky you see a job posting.

Concrete example: Lone Pine just publicly promoted Rahu as the third co-PM with Kelly and Dave Craver. As a result, 3 senior analysts are leaving, all starting funds separately. That’s probably telling me there might be headcount openings at Lone Pine. You gotta pay attention. That’s on Bloomberg. But if there wasn’t a promotion, they wouldn’t be hiring again for 2 years.

They just don’t hire until they need to. If you miss that boat, they’re not gonna hire again this time of the year next year. So there’s no recruiting season.

Last thing — everybody should build an online brand under a compliant framework.

There’s so fewer investor professionals bouncing ideas on Twitter. I heard that crowd has flocked to Substack — increasingly a social media platform where people talk about ideas. Some buy-siders I talked to said Substack is a lot better for shooting ideas than Twitter.

Provided you know what you’re doing as an investor, if you’re aspirants outside looking in and super passionate, you should build an online brand. For outsiders, that’s compliant by nature. If you’re inside at a hedge fund, that’s tricky because you have to disclose. But I think for smaller funds the PMs will let you bounce ideas.

That should be part of your job search motion. Most is push — cold-reaching out, doing coffee chats, submitting applications (least effective). The last part is pull — build a brand authority online, and people come to you. I know people who got hired through podcasts, through online presence. A gentleman at an Ivy League school has a great podcast where he gets portfolio managers on — he got hired at a very respected long-only. How does that happen? You attracted an audience who might give you a job.

Internet lets you do that at scale.

ADVICE FOR EMERGING FUND MANAGERS ON HIRING

Bryan: And on the hedge fund manager side — with how competitive things are, competing for talent against the Citadels and Millenniums of the world. If you’re an emerging manager with a decent track record, maybe running for a couple years, good pedigree, starting to raise assets — it’s time to hire. What advice?

Jerry: First thing — just be open-minded about where talent comes from. My PM hired me. I don’t have a very good background — I don’t have the traditional IB/PE background. My PM has a pretty good background — just an undergrad, which tells you how successful he is. He didn’t need to do an MBA. I did an MBA because I had to.

Be open-minded about where talent comes from — especially in terms of their pre-buy-side work experience, not from IB/PE. I’ve seen this with older founders. Be open-minded about people’s past. Even the best stock pickers are only above 50% hit rate. So why only hire people who never failed in their life and career?

I talked to a recruiter who tells me a fund in Seattle still imposes SAT score and GPA requirements. For someone hiring a senior analyst who’s out of college for 10 years — does it really matter? I had a low GPA, I got into a hedge fund. So don’t be so rigid and elitist.

I want to use your platform to message this: There is a massive talent degradation in the entire profession — sell side and buy side. Why? People flock to where the money is, and money is in tech and AI today. That’s a fact. You don’t get to make that rule.

And the very best talent are doing what I do — they have a vision. They might not have product experience, they will vibe code something and find product market fit and make nine figures. I go to these founder events sometimes and these guys don’t even know some of the television shows I’ve seen, they don’t know who Kobe Bryant is. That tells you how young they are.

On posting jobs — there are a few issues. They post at the wrong places. It’s probably better to post at a verticalized job board than on LinkedIn — LinkedIn is a mass audience, not verticalized by finance. Post where candidates have high intent for buy-side jobs.

They don’t know the social media game. They should learn by talking to LLM, or hire a Gen Z as a free intern — ask them how social media works. If you have a job post, understand what a hook is, what a call to action is. “We’re a $200 million long-short hedge fund investing in old economies” — versus having a hook that intrigues the audience. Maybe 10x difference in engagement, and engagement funnels down to clicks.

I was in Los Angeles in January, talking to a friend who founded his own fund — he’s looking for an intern and doesn’t know where to post. I offered to shout out to my 8,500 newsletter subscribers.

But I also advised him: Fund managers should have an owned audience. The most loyal audience is newsletter. Where you can attract highly engaged candidates, LPs, and all sorts of relevant people within the ecosystem of running a fund. You find aligned candidates who believe in your investment style.

VC has perfected this long ago — a16z has a media arm for sourcing deals. Brett Caughran sponsors stock pitch competitions — part of sourcing talent. John Griffin of Blue Ridge — I know people from Columbia Business School, highest performing students in his class got hired. John used to teach at Columbia, he went to UVA, used to teach at UVA. Why do these people teach there? Part of it is sourcing candidates. They know their dear alma mater attracts and filters the most qualified, highly engaged candidates.

The punchline: the worst way is to use the traditional channel to source candidates. Podcasts — if you go on a podcast, say “hey, we’re hiring,” you shout out on Patrick O’Shaughnessy or the Acquire podcast with Ted Seides — you’ll be flooded with emails. People need to be aware of how information gets disseminated today.

WHERE TO FIND JERRY

Bryan: Where can people find you, Jerry, if they want to read more of your content or sign up for your newsletter?

Jerry: It’s really simple — just type in “Richard Toad” on Google and you will find all my assets across the internet. I operate kind of like a casino where you can’t leave. You go to my Instagram, you will see my newsletter, you go to my newsletter, you’ll find all my socials. You can engage with me across the channel of your preference.

You’ll get most value out of my newsletter — it’s called “Inside Equity Research with Richard Toad.” That’s where you get all my career tips, all the investor bios, and the fund database if you want to really buckle down and target and maximize your shots on goal for your buy-side search.

Bryan: Well, awesome. Thanks again for your time today, Jerry. I really appreciate it.

Jerry: You bet, thanks for having me. Real honor to have this conversation. Thanks for having me.

What the model looks like

The cost stack is built bottom-up from analyst estimates and public filings: manufacturing cost in the hundreds of thousands per satellite, $15-25M internal launch cost per mission (modeled -- SpaceX doesn’t disclose this), 23-29 satellites per Falcon 9 launch. That gives a fully loaded annual cost per satellite of roughly $250K to $500K depending on the scenario, and an annual fleet replacement burden of $2.4B to $4.6B for a 10,000-satellite constellation.

On the revenue side: ~10 million active subscribers at a blended ~$92/month ARPU implies roughly $11B in annual revenue, which cross-checks reasonably against Reuters reporting that SpaceX generated $15-16B total in 2025 with Starlink as the primary driver.

Credit where it’s due -- Quilty Space has done very impressive work and is hosting another webinar in April. Tim Farrar on competitive dynamics, Moffett on Bloomberg Television, Evercore’s work, the Kook Report on ASTS, and Kerri Cahoy’s work at MIT have all shaped the thinking.

The punchline

The model’s ROIC is almost entirely a function of satellite replacement cadence. At a 4-year satellite life with 35% EBITDA margins, Starlink earns roughly 0% on invested capital -- the replacement burden eats the entire profit. At 6 years with 48% margins, ROIC is around 11%. At 6 years with 61% margins, it’s 27%.

The swing variable is not manufacturing cost. It’s not launch cost (probably). It’s how fast you have to replace the fleet. The difference between a 4-year and 6-year satellite life is a ~$2.2B annual swing in replacement spending. That flows straight to returns.

The two questions

1. What is the actual observed average operating life of V2 Mini satellites?

FCC filings reference a 5-7 year life. Moffett referenced 4 years on Bloomberg. Eutelsat management has cited 7 for their constellation. The range between 4 and 6 years matters more than any other assumption in the model.

2. What is the true fully burdened internal launch cost per Starlink mission?

SpaceX’s published commercial price for a Falcon 9 launch is $74M. Most external models use $15-25M for internal Starlink missions, reflecting reusability economics. But how much booster amortization, refurbishment, and overhead should be allocated to Starlink vs. commercial customers? Moving from $17M to $30M roughly halves the base-case ROIC. But none of this accounts for Starship, which could carry several times the capacity of a Falcon 9.

If you can help

If you have a view on either question, I’d appreciate hearing from you. DMs are open.

Subscribe now

This conversation details the brute force hustle that got his first readers, building StockPromotionTracker as a non-technical founder, and where he sees prediction markets going.

If you’re not subscribed yet, sign up here so you don’t miss future interviews (I’m recording another one this week):

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Listen on Spotify here.

The Early Days of The Bear Cave

0:00

Bryan Wagman: So, wanted to start with something that I think is really cool, actually, about your journey, which is the… I guess the… the DMs that you sent and the emails that you sent to get things off the ground in those first days when you were just getting things rolling with the Bear Cave. So, can you… can you tell that story?

0:21

Edwin Dorsey: Yeah, absolutely, Bryan. So, when I was a senior in college, I started the newsletter, The Bear Cave, mainly as a way to get attention and hopefully get hired by a hedge fund. And so, I started writing this newsletter in my dorm room in February 2020, right before the pandemic hits. The pandemic hits, everybody goes home, I graduate a quarter early, so I got all the time in the world to work on this newsletter, and hopefully make it into a thing that people start reading. And it’s always tough to get your first thousand readers. I tweeted about it, and it got some traction, and I had a few Twitter followers at the time, but I really wanted people to read it.

So, I went through every single person who was following me on Twitter, I don’t know how many, maybe it was 10,000 people, and individually DM’d every single one that had DMs open. I literally spent 3 days just DMing people, saying, will you please read my newsletter? And my eyes were hurting, and that’s one way in which I got a few readers to sign up for the Bear Cave early on. Another thing is that I looked at every single college student investment club, and I cold-emailed every college investment club, asking them to check out my newsletter. I just went out to the world and found every potential reader and emailed them to say, sign up for more emails. And luckily, it was the pandemic, and people were really open to finding stuff to read, so that’s how I got the initial ball rolling. And what I found with newsletters is once you have the initial readership of a few thousand people in the right audience, then as long as you produce good content, it kind of grows on its own. So there was a lot of hustle to get those early readers, but now it’s just… the momentum takes it.

2:06

Bryan Wagman: What were those 3 days like? Like, did you have a certain routine to kind of get through it? Like, were you, you know, surviving off coffee? Just, like, paint the picture for us.

2:17

Edwin Dorsey: So I don’t do coffee, lucky. I try to avoid that. I was living with my… in my parents’ house at the time, just graduated, and I’d go down to a table, and it… it’s terrible, it’s not fun just to repeatedly cold email people. The first thing I do is you want to test out various prompts. I had a lot of experience cold emailing people when I was a college student. I sent so many cold emails just trying to meet and network and learn, so I think I drafted 2 or 3 different versions of a DM I could send people to sign up for the newsletter. I tested, I iterated. And I was also testing different times. I’ve long been a believer the best time to ask anybody for a favor or reach out to them to get their attention is in the afternoons. In the mornings, people are busy, and you got your work to get through, and in the evenings, you’re gonna go to bed, and you’re socializing, but in the afternoons, you just had lunch, you’re in a good mood, it’s a lull in the day. So I was testing various different prompts at various different times to send DMs, and I think I concluded, like, I found the prompt that worked best. It’s always just good to keep it short and directly ask what you want, which is them to sign up for the newsletter, and I found that the afternoons were good, so I’d block out 4 or 5 hours, and, you know, say, just get through this many, just get through this many, just get through this many, and then by the time I did, you know, roughly 10,000, I didn’t have anybody else to DM. And it was nice, too, because if people don’t like the message, they’ll just ignore it, and they won’t sign up, but if people do like it, they’ll give you some positive encouragement, so it was cool to get a lot of DMs back, saying, oh, this is so cool, I’ll definitely check it out, I’ll tell a few people. I think the traditional advice with venture capitalists is you do things that don’t scale in the early days to get customers and readers, and this is one example of that.

Brute Force Networking

4:11

Bryan Wagman: Yeah. That’s… that’s sort of what I wanted to ask you about, because I think that’s exactly what it is. Like, it’s… it’s not scalable, and even beyond that, I feel like most people, when they think of just the… the idea of DMing 10,000 people or something like that, like, it seems almost like… not possible, or just, like, something most people wouldn’t really consider. I’m curious, in the past, had you had other examples of taking this sort of, like, brute force type approach to life?

4:38

Edwin Dorsey: Yeah, oh, absolutely. I love that question. That’s one thing I did really good, especially when I was young. I think when you’re a college student in particular, you’ve got this innocence about you, which means people are way more likely to help you than they are, you know, once you graduate from college or you become a full adult in your late 20s and early 30s. So, as a college student with my college email, I… when I was in New York for a few months, I looked at every single Stanford alum at the big financial firms that I admired, and I just pulled their emails from our alumni database and cold email. I think I was averaging 100 cold emails a week. 10% response rate, 5 would lead to meetings. I would not be surprised if I have cold emailed more Stanford grads in finance than anybody to ever be an undergrad. And this is how you get the foot in the door. And the other thing is, it’s great to network when you don’t need anything. So if you don’t need an internship, or you don’t have, like, a clear ask, you’re genuinely just going to learn, and maybe present, and try to… show your skills a little, and just understand the industry better.

So, that was a big brute force approach. There’s one story I like to tell of a particular hedge fund in San Francisco, and I cold email, like, everyone told me you gotta meet with them. And I cold email, I cold email, I cold email, no one’s responding. They didn’t say no, just no responses. So, I decided, as a freshman, let me just go there and see if they’ll meet with me. So I took the train up, I go to this big, fancy building, I go up to the desk with the guard, you know, guarding people from going to the elevators, and he says, do you have an appointment? And I say, no, but I want to present to them my ideas, and maybe they’ll give me an internship, and he’s like, he says, you can’t come up without an appointment. I said, please, just let them say no to me, I just want to go up, and they say, you can’t go up without an appointment. Perfectly fine, and I said, okay, I’ll sit in this lobby and see if… if someone calls down to get me, you know, then they can… I’ll be let up. So I go, I sit down in the lobby, and I start LinkedIn DMing everybody at the hedge fund, saying, look, I’m a freshman in college, I’m in your lobby right now, will you please meet with me? I want to share stock ideas. In hindsight, it’s a little weird, but… in the moment, I had this confidence, and eventually one of them said yes, and they called down, and the guard, the front desk agent, was just amazed that I got let up, and I met with them, and I think they became subscribers to my newsletter four years down the road, and it was just a funny story. So, it’s really important to take a lot of initiative, and once you get older, you can’t randomly show up places, and, you know, cold outreach doesn’t work as well, but I think especially when you’re young, it goes a long way.

7:28

Bryan Wagman: Yeah, that was gonna be my next question. Now that you’re more established, do you find you have to use these sorts of tactics somewhat less? Or, like, when was the last time you can think of sort of doing something along these lines?

7:41

Edwin Dorsey: So, I would never now go show up somewhere randomly, it’s disrespectful and odd. You know, I might… I probably wouldn’t just cold email somebody to say, hey, I just want to talk, unless I feel like I can bring something to the table, because I don’t want people just to donate their time for maybe no reason, unless it’s a special circumstance, but I do cold email a lot of people to get featured on my Idea Brunch newsletter. The thing is, if somebody says no, like, then I’ll take them off my reach-out list. I won’t continue to persist, but I do cold email a lot, but I also believe in just respecting people if they say no, and they’re not interested. You know, I’ll have some people I really admire who I just, every 6 months, I’ll reach out to them, and, you know, until they tell me they’re not interested, I’ll email them every 6 months, because I think they’re great. And, you know, some people do, you know, after 2 years of pestering them every 6 months, hey, can you come on my interview series? They do go on. So, that’s another example. But I’ve found that as you get maybe a little older and more established, it’s better just to demonstrate the value you can provide, do interesting things online, and then let people come to you. And that’s the best way to do it, and that’s kind of been my approach, is try to build cool tools and share them online, write interesting things in your newsletter, and then if people come to you, that can be your new network.

Starting Over & AI Integration

9:01

Bryan Wagman: And if you were just getting started out today, what would you do differently, both in terms of, I guess, the the product and the value add to the client in terms of, like, what you would think about trying to provide, as well as how you would think about distributing it.

9:18

Edwin Dorsey: In terms of, like, if I was starting the newsletter now, what would I do differently with the Bear Cave? The number one thing is you want to be very fluent in AI and using AI tools. I use ChatGPT a lot. I kind of wonder if I was doing the newsletter now, how many AI-related screens can I do to… and make that integrate to the Bear Cave’s content? So, every month or so now, I have ChatGPT Deep Research give me a list of all recent IPOs and SPAC mergers that have high levels of consumer complaints. If I was starting the newsletter now, I’d probably, you know, make 5 or 6 of these different screens that are running all the time, and have AI researching it, and then, you know, here’s some AI-generated ideas, quick spark notes on each one, and the unique filters we’re using to come up with them, so that’s one big thing. I’m not sure I would do anything terribly different. I think I know the newsletter game pretty well, and I think I was really lucky with the pandemic thing timing.

Maybe one thing I did wrong is I think pricing it between $500 to $1,000 a year, that’s a no-man’s land for pricing. I was originally at $340, $34 a month or $340 a year, then I raised it to $44 a month or $440 a year, while grandfathering in existing subscribers at the lower rate, and then I raised it again to $640 a year. I think that last price increase going above $500, it’s a psychological hump where you either charge over $1,000 or under $500. That’s a no-man’s land, and that’s maybe one thing I wouldn’t have done.

Daily Routines & Walking

10:56

Bryan Wagman: Yeah. One thing that stood out as I was doing some research for this podcast was, you have a big walking habit, it sounds like, and also your work, just, I guess, patterns seem to fluctuate a lot. Like, some weeks it can be super intense, and then some it’s more relaxed. So, like, what’s a… what’s a typical day, I guess, like, for Edwin Dorsey during a calmer period? And then, same question for maybe a more intense period?

11:25

Edwin Dorsey: I have a very atypical life and very atypical day-to-day schedules. For me, some of my day is dictated by the weather here in Miami. If the weather’s nice, I’m gonna go for a really long walk, and maybe go to the beach and listen to a podcast or stuff that’s relevant for work. I might, you know, have 3 tickers I’m interested in, I’ll find 10 hours worth of podcasts from CEO executives and industry participants talking about these companies. Just go for a long listen to the podcast, and I’ll listen to one CEO, and I’ll say, you know, he seems reasonably okay. Maybe don’t write on that company. I’ll listen to another one and say, this guy is so bad. Now, this is gonna be a focus, and I’ll try to, you know, piece together a mosaic. So that might be one thing, if the weather’s good.

If the weather’s not so good, you know, I spend a lot of time now on prediction markets, which we may talk to later, so I do a lot of research on those things. I might be just writing the newsletter, because I’m on a schedule. We’re first and third Thursday of the month. I publish these Bear Cave Deep Dives. I have a Bear Cave Deep Dive due this Thursday, so tomorrow and Wednesday, it’s gonna be full-on 12 hours plus in my apartment, just writing the newsletter, doing research on them. That’s really intense. But if it’s a week where I don’t have a Bear Cave due, I’ll probably be spending more time on prediction markets, more time going for walks and listening to podcasts, and more time just, you know, doing soft research on various ideas to try to narrow down which company I want to write on.

Career Path & Betting on Yourself

13:00

Bryan Wagman: Yeah, for sure, and definitely going to get more into those prediction markets later. They were pretty new for me, so I have tons of questions. One other thing I’m really curious to hear how you think about both now, but as well as in the past, and how you sort of found yourself in this situation, is just, you know. Obviously, given your background and your aptitude in this field, you know, you certainly could have pursued a role working on the buy side, or eventually starting your own hedge fund, or something like that. And so now you are certainly still an investor, which I did want to… it was another part of this question I wanted to ask was just sort of, what do you do in terms of… for your own investments, but also you’re kind of running a media company as well, so I’m just curious how you think about your career path, if you will, and why you chose to go the way that you did.

13:53

Edwin Dorsey: Yeah, so, originally, I was interning at a fund all four years of college. I wanted to work for that fund after I graduated, and they said no, because they were kind of in the process of winding down. So I couldn’t work there, and I wanted to get hired at another fund, so I started the newsletter as a way to get hired. So I originally did want to go the hedge fund route, although I really care about culture, and I maybe don’t love typical finance culture. I want to do things that I feel are societally valuable and useful. So, I wanted to maybe work at a really, like, small shop with a good culture that has some, you know, element of short selling for the benefit, or talking to reporters, or highlighting misinformation to others.

So I started the newsletter, and it just became commercially successful in its own right. I think within 6 weeks, it was 100K ARR. I remember I talked to one fund that was kind of interested in me, and I mentioned how much I was making, and I said I would expect it to be, like, matched or double, and they’re like, we don’t pay first-year analysts that much. I’m like, well, then why were we having the conversation, you know? So it became successful. I think there’s a saying, which is, once you work for yourself, it’s tough to work for someone else, and I’ve never worked for somebody else, and I think I would find it really tough. I like having my own schedule, I like working whatever hours I like. I like being able to do whatever I want to do. So that makes me hesitant to join a traditional firm. And I like betting on myself. I think these… there’s chances to make really big newsletters. Doomberg does over 3… I think over $4 million a year now in ARR, and it’s like, well, that’s a huge thing. If I can get to that level, I can build my own tools. I think prediction markets are gonna be an absolutely huge space, so if I have a second act, I could really see it being in tools for prediction markets, or making my own funds and investments to trade on prediction markets, so that’s an area I see a lot of potential, too.

15:58

Bryan Wagman: Yep. In terms of, I guess the, you know, you mentioned AI earlier, and just how that has, you know, become a more significant part of your work. Could you detail just sort of what that journey has been like, and I guess… when did you start to integrate it into your process? How do you feel like it’s come along in terms of the capabilities and how prevalent it is throughout your work, and just where you’re at with it today?

16:28

Edwin Dorsey: So, I mean, it starts by just using ChatGPT a year or two ago and asking it a bunch of questions. Then I use it for maybe more screening. Now, if I’m researching a company, I find myself going to ChatGPT research and just asking a ton of questions to learn, learn, learn. Sometimes it’s surfacing useful insights. Sometimes it struggles with things. Like, it’s really bad at analyzing Glassdoor reviews, which is an area I care about. So, part of it is just company-specific research, asking questions. Part of it is idea generation, asking it to highlight, you know, look at 100 recent IPOs, and give me the five that have high levels of consumer complaints, and then I’ll briefly look at those five, and two will be interesting to me. So, that is idea generation, company-specific research, and then there’s these unique cases. I know we’re going to talk about Stock Promotion Tracker. That uses a ton of AI, where I have a dedicated email inbox that’s receiving all these stock promotion campaigns, and an AI agent reads it all and summarizes it and gives me the data. So, that’s kind of a unique case where I’m using AI to, you know, to try to digest huge amounts of information that otherwise would be too burdensome for me to deal with.

17:44

Bryan Wagman: Yep. You said something earlier when detailing, sort of, your story of starting the newsletter that I thought was interesting, about betting on yourself. And, like, when you were talking to that fund, and you’re like, hey, this is what I’m making off the newsletter, if you can’t match or double this, it doesn’t really make sense. And I think that’s really interesting, because I think a lot of people, especially when they’re younger, get caught up in this mindset of almost just, like, “I’m just happy to be here,” or something like that. And, like, you know, they want to, you know, a lot of people say, oh, don’t worry about how much money you’re making, just focus on the learning experience. And I’m curious to hear your impression of, you know, sort of that career advice, and sort of… how you navigated the… I guess there, you know, because obviously, from your perspective at that point was, oh, well, I guess maybe I won’t have as much mentorship as I did if I went and joined a fund, or, you know, maybe my resume won’t look as nice, but like you said, you bet on yourself, which I think is really impressive, and I’m just curious to hear more about, sort of, your mindset around that.

18:57

Edwin Dorsey: Yeah, so I think, in general, when it comes to giving advice or professional advice, good advice needs to be very personalized. Very little advice or good advice is one size fits all. So what works for me might not work for someone else. What works for someone else might not work for me. I think one universal thing you hear among people who try to start businesses when they’re young is it’s a lot easier to take risks when you’re young. If you graduate from college, and you spend a year trying to build a newsletter business, and it goes nowhere, employers might look at that slightly negatively, but I don’t think anybody would hold it against you to a strong degree. I do think if you’re 30, you know, you have a lot more obligations, you might have a wife and kid, it’s a huge financial risk. If you leave your job, can you go back and join at an equivalent salary and without losing status and prestige? And, you know, it’s not a guarantee. So it becomes way… it just continuously becomes tougher and tougher to take risks as you get older, partly because you have more obligations, partly because you’re giving up more.

But that’s not true when you’re young. So, I think it is true that you need to, if you want to take risks, take risks when you’re young, and I do believe in testing things out in ways that it’s easy to fail. So, not everything I’ve done, you know, has turned out great. I’ve had many side projects that went nowhere, but never have I lost a ton of time or money over a side project which failed. For example, I tried to create a job board for finance jobs. I thought there could be a, you know, universal job board for hedge funds to post internships. And I really tried to promote it, I DM’d everybody, I promoted it in my newsletter, but I could see after 2 months of trying really hard, there was no traction there. So I just shut it down, it cost maybe $1,000, 2 months of focus. No harm. And so, I think I see, you know, with some people, they say, well, do I quit my job or not to start this thing? And I say, well, why not try to test it on a small level? If you’re going to start a newsletter business, try getting active on Twitter and see if you can build a following. Because trust me, if you can’t get people interested in you on Twitter, you’re not going to be able to get them to give you their email. And then, why don’t you start a free newsletter and see if people will give you their email first, because if you can’t grow a free newsletter, there’s no way you’re going to grow a paid newsletter.

To me, the two kind of things I think about are, one, take risks, tremendous risks when you’re young, and two, set things up in a way so you can experiment. So if the experiments go poorly, you can just shut it down easily and try something else. I have had so many things that just, you know, don’t go the way I planned for some reason, but it’s never cost me big time.

Stock Promotion Tracker

21:46

Bryan Wagman: Yeah, absolutely. That’s, that’s good stuff. Wanted to pivot to the promotional tracker tool. So maybe first, if you could just kind of give us an overview, maybe from more of, like, a narrative story perspective, of just your experience tracking stock promotion over time, and just how that idea became to… like, how you came to think, hey, this can be something I can actually productize.

22:13

Edwin Dorsey: So, I didn’t have a ton of experience tracking stock promotions. IPhawk, a guy on Twitter who has a newsletter, you know, would track them. It used to be stock promotions and companies engaging in paid stock promotion were really micro-cap, sub-$100 million companies. Over time, especially as we’ve seen a huge influx of retail investors, we’ve seen a lot more stock promotion, a lot of companies engaging in stock promotion, getting a lot bigger. Stock promotion has moved to new forms of media, like Discord, Reddit, and YouTube. So, it’s kind of become more complex, more institutionalized, bigger dollar amounts, bigger companies. Which makes me think, oh, I can write about some of these companies in the Bear Cave. And so I first kind of got interested in stock promotion by wanting to know what companies would be interesting for short sellers to highlight in the Bear Cave.

Now, in terms of productizing things, I did not originally set out to build a tool that would track stock promotions. I was looking at myself and thinking, I got a good newsletter in the Bear Cave. I got a good newsletter in Sunday’s Idea Brunch. I’m getting this cash in, I have extra money to now spend on new projects. What do I want to do? I want to build tools that are useful for me and useful for others. The first tool I built was FOIA Search.com, which is still up, that lets people search the SEC’s FOIA logs to track potential signs of undisclosed investigations. It’s a really useful tool. I thought it was the best thing in the world. I thought every hedge fund is going to sign up for the paid features to track their portfolio holdings and get alerts, and I think… it got, like, 50,000 visitors, 50,000 people have used it, and maybe 5 have signed up for a paid feature. They’re, like, $50 a month. It was just not… not enough people care, not enough people want to pay for it, it just… for whatever reason, it wasn’t commercially viable, even though I thought it would be, and it’s a useful tool. I made a few other tools, like Comment Letter Tracker, that makes it easy to track SEC comment letters, and a few other minor things, a website so people could highlight text messages sent by stock scammers overseas. So, StopNowZack China Fraud is another website. But none of those were commercially viable, so I decided to just do this stock promotion tracker mainly as a way for myself to track these things. I have an engineer I work with who I pay to help me build these websites who’s excellent. And we were building this, and we quickly realized it’s incredibly complex. He’s working on it 20 hours a week, I’m talking to him 2 hours a week. And we eventually made it into a useful tool for me to find stock promotions, and then for other people to find stock promotions. And then, you know, I’ve been able to charge $1,000 a year for it or so. There’s 20 paying customers now, and I see a big pathway to grow it, or sell it, even.

25:09

Bryan Wagman: What was your process like for finding and beginning to work with that engineer?

25:13

Edwin Dorsey: Well, originally, somebody cold emailed me a long time ago, and I was working with him. He was great, but he didn’t have necessarily the skill sets for what I wanted for something else, so he recommended me my new guy. And then, you know, I think I reached out to, like, 5 people, and this guy on someone else’s recommendation, and he was really excellent. I was just like, might as well work with him. So, I didn’t use any of the traditional… it was just a friend of a friend, which is how I think a lot of these things start.

25:48

Bryan Wagman: Yeah, and to the extent you’re open to speaking about it, would you be able to share anything about, just in terms of the, I guess, tech stack that’s going on behind the scenes for the promotion tracker tool?

26:02

Edwin Dorsey: To be honest, I don’t have no clue. So, like, I mean, I know we use AI tools, and I’m spending, like, $1,000 a month on AI to read through the email. I could explain in a more basic, crude form how it all works. I don’t know necessarily all the tech tools. Despite… I am the least technically savvy person to ever come out of Stanford. I don’t know how to code, I don’t know, like, all these fancy things. I’m good at my research, I’m good at intuition with corporate misconduct, I’m not good with tech stacks. What I can tell you is, you know, we made a list that’s ever-growing of places engaged in stock promotion, and these firms shut down, they sprout up, there’s a lot of YouTube channels. I mean, it’s really more complex than you think. It’s not, like, a universal thing. The SEC doesn’t have good data on it at all, so we kind of initially made this list, and it started with just tracking websites that would put out promotional content. And, you know, you scrape the website every day and upload that data. And we have a scraper and an AI agent that reads it and looks for the data and puts it in.

Then, it changes to be a little more technically complex, where we have a dedicated email inbox that signs up for all the email campaigns, because most of it is done over email, and then we’re scraping that. And then we find 50 or so YouTube channels that engage in stock promotion, and then we put them in, and we build a scraper for that, and it’s complicated with YouTube, because most of these places, they don’t disclose the payments in their YouTube description, they’ll have you click on a link that takes you to the information… so now we have a thing that checks every single link in the YouTube videos from these 50 channels to see if they’re disclosing payment, and sometimes they’ll say, “we may or may not be getting paid.” And I’m like, well, that’s not the law, but I mean… now what do we do? So there’s a million different edge cases, and so much complexity goes into it, which also creates our moat. It’s not as simple as just going to Edgar and seeing, give me a list of all companies paying for stock promotion, but now we’ve got this database that kind of works autonomously, whether it’s checking company blogs, checking our dedicated email inbox, checking all these YouTube channels, a few other sources. We might want to expand to Reddit and text messages and Discords, but right now, I’m confident in saying we have the best database for tracking paid stock promotion in our public markets. I don’t think many hedge funds are aware of it. I don’t think I’ve done a great job promoting it. I think it could be huge. I could see it integrating with a lot of other service providers. I want Seeking Alpha to have a stock promotion tracker risk score, like an API connected to us where we can warn about companies. Benzinga, all these other platforms. That would be a really useful service that doesn’t really exist. But right now, it’s just, you know, we need to be the best source of data on stock promotions, and that’s how we do it.

29:01

Bryan Wagman: Yeah, and maybe you could expand on that a little bit, like, just from a hedge fund’s perspective, like, just what exactly is the value add, and how would you see them potentially integrating it into their process? Or I don’t know if you’ve actually had any conversations with existing customers so far about how they’re using it.

29:17

Edwin Dorsey: So, I think there’s a dual purpose to StockPromotionTracker.com. One can be idea generation. I’m looking for companies to short. Show me which ones are spending tons of money on stock promotion campaigns, and are moving up. So we have a lot of filters for that. We can show you companies that have only recently started paying for stock promotion. We can show you companies that have spent over a million dollars paying for stock promotion. We can let you filter by market cap, because people generally don’t care about sub-$100 million companies. We make it easy for you to find companies that have over a $100 million market cap that have multiple paid stock promotion campaigns in the last 3 months that are listed on a major exchange. You can’t get that list really anywhere else other than our tool, and so that can serve as a really good source of idea generation. I know it serves as a source of idea generation for me in highlighting things in the Bear Cave. It’s unique, it’s differentiated, it’s repeatable, and it’s… these aren’t necessarily companies with no volume, but they’re also not $20 billion companies that everybody’s looking at. It’s really in this $100 million to billion dollar market cap sweet spot.

So that’s one area. I think the second area is diligence. If you invest in a lot of small cap companies, and people who invest in small caps tend to invest in a lot of small caps, it’s not necessarily easy to see: are these companies credible, or are they being overly promotional? Are they paying for stock promotion? Are they paying for stock promotion egregiously, or are they only paying once or twice in the last 2 years? Our tool makes it so easy. 5 seconds, just type in the ticker, and you can see if it’s paid for stock promotion in the past. So it can just be if… you don’t short at all, but you invest in a lot of small-cap companies, 1 out of 10 in your portfolio might be paying for stock promotion, 1 out of 20 might be egregiously doing so, and it’s a sign that maybe you don’t invest, or you at least apply more diligence. And based on the data we have, it seems like companies that do a lot of stock promotion really underperform. And now we’re building more tooling where you can kind of see, like, you know, they kind of go in waves. So does it have one wave where it promotes, issues stock, and collapses, and then another wave? So we’re really trying to do a lot with the data, but right now, it’s just… if you want to track stock promotion campaigns, StockPromotionTracker.com is the place to do it.

31:43

Bryan Wagman: Makes sense. And from a Bear Cave business model perspective, do you feel like your vision for the future, like, is part of this intentional to try to shift more to, like, a software-type business model, as opposed to something that requires you to keep putting in your time regularly?

31:59

Edwin Dorsey: Yeah, I think, you know, Bear Cave, I love it, and I used to say, I’m gonna do it forever, and it’s just my career now. I still love it, I think it serves a societal purpose. If you look at the way people get really wealthy, it’s through building businesses, and if you look at an advantage of the Bear Cave is I don’t just… I can monetize through subscriptions, but I’ve got a great distribution channel to promote other products. I mean, a big thing people struggle with is you can build great products and you don’t have distribution. I have great distribution. It’s almost lazy and foolish if I don’t try to build great products to take advantage of the distribution and trust I have with readers. So, it’s, to me, a natural kind of extension. I do see, you know, newsletter authors, the best might be earning millions a year, but if you really execute, you can build a company that could sell for tens of millions a year, or work autonomously. So, I love experimenting, I love trying new things. So that’s kind of just, you know, I got extra time, I got extra energy, let’s see where this goes. And that’s kind of how I think about it. I’m also incredibly bullish on prediction markets, so we’ll see. I can see myself, honestly, in the future, trying to drop everything to just exclusively focus on prediction markets.

Prediction Markets

33:19

Bryan Wagman: That’s so cool. Let’s get into that. And I want to thank you for putting them on my radar, too, because, like, literally before, you know, a few days ago, I had hardly looked into them at all, and then just, like, binged a bunch of podcasts and stuff like that this weekend. Yeah, like, what an interesting space, but I guess to kick things off, like, how did you first get involved here?

33:43

Edwin Dorsey: So, I first heard about prediction markets when I was a freshman in college. There was an ad for PredictIt, which was a kind of an academic experiment where you could bet up to $850 on political markets. Who will be the next president? Who will be the next governor of a state? What will be the margin of victory? Things like that. And it was really small, it was illiquid, you could only bet $850 into a single contract. It operated under a no-action letter from the CFTC, in which the CFTC is kind of saying, look, as long as you operate under these parameters, we’ll let you continue with your experiment. And I lost money on the first election, it kind of died down.

But then, the second election, in 2020, with Trump-Hillary, then it really started to sprout up, and I just quickly realized there’s a lot of easy ways to make money. You know, there was a monthly market for, “will Hillary Clinton get indicted?” and it’s just, it was a very low chance, and every month it starts at 8%. I’m like, this doesn’t make any sense. It’s a free $50, just max shorting it. There is so many… the numbers would add up in a multi-contract market. “Who will win the Republican nomination?” You just look at all the players, it adds up to 140. So you just short everyone, and you’ve locked in a guarantee. There’s so many inefficiencies, partly because there’s inefficiencies in these new markets, partly because of the $850 limit meant smart money couldn’t come in and correct it. So, I got… and I did really well the second time around with prediction markets, just spotting really obvious inefficiencies, where you could make tens of thousands of dollars in total, but you couldn’t make millions, because there wasn’t liquidity there, and there’s all these limits.

So, that kind of got me interested, but again, the election happens, and it dies down. And now the third time is different with Kalshi. There’s Kalshi and Polymarket. I never touched Polymarket, partly because the… the legality of it for U.S. people is unclear, but I did do… I started depositing on Kalshi for the newest election, and I was betting on it. I think I did fine on the election, but I just see all these other markets where I just start trying to trade and get edges. There’s Spotify markets, and I do well, I do poorly, but I spent kind of a year learning it, and, you know, starting 6 months ago, I really just became consistently profitable at it. I think I got edges, and… now I’m just spending a ton of time on it. I see a path that… I follow prediction market people who earn millions a year. I was like, why can’t that be me? I think there’s gonna be a big market for newsletters for prediction market traders, but also tools to help them do research better. There’s this whole new ecosystem in finance that I’m incredibly bullish on, that the exchanges exist, but the infrastructure around the exchanges don’t. So, I can make money as a participant, and I can make money as an information and infrastructure provider, and I see that as just a huge, enormous opportunity. And I can make money in the Bear Cave highlighting the companies that are gonna be hurt by prediction markets.

36:55

Bryan Wagman: Yeah, this is, maybe, maybe a broader question, but definitely want to get into the prediction element of it after, but in terms of… if you’re open to sharing this, in terms of how you think about investing your own money, like, whether it’s, I want to invest in stocks, or I want to invest in, you know, the Bear Cave, or invest in paying an engineer to build me some tools. Or, you know, prediction markets, like you said. Like, what percentage of your, kind of, portfolio or net worth would you say you’ve been allocating to prediction markets, and how has that trended over time?

37:30

Edwin Dorsey: You know, so prediction markets are liquidity constrained. If I could put all my money in prediction, I think I get higher returns there than I do in stocks. It also is a little scary because, I mean, I trust Kalshi, I believe the money is safe there, but I don’t feel as safe as in my Schwab or Robinhood or anything else. So, basically, I’ve just taken my… and also, because I’m good at what I do on there, it kind of grows naturally. I don’t need to deposit more, I have enough to take advantage of the trade. I historically have invested a lot just in stocks, large cap tech, some random small caps, not too active. I’ve shorted one or two things in my PA or an ETF, but really don’t try to do that, just because it could conflict with the newsletter. There’s not a ton of ways I can invest in the Bear Cave, per se. You know, I could spend money on advertising, but my small experiments there yielded poor results. To me, the number one thing to invest in is always trying to build new tools. So, spending money on an engineer or people to help me, that is always going to be good money, even if it fails, because you get information. So that’s priority number one. I have enough money in the markets, Kalshi, so I don’t need to put more money in. So, just keep money in stocks, be fully invested at all times, don’t use leverage, but don’t not be fully invested when you’re young, I think that would be foolish. But now it’s less, let’s say, financial resources and more, where do I spend my time? Because, Bryan, I don’t know if I look tired to you, but I work from morning till night, you know? I got no free time, ever. Other than to come chat with you. So, it’s more of a time commitment. Where am I prioritizing my time? And I think increasingly… increasingly it’s gonna get to prediction markets.

39:19

Bryan Wagman: Yeah, and so what, you know, you mentioned that it’s sort of been a journey for you of just developing that skill set and getting to the point of being consistently profitable. For someone who knows very little about prediction markets and doesn’t know what a good prediction market investor or trader looks like, or what the different kinds can look like. Can you help me just kind of understand what your journey has been like to this sort of place that you feel like you’re at now of consistent profitability?

39:49

Edwin Dorsey: So, for all prediction market traders, first, you don’t need to trade prediction markets. The best way to get wealthy is to do well at your job, consistently do well, save a little, invest in the S&P 500. That is great advice for 98% of people. You can ignore everything else. You just do that, you will do well in the long run. And if you want to experiment with prediction markets, take 500 bucks and experiment, that’s great. Number one thing with prediction markets is you always want to start small. These markets always have sharp players, even if they seem inefficient. You always are going to do poorly in the first few months. Even if you get beginner’s luck, it is… you should treat your early stages as learning. Even when I start to trade new markets, I just tell myself, I’m gonna lose a few thousand dollars to learn how they work. I’m never gonna make an absurdly big bet because I’m so confident if I’ve only traded a market for the second time. It’s… there’s so many nuances, and “rules cucked,” is what they like to say, and just weird situations that you do not make money early on. You know, you keep it very, very small.

I think another thing that’s really important is to do your own research. I kind of find with the Bear Cave, I am an information service provider, where I’m getting information, I’m servicing it, I’m digesting it, I’m interpreting it, but a lot of times, I’m going direct to the source. I’m using FOIA to get consumer complaints. I’m not relying on other people’s analysis, or at least I try not to. With prediction markets, if you want to be good, you need to think independently and get information from the source. And, you know, I think there’s a big issue where media, mainstream media, can influence prices a lot. But if you just read the media and trade off that, you are the dumb money. The smart money realizes the flaws of media and how they tend to exaggerate and be systemically wrong. One kind of great example is there’s a market for, “will the Ayatollah lose power in Iran?” Will they lose power this month? Will they lose power by March 31st? Will they lose power by the end of the year? And if you read U.S. media, it’s, you know, “Iran is doomed, Trump’s gonna bomb them, they’re done.” And the average person says, oh, let me bet on this guy losing power. Go to Polymarket, look at the market for it, and I… I kid you not, you look at the biggest no-holders, people betting on the Ayatollah staying in power, every single one has millions in lifetime profit, and every single yes holder who’s betting on the Ayatollah losing power has lost a ton of money.

It is never… you can never see a more clear smart money versus dumb money dynamic. This media likes to exaggerate, the reality is you don’t lose power unless you have military defections, and that’s not the case. Iran’s a nuclear-armed power, so you might hit them, but I don’t think you’re gonna topple them. And if regimes tend to lose power, like, even in fast revolutions, with few exceptions, it takes weeks or months of leading up to it. It does not happen, you know, by the end of this month. So there’s… start small, think independently, realize the biases caused by media, follow smart traders, and eventually, I think you’ll start getting a repeatable process that works for you.

43:35

Bryan Wagman: What’s your process for identifying and following smart traders?

43:39

Edwin Dorsey: Well, it’s easy, there’s leaderboards. So, I go to the Kalshi leaderboard, and I turn on alerts for every one of the people who are on the leaderboard. I look at, you know, there’s a trader, Domer is his name, I think he’s fantastic. I follow his Polymarket bets. I follow a few traders that I think are smart and listen to their podcasts and livestream interviews. So, it’s really, you know, that’s why I love prediction markets. In media, there’s so many talking heads. How do you know who’s credible? How do you know who actually knows what they’re talking about? It’s just credentialed—oh, this guy went to Yale, this guy comes with this—but with prediction markets, it’s pretty clear. Your track record speaks for yourself. And so, prediction markets are going to be really good at surfacing new talent and really good at also calling out the fakers of the world. I bet you there’s a lot of people in media who get tons of followers and are seen as really credible who could not outperform on the prediction markets. And then there’s people who will kill it on prediction markets who have no following. So I like prediction markets because… for so many reasons, one of which is they highlight true talent and people who are really good at predicting the future, versus people who are not. And maybe one final thing is, on prediction markets, the one incentive is being right. With traditional media, the incentive can be driving clicks, it can be driving subscriptions, it can be being right, but it can also be playing to a base or playing to biases. With prediction markets, one incentive: be right.

45:24

Bryan Wagman: Yeah. When I was preparing for this, Domer was one of the people that I read through some of his stuff, and I saw on his Twitter account that his pinned tweet—some of his recommended resources are, like, Chapter 8 of The Intelligent Investor, and Superforecasters—and I’m like, as I started to read through this prediction market stuff, I started to think, well, geez, all of these sort of ways of thinking about the world and trying to be data-driven that I’ve learned and tried to apply in investing may even apply better to at least certain markets and prediction markets, it seems like.

46:01

Edwin Dorsey: Yeah, I… you know, you want to play with less sophisticated people. So, if you’re trading mega caps, maybe it goes well. I’m not saying you can’t make money trading, but you’re going against really smart money. You go to small caps, well, you’re still going against some smart people there. You go to prediction markets… you know, I saw one quote from somebody I thought was smart: “You always want to be trading in markets where liquidity is an issue for you.” Because if you’re not, then you’re playing against smarter people than you need to play against. And you go to prediction markets, and you can easily find these niches where you can develop repeatable approaches and start printing money. Markets have gotten more efficient over time, but trust me, there aren’t that many really sharp, you know, traditional finance institutions playing on prediction markets. It is a lot easier to develop a repeatable edge than you think.

46:59

Bryan Wagman: What does your portfolio look like in terms of time horizons and sizes of bets? Because I was thinking about getting into this, you know, if I just want to throw, like, $100 at it or something, I’m thinking, like, okay, I want enough trials that I’m going to be able to learn from this, and I want them to be done in a short enough time that hopefully I can… which is part of the thing that’s so hard about investing, is sometimes the feedback loops. You don’t know if you’re right or wrong about an investment for a couple years down the road. So, when I’m thinking about prediction markets, I’m like, well, I can kind of… I can maybe intentionally shorten the feedback loop. I’m curious how you think about portfolio construction, if that’s even the correct term for prediction markets.

47:44

Edwin Dorsey: I mean, for me, I do things that are expiring generally within an hour, a day, a week, or a month. I don’t want to lock up my capital for a year or two years. Because then, even if I double it over 2 years, I could have… I could get much higher returns just getting a repeatable process in short-term markets. So, the way I think you can make most money is especially with small amounts of money, it’s just repeatable things, and there’s a lot of things for that. For example, there are markets on Rotten Tomatoes scores, trying to predict that, and you start to learn things over time. Rotten Tomatoes scores tend to fall over time, because the people who review it earliest are most excited to see it. The people who review it later are less excited to see it.

Without even the movie being released, how can you predict it? Well, how much is the studio investing in marketing? That’s a good proxy for how good they think it’ll be. When do they embargo reviews? Traditionally, if a studio says to film critics, “you can release your reviews a week in advance,” they know it’s gonna be good and build hype. But if the studio says you cannot release reviews until the movie is in theaters, then that’s a sign they think the movie’s gonna be bad. So there’s all these kind of proxies for how, you know, a Rotten Tomatoes score will be. And once you figure these things out and get to model it, if you’re playing in these markets that repeat every week, you can start kind of printing money. And I think there is a societally useful component to this, where it isn’t just aimless gambling. In Rotten Tomatoes, knowing if a movie is projected to be good or bad is really useful. So I see prediction markets as being a way to kind of digest the world’s information into societally useful ways to help people make better decisions.

49:50

Bryan Wagman: I’m imagining the sell-side firm of the future that has sector specialists focusing on Rotten Tomatoes scores.

49:58

Edwin Dorsey: Yeah, I think these markets are too small a niche, and there’s really sharp people. Your track record is everything, and they’re repeated. With finance, it’s like… I don’t know, you can kind of get lucky in the short term, you can underperform, but you’ll say it’s because you took less risks on a risk-adjusted basis. Everybody outperforms risk-adjusted, it seems like. But with prediction markets, it’s a lot clearer, it’s a lot cleaner. I think it’s a great way to digest the world’s information.

50:36

Bryan Wagman: What are… what are some of those other somewhat shorter-term markets?

50:41

Edwin Dorsey: You know, I think everybody can figure things out for themselves on prediction markets. I don’t want to steer people too much, but you know, there’s weather, there’s Rotten Tomatoes, you gotta experiment on your own. But that’s where I would be playing around if… don’t put all your money in prediction markets. S&P 500 is a lot, but don’t think “I’m gonna make money trading stocks or options.” Think, “I’m gonna make money trading prediction markets.” I think that’s where a lot of low-hanging fruit lies. And the other benefit of prediction markets is you have an enormous number of casual bettors coming through these distribution points, like Coinbase and Robinhood or whatever, who don’t know what they’re doing. So you’re not necessarily playing against the Citadels, you’re playing against just average Joes who are doing it for fun.

51:27

Bryan Wagman: And… so you’ve written on the Bear Cave about how these prediction markets are certainly a new form of competition, I guess, for the wallet dollars of people who are gambling. They’ve had some responses lately that I’m curious to hear your thoughts on, just in terms of, like, I think they had maybe their own predictions app now, and then the, what was it, Railbird acquisition? So, curious to hear your thoughts on the moves that DraftKings has made in response.

52:02

Edwin Dorsey: I think… they’re terrible. I mean, I am in Florida, where things are somewhat restricted, but I look at a lot of reviews, and I mean, everybody just hates these apps. You can’t… it’s very one-sided. It’s just like a sportsbook, still. The whole idea of prediction markets is it’s kind of peer-to-peer. I can’t go on DraftKings Predicts and start giving limit orders to give to somebody else. There’s big liquidity constraints. It’s just like a worse version of a sportsbook. I think in DraftKings’ minds, they’re just gonna call it DraftKings Predict and launch it in new markets where there isn’t legalized gambling as a way to kind of take share. But they haven’t really bought on with the prediction market model. They aren’t allowing new people to come in and participate and be counterparties to the casual bettors. They still want to own that relationship. So I… as far as I’m concerned, it’s a huge and massive miss with both DraftKings and FanDuel. I’m fairly in tune with the prediction market space; I don’t think anybody’s investing any time in trading on those platforms. They realize it’s just a way to scam casual bettors.

Future Content & YouTube

53:22

Bryan Wagman: Gotcha. Another thing I read in one of your interviews—I forget which one—but you had mentioned in passing that you were a fan of, like, MrBeast, for example, and I think there was one more YouTuber who I’m blanking on who had maybe done, like, a daycare investigation or something? Nick Shirley? Yeah, yeah, so I’m just curious to hear more of your thoughts around YouTube, and if you were to do something there someday, what that might look like.

53:50

Edwin Dorsey: I think YouTube and video is the dominant form of content. If I could see myself making a ton of money on prediction markets and just focusing on YouTube investigations. I see Nick Shirley’s video, and I admire it, I admire the impact it had, and I look at it, and I watch it, and I can think, these are 20 things I would have done differently. But I think, like, I can do that. Why am I not doing that? Why am I not getting out there? I have too many projects I’m working on. But I think video is a lot of fun. One thing that kind of frustrates me is you look at so much of these YouTubers, and, you know, it’s… I like just showing the evidence and letting people draw their own conclusions, where I think too much of media now, both creator-led and mainstream, is just telling people what to think. Well, I want to be, like, more of a neutral tone of voice, just an information provider. Let me surface the information for you in a very respectful way towards all parties. No name-calling, no calling for… just very respectful, neutral tone of voice, and let people draw their own opinions. That’s kind of what I try to do with Bear Cave.

And I think there’s a huge market for just information surfacing and letting people think for themselves. So I could see, as I’ve gotten older, my career path options have exploded, rather than narrowed. So I could see myself doing YouTube eventually. I could see myself just really focusing on prediction markets. I could see myself doing Bear Cave and traditional finance tools. I have no clue what the future has in store.

55:48

Bryan Wagman: Yeah, time will tell. This is… it’s been awesome, Edwin. Thanks so much for your time, and is there anything else that you want to let the listeners know?

55:57

Edwin Dorsey: No, Bryan, I really appreciate this interview, and I hope it’s useful for people, and maybe we’ll do it again in two years and see how things have changed.

56:06

Bryan Wagman: Awesome. Sounds good. Well, thank you so much, Edwin.

56:08

Edwin Dorsey: Thank you, Bryan.

56:09

Bryan Wagman: Alright, I’ll see ya.

P.S. Unrelated -- I’m spending time learning about the hedge fund headhunting and talent placement world, and trying to understand if there is an opportunity to serve any of the involved parties. If you work in recruiting, have placed candidates at funds, or are a fund/analyst who’s worked with headhunters, I’d love to hear about your experience. You can message me, email me at stockthoughts81@gmail.com, or book a 20m call here.

The finance side

Y Combinator’s 2026 “request for startups” includes a section on AI-native hedge funds. The thesis: the next Renaissance, Bridgewater, and D.E. Shaw will be built on AI. Swarms of agents will do what hedge fund traders do now.

Brett Caughran (ex-Maverick, D.E. Shaw, Citadel, Schonfeld - now building an analyst training firm) pushed back. His argument: big funds aren’t threatened because LLMs are still an “unreliable world calculator” — they can complete quantitative tasks about 75% of the time, which isn’t exactly keeping Renaissance up at night. And you’re not going to unseat quant firms running on massive leverage, compute budgets, and decades of infrastructure with “two guys and a swarm of agents.”

The real opportunity, he argues, is somewhere else entirely (emphasis mine):

“The much bigger opportunity is to help fundamental investors become more ‘quanty’ by regaining some of the stacked alpha into the fundamental process that quants have been eating for the last 10+ years. Building the ‘Iron Man’ suit that becomes an AI Native operating system about both internal & external data (i.e. a swarm of agents can’t walk the floor of a tradeshow or attend the JPM HC conference). No one has really done this yet, because it is an incredibly difficult, but incredibly high ROI task if done right.”

In a separate thread, he showed an example of one small tool that could arise from a mindset and a system like this — a Claude prompt that generates a structured 7-page institutional-grade technical analysis report on any ticker in about 10 minutes. One signal in a larger system.

kwak (Point72 / Perplexity) quote-tweeted Brett and added a couple of important points. The core of it:

“Most AI ‘research’ tools for finance today is simply a regurgitation of the web, which consists of the opinions of others... it generates almost no alpha because it is simply an average of public sentiment. This is like paying a HF analyst to summarize 2-3 news articles as his ‘recommendation’ - would be fired instantly.”

His argument: the real shift would be AI that can formulate a plan of attack, retrieve primary data from filings or expert calls, build analysis tools, and synthesize. He points out that the “holy grail analyst” - someone who could take any dataset (credit card data, 300 expert call transcripts, weather forecasts) and build the tools to analyze it AND turn it into a recommendation - was always the dream at big funds. Analysts refused to learn Python (and even if they did, it still took time to write). With Claude Code, it has become dramatically easier to become that person.

The software side

The same day, Gergely Orosz (who runs The Pragmatic Engineer, one of the most-read software engineering newsletters) published a conversation with Grady Booch. Booch co-created UML, spent decades as an IBM fellow, and is one of the founding figures of software engineering as a discipline.

His thesis: software engineering has gone through three “golden ages,” each defined by a rise in the level of abstraction. Assembly to high-level languages. Individual programs to object-oriented systems. And now, apps and programs to integrated systems and platforms. AI coding tools are the latest step in that pattern.

His take on the current anxiety about AI replacing developers:

“Fear not, O developers. Your tools are changing, but your problems are not.”

And on Dario Amodei’s prediction that software engineering would be automatable in 12 months, Booch pushed back. His point: Amodei is talking about automating the lowest layer (writing code), not the actual job of software engineering, which is balancing technical, economic, and human forces to build systems that endure.

The connection

These are the same conversation.

In software, the easy stuff automates first - boilerplate, repeated patterns, standard web applications. In investing, the same thing: “summarize the web” is useful but it’s consensus regurgitation. No edge.

What doesn’t automate is similar in both worlds: systems thinking, judgment calls, relationships, and field work. The scarce skill isn’t writing code — and soon it won’t be just reading 10-Ks or building models either. It’s designing and managing systems, then allocating attention, time, and capital around them.

People and companies worth following on this

• Brett Caughran

  • Check out his Cutting Edge podcast

• kwak

• Gergely Orosz

• Grady Booch

• Khe Hy

• Portrait Analytics

• Rogo

• Finpilot

• Clarity Markets (@IndraStocks)

• Jim Moran (Flat Circle)

• Who am I missing?

It’ll be interesting to watch who actually builds the “Iron Man suit” - and whether it comes from a startup, a fund building it internally, or something nobody’s thinking of yet.

PS: I’m having a lot of conversations with funds and analysts figuring out this shift — what the AI-native research workflow (or asset management firm more broadly) actually looks like, and who can build it. If that’s you, I’d love to hear what you’re seeing. DM me, reply, or book a call here.

I ran it on my personal account first since it has more data (392 tweets from the last 3 months).

Findings

Correlations with impressions:

• Original tweets do better than replies (-0.265 for replies)

• $tickers help (+0.226)

• Character count: weak positive, 150-200 chars best but noisy

Correlations with engagement rate:

• t.co present (+0.427) - see caveat below

• Character count: nothing

Day of week:

• Thursday best (4.01% engagement)

• Saturday worst (2.35%)

Questions: No effect (-0.02). Could be sample size.

What the Data Can’t Tell Me

The numbers need interpretation.

$tickers: are those impressions valuable?

Ticker tweets averaged 1,628 impressions vs 978 without — a 66% uplift. But how many of those are fundamental investors intentionally searching a ticker vs. ticker-monitoring bots and algo distribution? A tweet with $APO might get 1,600 impressions, but are those the eyeballs I actually want?

I don’t know yet.

“t.co present” is a messy proxy.

My script flags tweets containing t.co/ URLs, but that catches images, videos, quote tweets, and external links in one bucket. The +0.427 correlation with engagement is real, but I suspect images and videos are carrying it. External links to articles probably hurt. X Analytics doesn’t break these out in the export, so I can’t isolate the signal.

Questions don’t matter — waiting for more data.

The “end with a question to boost engagement” advice is everywhere. In my data: -0.02 correlation. Basically zero.

Could be my audience. Could be sample size. Could be the questions I ask. Could be that questions only work in certain formats. Flagging it but not acting on it yet.

The Faceless Account

With my personal account, I post what I want. There is no single goal.

The faceless account is trying to sell an ebook. We’re at 7 followers. We reply to podcast hosts with notes on their episodes. Do we get more replies when we ask the host a question? Or does that look spammy? We’re going to track it.

What I’m Actually Changing

Personal account: Probably a few more pictures and quote tweets. That’s about it.

Faceless account: We’re going to track it.

If you want to chat or learn more about using social media, whether you’re just getting started or more advanced, book a free 1:1 office-hours session with me here.

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The middle step is a mystery because it doesn’t work that way.

Some things that have happened to me from posting online:

• My first buyside internship came from a Seeking Alpha article I wrote in college. Someone read it and reached out.

• The following summer, another internship - through a referral from someone I knew because we’d both written for Seeking Alpha. Never met in person. Just recognized each other’s work.

• Last week I tweeted a question about the cable industry. Within minutes, someone at a large long-only fund replied and caught me up on the bear cases and how things have evolved. Would’ve taken me days to piece together on my own.

• I had an idea for a business, posted a Calendly link, and had four discovery calls booked within a week.

What these have in common:

None of these required a massive audience. They required the right people paying attention.

When I need something — information, introductions, feedback, potential customers — the network responds.

Building the feedback loop

In the gym, progress is visible. The mirror shows you it’s working.

Posting doesn’t work like that. The first few dozen followers are basically a silent grind. Eventually, you put something out, get 10 likes, and think nothing happened. But things did happen — you just weren’t looking.

• Potential Clients: Three of those people could be potential clients.

• The Excuse: You now have an excuse to DM them.

• Mindshare: They’re more likely to stop scrolling next time your name comes up.

• Referrals: Someone might mention you to a friend.

• Passive Asset: The post sits there working while you sleep.

Most people don’t track any of this. They look at follower count, see it barely moved, and assume nothing is working. So they quit.

The fix is simple: build your own mirror. After you post, write down what actually happened. Who engaged? Anyone worth reaching out to? Any DMs? Any downstream opportunities a week later?

If you don’t track the real results, you’ll never see them.

Consumption vs. production

Two ways to spend 30 minutes online.

• Consumption: Doom scrolling. You finish feeling restless, anxious, maybe jaded depending on what you read. The system designed to capture your attention got you again. 30 minutes gone, nothing to show for it.

• Production: You made something. Posted it. Now you see what comes of it, then do it again tomorrow. Chop wood, carry water.

This isn’t only about making money

Most people think “I just want to learn, so scrolling and reading is fine.” But they don’t realize how much they’re leaving on the table.

• Writing clarifies your thinking. You don’t fully understand something until you try to explain it.

• Posting brings connections. My cable industry question got answered in minutes because I’d been posting - someone recognized my work and decided I was worth helping.

• Having a presence changes how people respond to you. When you reach out to someone and they can see what you’ve written, they’re more likely to engage. You’re not a stranger asking for free advice. You’re a peer looking to engage intentionally.

Whether your goal is money, learning, or opportunities — the math is the same. Production compounds. Consumption doesn’t.

The real point

If you’re someone with expertise and something to say but no presence yet — yes, you need to grow first. You need people paying attention before you can do anything with that attention.

But grow with intention. Know what you’re building toward.

The question isn’t “how do I get more followers?” It’s “of the people paying attention, who can I help? Who can help me? How do I stay useful to them?”

That’s the difference between posting and posting to get a result.

P.S. I’m running free office hours for people figuring this out — message me or book here.

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I made a 15-slide summary. PDF here.

Original: Part 1 and Part 2

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I talked to someone recently who posts regularly on social media. He runs a small business and uses a scheduling app to queue up posts ahead of time. I asked what he’d do differently if he were starting over. Without hesitating, he said he’d start using the scheduling app sooner.

The reason surprised me. It wasn’t just about consistency or saving time. He said it gave him more time to rework the hooks. When he’s tired and posting manually, he tends to just hit publish and move on. But with the scheduler, he can draft something, walk away, and come back with fresh eyes before it goes out.

Here’s my problem: Even building to 10k+ followers, I’ve never scheduled posts. Everything has been manual - write something, copy it, paste it into each platform, hit post. It works, but only when I remember to do it, when I have time, and when I’m not exhausted.

And I haven’t done it nearly enough. Realistically, I’ve posted maybe 50–70% of the days I intended to. That sounds fine until you think about compounding. Over five years, the difference between 70% and 99% consistency isn’t 30% more posts - it’s a completely different growth curve. More viral tweets. More connections made. More people reaching out. More opportunities I never saw because I wasn’t there that day.

The fix is not complicated. A couple hours to set up a system, then maybe 30 minutes a week to batch (or just integrate it with your workflow).

I was already doing the work. I just wasn’t capturing and sharing it.

Why I never used scheduling

I’ve known scheduling tools existed for years. I just... never used them.

Why? The honest answer is that I never had the systems in place to make it easy. No batch of content ready to go. No workflow where scheduling would slot in naturally.

But there’s a deeper reason. AI and automation are becoming non-negotiable skills. If I value my time, if I want to build income online, if I’m going to be posting a lot anyway - learning to automate what can be automated is just... something that is good to be good at. It’s an ethos. This experiment is partly about consistency, but it’s also about forcing myself to build the muscle.

The tiny experiment framing

Anne-Laure Le Cunff has this framework she calls Tiny Experiments. Instead of committing to some grand plan, you try something small, see what happens, and adjust. Learning over outcomes.

That’s what this is.

The setup: Partial automation (for now)

I asked around about scheduling tools that could handle X, LinkedIn, and Substack Notes in one place. Turns out, Substack doesn’t have an API - so any tool that “pushes” to Notes is either violating their TOS or using browser automation. And Zapier’s direct Twitter integration broke in 2023 when Twitter changed their API pricing.

So full automation isn’t possible. Not yet, anyway.

Here’s what I’m trying instead: Typefully for X and LinkedIn, Substack Notes manual.

The workflow:

1. Write the post in Typefully

2. Schedule it (or save as draft to refine later)

3. Typefully cross-posts to LinkedIn automatically

4. Copy the same content to Substack Notes manually (30 seconds)

It’s not as automated as I’d like from an “automation ethos” perspective. But it’s a step. I get the core benefits of scheduling - consistency, time to refine hooks before posting, batching instead of scrambling. And I’m building the muscle of systematizing this, even if the system isn’t perfect yet.

Side note: I just signed up for Typefully while writing this. Two observations:

First, it looks nice. Clean interface, no clutter.

Second, look at what they’re highlighting:

• Write without distractions

• Schedule for peak engagement

• Track what resonates

• Cross-post everywhere

These aren’t just Typefully features - they’re the benefits of taking a systematized approach to posting in general. The tool just makes them easier to capture.

What I’m watching:

• Does this actually improve consistency, or do I just procrastinate the batch instead?

• Does having distance from the post before it goes out improve quality?

• Does this reduce the friction enough to matter?

This post is rep 1. I’m using the system to distribute this very article/the associated short-form posts. I’ll report back on how it goes.

Why I’m sharing this

I’m working on helping people build their online presence, and I think that means I should be constantly running small experiments like this on my own process. Each one is small. Each one might teach me something I can pass on.

I’m not writing this as someone who has the answer. This is me trying to move my process in a better direction, and I’m curious if this one sticks.

PS: If you’re someone with real expertise in your field who’s been meaning to start posting online but keeps putting it off, I’m building something for you. Reply to this email, DM me, or book [here: https://calendly.com/stockthoughts81/new-meeting] -I’d love to hear what’s in the way. I’m equally interested in speaking with people on the other side of this journey - who have used social media to find clients, connections, or opportunities.

Five days ago I built a personal operating system using Claude Code. This week I’ve been using it daily — and each pain point became an engineering problem to solve.

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Git workflow in practice

Day 2, I finally understood branches. Not from a tutorial — from realizing my AltsPipeline repo (separate from life-copilot, to be clear, and very much a work in progress) had 11 commits on a feature branch and 1 on main. Merged via GitHub, learned the mental model: main = production, feature branch = draft. Simple, but now I actually get it because I needed it.

Data pipeline expansion

Day 3, I wanted expense tracking. That meant modifying sync-all.py to handle a 9th Google Sheets tab, updating the schema configs in sheet_helper.py, and verifying the CSV output format matched my existing data structure. Added 15 lines of Python across two files. The system now syncs 9 data sources + calendar every 3 hours via Windows Task Scheduler.

Refactoring and tech debt

Day 4, I had 9 one-off scripts cluttering the root directory — fetch-calendar.py, add-reminder.py, etc. Archived them to archive/scripts/, consolidated functionality into the main sync module, and fixed stale documentation references. Classic cleanup: reduce surface area, single source of truth. (Note to self: always use plan mode… for pretty much everything but especially this).

Debugging a production issue

Day 5, auto-sync started failing. The scheduled task runs from a different directory than where I develop, so relative file paths broke. Fixed by updating the config loader to resolve paths relative to the script’s location, not the working directory. Classic “works on my machine” bug - only surfaces when code runs in a different context.

Configuration as documentation

After that debugging session, I added a Technical Infrastructure section to CLAUDE.md with @ file references — so the next time something breaks, debugging starts with the right context instead of grep searches.

Automated documentation for building in public

I wouldn’t have been able to recall all these details without the session archive system. Every session ends with a /shutdown command that logs what got done, what broke, what I learned. The archives become raw material — for this blog post, for future reference, potentially for automated pipelines to other platforms. I accidentally built a content capture layer while trying to give Claude context between sessions.

Security as a first-class concern

Day 4, I ran a security audit using Claude’s Plan Mode. The goal: verify sensitive data isn’t leaking into git. Result: credentials, state files, health data, and session archives all properly gitignored (not to mention this is probably staying all local, for now). But a one-time audit isn’t enough.

I’m considering building a security subagent — something that periodically scans for secrets in tracked files, sensitive patterns in committed code, dependency vulnerabilities, and gitignore gaps. I asked Claude what tooling exists for this: Semgrep for static analysis, GitLeaks or TruffleHog for secrets detection, Safety or Snyk for dependency scanning. For training/context materials: OWASP Secure Coding Guidelines, CWE Top 25, and Anthropic’s docs on building security-aware agents. Haven’t had a chance to look into them yet, and very much open to other recommendations — but the goal is treating security as continuous (almost like having an infosec team), not a one-time checkbox.

The stack so far

Python 3.11, Google Sheets/Calendar APIs via gspread and Google OAuth, Windows Task Scheduler for automation, Git for version control, structured markdown for state management.

The learning model

Real usage surfaces real problems. Real problems require real engineering. I’m not building a portfolio project — I’m building infrastructure I depend on, which means I have to actually make it work. I’m literally trying to run my life on this thing. It can’t miss stuff.

I plan to continue building more with tools like these in addition to my regularly scheduled program. Feel free to follow along.

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Below I am showing some NotebookLM slides that illustrate one of the first projects I completed - an AI-based life-copilot/executive assistant.

I’m curious to hear what others have built with these tools, as well as how others approach the underlying time/energy allocation issue that this system attempts to address.

I spend a big chunk of my time on expert calls, and they’re genuinely my favorite part of the job. The question I keep coming back to is: how do I take what I hear on those calls and turn it into actual numbers in the model?

Not “use” in the vague sense of “it informed my thinking,” but in the literal sense: what number do I plug into the cell for cents per gallon (CPG), long-term volumes, or normalized margins after I hang up?

I’m not writing this as someone who has the answer. This is me trying to move my own process in a better direction, and I’d genuinely love feedback from people who’ve been doing this longer and at a higher level.

The tension: prodding vs keeping the relationship

On almost every expert call, there’s a moment where I could push a little harder.

• “When you say ‘margins are pretty healthy’… what does that actually mean in cents per gallon?”

• “When you say ‘down a touch’… is that 1–2%, 5–10%, or something else?”

• “When you say ‘single digits’… do you mean 1–3% or 7–9%?”

But there’s always a trade-off in the back of my mind:

• If I push too hard for precision, do I come off as transactional or annoying?

• Will this person be less willing to talk next time?

• Am I turning a good, open conversation into an interrogation for the sake of a model input that isn’t even “my” number?

So I sometimes back off a little earlier than I should. I walk away with a sense of the direction and some rough boundaries, but not always with numbers I feel comfortable tying directly to a cell.

That’s the core tension I’m trying to work through: how to get (and ultimately use) more output from a call without ruining the relationship or the vibe of the conversation.

The “false precision” trap (and what to do instead)

One understandable reaction is: “Don’t overthink it. Put in 40 cents per gallon and move on. The model is approximate anyway.”

I get that. Fake precision is dangerous.

But if I’m going to do the work and make the calls, it feels like I should aim a little higher than “eh, 40 cents seems fine.” The point isn’t to pretend I know the exact right number. It’s to use what I’ve learned to narrow the range on the 2–5 variables that actually drive the outcome.

In practice, that probably means:

• Actually tallying what I’ve heard from people who live this every day

• Putting some structure around the ranges for CPG, volumes, and margins

• Letting those ranges show up explicitly in the model, instead of just in my head

If I do twenty calls on an industry and hear a bunch of data points on CPG, volumes, and store productivity, it seems odd for all of that to collapse into a single “0.40” that’s mostly based on vibe and conservatism.

A better goal might be something closer to how superforecasters handle key variables: carefully collecting base rates and ranges, tracking how views differ by segment or cycle, and then updating as new information comes in. The output doesn’t have to be a single magic number; it can be a range with a clear center of gravity and a few explicit scenarios.

That’s the direction I’m trying to move in: still humble about what I don’t know, but a little more intentional about using what I do learn, instead of hiding behind “false precision” as a reason not to decide.

Moving toward a “superforecaster” approach on 2–5 key variables

I don’t think every line in a model deserves this treatment. Most don’t.

But for the 2–5 variables that actually matter, I’m starting to think they do:

• Cents per gallon over the cycle

• Long-term volume trends

• Normalized inside-store margins

• Realistic cadence for unit growth or closures

• Maybe one or two company-specific levers

The idea is to treat each of those like its own mini-forecasting problem:

1. Build an input tab just for that variable.
   Not a mess of assumptions, but a simple place where all the relevant data points live: every range, quote, or directional statement from management, competitors, and experts.

2. Tag the sources and context.

   • “Single-store operator — Midwest — said 25–35 CPG ‘through the cycle’.”

   • “Jobber, Southeast, said recent margins feel ‘elevated versus history’ and might normalize lower.”

   • “Public comp: disclosed X CPG in 2018–2024, with Y volatility.”

3. Make the range explicit.
   Instead of pretending there’s one “true” number, actually write down (making up numbers):

   • Base case: 30–35

   • Bull: 35–40

   • Bear: 20–25

   And link those ranges into the scenarios rather than a single “best guess” hard-coded into the model.

4. Let the model reference the range.
   If I’ve done the work and the weighted average of everything I’ve heard points to 30, then I shouldn’t plug in 40 just because management and consensus said so.

This is less about worshiping precision and more about respecting the information I’ve chosen to spend my time collecting.

Actually using the call: comments, ranges, and receipts

One very practical change I may experiment with is simple:

Where the key input lives in the model, I add a comment that lists:

• The 5–10 experts I’ve spoken with

• What range they gave (or what their qualitative language implies)

• Any public data that cross-checks it

Something like:

“CPG assumption (30–35):
– Operator #1 (TX, 20+ yrs): ‘Used to be low-20s, now 30+ feels normal.’
– Jobber #2 (Southeast): ‘Mid-30s right now, don’t count on it lasting.’
– Public comp A: 2018–24 avg ~28, last 2 yrs ~33.
– Public comp B: similar pattern.”

Is it perfect? No. It isn’t perfect but it forces me to actually use the work and be rooted in the data.

It also has two side benefits:

• Future-me can see it. I won’t remember in two years why I picked 32 vs 35 unless I write it down.

• It’s shareable. If someone else on the team opens the model for the first time, they can easily see where my numbers came from.

How to ask for numbers

On the call-side, I’m trying to get a little more intentional about how I push for numbers so it feels less like a cross-examination and more like a collaboration.

A few things that may help:

• Offering ranges in the question.
  “When you say ‘pretty healthy’, is that more like 20–25 CPG or 35–40?”
  People seem much more comfortable reacting to a range than producing a point estimate from scratch.

• Anchoring to history.
  “Versus, say, 2018–2019, are margins today 5 CPG higher, 10 higher, or about the same?”
  It’s often easier for operators to compare than to level-set.

• Being explicit about why I’m asking.
  “I’m not trying to pin you down to the penny, I’m just trying to avoid making up a number on my end that’s way off from reality.”
  That would probably disarm people a bit.

I don’t think this eliminates the risk of annoying someone, but it feels more honest: I’m telling them what I’m trying to do and why.

Where I’m still unsure

Here’s where I’d especially love pushback from more experienced people:

• How far do you go before you’re overfitting?
  At what point does all this become pseudo-scientific, dressing up a fundamentally uncertain world in too much structure?

• How much weight do you give experts versus your own prior?
  If my prior is 40 CPG and ten smart people all cluster around 30, how aggressive should I be in moving?

• Do you formalize this (model features, checklists, templates, etc.), or just do it in your head?
  I’m tempted to build a more explicit “superforecaster-style” tab for the 2–5 big drivers in every name. Not sure if that’s a good discipline or busywork.

Closing

The direction I’m trying to move in is simple:

If I’m going to invest time in expert calls, I want the work to show up where it matters: in the few cells that actually drive the investment.

That means:

• Asking slightly more targeted questions on the call

• Aggregating what I hear in a structured way

• And letting that structure influence the model more than my mood or my desire to feel “conservative”

I’m not there yet. This is very much a work in progress.

If you’re a PM or a senior analyst who’s wrestled with this, I’d genuinely love to hear how you handle it: what’s worked, what hasn’t, and any traps I should watch out for as I try to push my process in this direction.

Disclosure: none of this is investment advice, I/we may own positions in securities mentioned.

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TL;DR

Carlyle took AIG’s legacy run-off vehicle and, using a capital-light model, helped stand up Fortitude Re - a Bermudian reinsurer that’s executed a string of sizable block and flow deals. Carlyle monetizes this relationship in four distinct ways:

1. A Perpetual Advisory Fee: A stable fee (approx. 10 bps) on Fortitude’s entire general account (GA) of ~$70-80b.

2. “Rack Rate” Fund Fees: Full management fees (e.g., 50-130+ bps) on the ~$21.7 billion of GA assets Fortitude has committed to various Carlyle funds.

3. Fund Management Economics: Carlyle (as the GP) earns management fees (and potential carry) on Carlyle FRL, the fund vehicle that holds the majority stake in Fortitude.

4. Direct Investment Income: Carlyle (the firm) earns its pro-rata share of Fortitude’s profits/dividends via its ~10% balance sheet investment (as an LP) in that same fund.

Fortitude Re: History & Background

• Aug 2018 — “DSA Re” partnership announced. AIG and Carlyle agree that Carlyle will buy 19.9% of AIG’s legacy reinsurance platform (then DSA Re, formed earlier that year) and enter a strategic asset-management relationship. DSA Re and AIG, in aggregate, plan to allocate $6B into Carlyle strategies.

• Nov 2018 — Rebrand + close. Deal closes; DSA Re is renamed as Fortitude Re; Carlyle’s 19.9% stake is confirmed.

• Nov 2019 → Jun 2020 — Majority sale from AIG. A newly formed Carlyle-managed fund, alongside T&D Holdings, agrees to and then closes on a 76.6% acquisition of Fortitude Group Holdings for $1.8B; pro forma ownership at close: Carlyle & its fund investors 71.5% (incl. the earlier 19.9%), T&D 25%, AIG 3.5%.

• Mar 31, 2022 — Growth capital + new advisory deal. Carlyle raises $2.1B for Fortitude (incl. T&D); CG will commit up to $150M. The raise expands Fortitude’s capital base and reduces CG’s direct stake (from 19.9% → ~10.5%). Simultaneously, a new strategic advisory agreement is expected to add ~$50B to fee-earning AUM and ~$50M in annualized FRE (effective Apr 1, 2022), with Carlyle expecting to more than double that FRE by 2025.

• Today — Multi-line reinsurer executing block + flow. Fortitude now runs a large, diversified book (life/annuity + P&C run-off; plus flow). According to the 2024 Group FCR, Fortitude’s ultimate parent (FGP) has four principal owners with the following undiluted interests: a Carlyle-managed fund (Carlyle FRL) at 38.53%, a Sovereign Wealth Fund at 32.64%, T&D at 26.37%, and Corebridge (AIG) at 2.46%. The Sovereign Wealth Fund was a former LP in Carlyle FRL and received its direct stake via an in-kind distribution after exercising an option for direct ownership.

People

Fortitude’s DNA features both Carlyle and AIG significantly. The first CEO, James Bracken, had been at AIG for 12 years (most recently as CFO - General Insurance). Brian Schreiber (MD and Co-Head of Global Financial Services Partners at CG in 2018; currently Head of Carlyle Insurance Solutions) had spent 20 years at AIG before joining CG in 2016. There are a number of notable management team and board members at Fortitude:

• Schreiber remains Chairman of the Board

• Alon Neches - Current CEO of Fortitude

  • Sept 2022 - Present: CEO of Fortitude

  • 2020-2022: MD and Partner at Carlyle Insurance Solutions

  • 2011-2019: various senior positions at AIG

  • 2009-2011: Restructuring at Federal Reserve Bank of NY; managed the Fed’s AIG investment

• Jeff Burman - General Counsel of Fortitude. Previously Deputy GC - Reinsurance at AIG.

• Mark Jenkins - Board member at Fortitude and Head of Global Credit at CG

• Several other impressive members of board and management I did not mention (see here).

• It’s worth noting there has been some turnover over the course of the past few years

  • Former CEO - James Bracken

  • Former Chief Life and Annuity Reinsurance Officer - Guillaume Briere-Giroux (only there for 11 months)

  • Former Chief P&C Reinsurance Officer - Jack McGregor (farewell post)

Carlyle Strategic Rationale

Carlyle’s venture into insurance with Fortitude Re is a deliberate, “capital-light” strategy designed to extend its core investment management franchise rather than transform Carlyle into a balance-sheet-heavy insurer. The primary rationale was to tap into the massive, long-duration asset pool of the insurance industry, creating a significant, scalable, and permanent source of fee-earning AUM (FEAUM) without assuming the direct leverage, volatility, and regulatory burdens of an insurance operator.

The strategy creates primarily two distinct, high-margin revenue streams for Carlyle:

1. A Perpetual Advisory Fee: Through a 2022 strategic advisory agreement, Carlyle earns a fee on Fortitude’s entire general account. This fee is approximately 10 basis points (totaling $74 million in 2024 on a ~$75B GA) and is structured as a perpetual contract. This provides a stable and growing base of high-margin Fee-Related Earnings (FRE), as the teams and platform to manage the assets are largely already in place. The initial 2022 agreement, for example, added $50 billion to Carlyle’s FEAUM and an initial $50 million in annualized FRE (and we know the fee rate is ~10bps).

2. High-Fee Fund Allocations: Fortitude allocates a significant portion of its general account, totaling ~$21.7 billion in committed capital as of mid-2025 (or ~25% of its GA), into various Carlyle funds. On this capital, Carlyle earns its full “rack rate” management fees (e.g., 50-130+ bps), which are substantially higher than the 10 bps advisory fee. To put this in perspective, this makes Fortitude Carlyle’s largest and most strategic LP. The relationship represents ~$22B in committed capital plus a ~$75B advisory mandate, a massive footprint against Carlyle’s $465B in total AUM.

This structure creates a powerful flywheel. As Fortitude grows its general account by executing large, “B2B” reinsurance deals for complex blocks (like the $28b Lincoln transaction, $3b Unum, or the $4b Taiyo Life deal), Carlyle’s 10 bps advisory fee base grows immediately, and the pool of capital available for high-fee fund allocations expands, driving a second layer of FRE.

By the Numbers: Quantifying the Fortitude Relationship

This relationship is already highly material to Carlyle. Fortitude’s audited financials show a $74 million “Strategic Advisory Services” expense paid to Carlyle in 2024. For context, Carlyle reported $1.1 billion in total Fee-Related Earnings (FRE) for 2024.

The advisory fee alone thus represents ~6.7% of Carlyle’s total FRE ($74M / $1.1B).

This percentage doesn’t even include the second, higher-margin stream: the full “rack rate” fees from Fortitude’s ~$21.7B in committed capital. When factoring in those additional fees (plus, note that management guided the Lincoln deal alone would add $40M in incremental FRE), the total Fortitude-sourced contribution is even higher.

Open Questions and What To Watch For

• Advisory-fee “doubling” scorecard. In Mar-2022, Carlyle said the new Fortitude advisory would add ~$50m annualized FRE and that they expected to more than double that by 2025. Fortitude’s audited financials show Strategic Advisory Services expense to Carlyle affiliates of $74m in 2024 (vs. $52m in 2023). That expense line is the best public proxy for the gross advisory take; it grew ~1.4–1.5× vs. the ’22–’23 base, but that doesn’t translate 1:1 to FRE (though it is probably close to it). Bottom line: as of FY-2024 they hadn’t “doubled” on a clean, apples-to-apples FRE basis, and 2025 is still TBD until Fortitude/FGH and Carlyle report. Lincoln should help some and possibly get them quite close given management guided to $40m incremental FRE from the deal over time.

  • Could “>2×” happen without GA/NIA growth? Unlikely. The advisory bps are banded and tied to Fortitude profitability; with returns drifting down a bit over time (Fortitude’s core ROA was 1.06% in 2024, down from 1.32% in 2023), getting to “>2×” looks tough.

  • However, it is worth noting that in recent public commentary management has been very upbeat about the amount of activity Fortitude is seeing. It would only take a few large blocks (or another Lincoln) to get them to their target. Perhaps even just Lincoln is enough.

  • On the Q3 2025 earnings call, Carlyle’s CFO stated that Fortitude’s recent initiatives (including the Unum deal and the new Asia sidecar) are expected to generate “more than $20 billion of new AUM in the intermediate term”

• A new growth lever: FABNs. Fortitude just entered the Funding Agreement-Backed Note (FABN) market with an inaugural $500M issuance in October 2025. This is a key tool used aggressively by peers like Apollo’s Athene ($11B+ issued in 2024; almost $30b total from all funding agreements) to raise liabilities at scale from institutional investors. While this first deal is small, watch if Fortitude scales this channel; it could significantly expand its capacity to fund large reinsurance deals, further accelerating the growth of Carlyle’s advisory and fund fee base. From Athene’s 2022 Retirement Services update:

  

• The black box problem. Like all insurance, Fortitude is somewhat opaque. While Carlyle investors get the fee stream without the direct balance sheet risk, the sustainability of that fee stream depends on Fortitude’s viability. You’re trusting management on complex asset-liability management (ALM), navigating complex regulations across different jurisdictions (e.g., Bermuda), and dealing with limited disclosure on reserving assumptions, surrender rate models, and longevity risk. While Fortitude has a deep bench of 170 actuaries, it has also seen notable departures (CEO plus both reinsurance chiefs). For Carlyle investors, the key comfort remains: they’re getting the fees without the direct leverage and blow-up risk of owning the insurer.

• A new growth lever (Asia): In parallel with the FABN market, Fortitude is expanding its global footprint. In Q3 2025, it “launched a reinsurance sidecar focused on driving growth in Asia”, capitalized with over $700 million, to pursue reinsurance deals in the Japanese market (where they are already a very strong player). This creates another avenue for AUM growth outside of the competitive U.S. market.

Disclosure: None of this is investment advice, I/we may have positions in securities mentioned.

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Who this is for

Fundamental investors, curious generalists, and anyone tracking the big alternative-asset platforms (Apollo, KKR, Carlyle, Blackstone, Brookfield, etc.) who keeps hearing about insurance partnerships and wants a plain-English explainer.

Why read this

Alt managers are already public-market compounders: recurring fee engines with operating leverage, reinvestment runways (or capital return), and multiple “adjacent” growth vectors (private credit, real assets, wealth/retail). Several of the largest platforms have also tied their fortunes, in different ways, to insurance balance sheets - either by owning an insurer (e.g., Apollo/Athene; KKR/Global Atlantic) or advising one (e.g., Carlyle/Fortitude Re). Understanding those links is now table stakes for analyzing the group.

The simple thesis (and where insurance fits)

The core point: these are good businesses first; and “insurance” is a key topic to understand about them. Insurer relationships push large, long-duration, relatively sticky assets into the platforms’ credit/specialty sleeves. The fee rates can be lower, but durability and scale can raise the quality and predictability of fee-related earnings (FRE).

At the same time, insurers globally are reallocating into private credit / “private investment-grade” as regulatory and market structures evolve, with banks ceding share. That secular flow is a tailwind for scaled originators across the alt platforms, even as regulators increase scrutiny of insurers’ private-credit exposures and capital treatment.

Two models (very high level)

• Own the insurer (balance-sheet model). Platforms that own an insurer (Apollo/Athene; KKR/Global Atlantic) capture spread income and fee revenue. The mix is capital-intensive but can produce durable, scaled earnings if ALM and ratings/capital are well managed.

• Advise/manage under contract (capital-light model). Others provide advisory/IM services to an insurer (e.g., Carlyle/Fortitude Re), earning primarily fee income.

Why this space compounds (and how insurance can reinforce it)

• Trading fee rate for durability. Long-dated liabilities can anchor multi-year fee streams and smooth earnings; lower headline bps can be outweighed by persistency and operating leverage in FRE. Carlyle’s Fortitude setup is a live case study in “profit-banded” fee durability.

• Distribution for private credit. Insurers are natural homes for investment-grade private credit and asset-backed finance that large alts originate, an area expanding across insurers and wealth channels.

• Platform flywheels. Owning origination, underwriting, and servicing creates internal “supply” of assets for insurers and third-party clients. Apollo and KKR both emphasize these synergies.

…and the guardrails

I’m not an insurance analyst, and I won’t pretend to assign precise probabilities to ALM or statutory capital scenarios from public filings alone. Real risks include ALM mismatches, ratings/capital pressures, and credit cycle exposure; there’s also ongoing regulatory focus on insurer allocations to private credit and on Bermuda-based asset-intensive reinsurance. I’ll stick to plain-English summaries, simple ratios, and clearly labeled questions.

What I’ll publish

Short notes on four platforms (probably CG, KKR, APO, BAM), each with:

• a short explainer of their insurance setup (own vs. advise; where earnings show up),

• analysis of recent key metrics

• the open questions I’m still working on.

Early read on KPIs (draft, comparable on purpose)

Advisory/IM model (e.g., Carlyle–Fortitude)

• Average GA assets under fee (simple average, annual).

• Advisory bps on GA = advisory fees ÷ average GA assets × 10,000.

• Carlyle-linked % of invested assets (disclosed items only; conservative floor).

• Blended advisory+IM bps on GA (for context).

Rationale: This reveals durability (average base), actual fee economics (bps), and “how much of the GA is truly with the platform’s strategies,” not just headline AUM from an advisory contract.

Owned model (e.g., Apollo/Athene; KKR/Global Atlantic)

• Net investment spread (company definition; track trend).

• Retail/institutional inflows & retention (directional; durability signal).

• Capital/rating cushions (very high-level; statutory/RBC or BMA disclosures).

• FRE attributable to insurance AUM (to see the fee engine, not just spread).

Rationale: This captures the spread engine’s quality and the fee engine’s scale, both emphasized by Apollo/KKR in public materials.

How you can help

• Point me to public documents you’ve found useful (investor days, audited financials, regulator filings, primers).

• Tell me the 1–2 KPIs you’d actually monitor for each platform.

• If you work or invest in the space, I am always looking for people to talk to.

Guiding questions I’ll keep working on

• Which model (own vs. advise) best converts insurer balance sheets into durable, high-quality earnings without overloading risk?

• What’s the fairest all-in way to compare fee-rate + spread economics across platforms?

• What public signals would flag rising ALM/credit or ratings pressure early? What is the best way to assess these sorts of risks, and how knowable is it?

• How big should insurance be inside a diversified alt platform?

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Letter to Self

Bryan,

The reason you're here, in Act Two, is to consciously move toward a different future. The goal isn't just a new project; it's a new relationship with work and life. It's the pursuit of the "pathless path."

Your Why: What is Beyond the Horizon?

What you're aiming for is a feeling: freedom, autonomy, agency. It’s a life not dictated by a 9-to-5 schedule or a capped salary someone else determines. It's about building something where the effort you put in is directly tied to the value you create and the flexibility you earn. That's the horizon. For the next five weeks, every action is a step in that direction.

Your What: The Five-Week Experiment

You've been circling several ideas—the podcast, the e-commerce project, short-form video. They're all valid vehicles. But right now, hesitation is the enemy of momentum. For this five-week sprint, we have to pick one and commit.

The choice is the Private Equity Newsletter.

Why? Because you have a head start. It builds on your existing knowledge and subscriber bases, leverages your interest in writing, and doesn't depend on scheduling guests or managing inventory. It’s the most direct route to creating something that signals expertise. This isn't a life sentence; it's a focused experiment. We're committing to this vehicle for five weeks. That's it.

Your plan is to run a "pilot season" on this Substack for these five weeks, focusing on sharp, data-driven insights rather than comprehensive buy/sell calls. You envision publishing one focused, high-leverage piece per week. This feels achievable within the 5-7 hours you're committing and aligns with the "tiny experiment" ethos. Possible topics include shifting AUM mix over time, compensation (FRE vs incentive), the opportunity in retail, etc.

Your How: Overcoming the Obstacles

Let's be honest about what's tripped you up before: life gets busy. A new job, travel, and a dozen other things can crowd out the deep work. The commitment becomes inconsistent, and things don't get published.

This time is different because of the structure and accountability of this program. The work has to get done and, more importantly, it has to get published. That means carving out the time on nights and weekends and treating this project with the seriousness it deserves.

Your Horizon: A Measurable Moment

In five weeks, how will we know this mattered? It won't be about massive follower counts. Success will be clear and specific:

• Publish four focused posts on the publicly-traded PE/alts space (KKR, CG, BAM, APO, BX, etc.).

• Earn one subscriber who is a "quality" connection. Someone who works for, invests in, or deeply understands the private equity world. One reader like that is proof that the signal is cutting through the noise.

That's the goal. It's tangible and it's meaningful. It’s the first step on the path.

Let’s get to work.

Open Questions

Here are a few things I am thinking about:

• What topics sound the most interesting?

• Would written interviews with PE professionals add value?

• What are the best existing resources to learn more about the publicly traded asset managers? Who are the most knowledgeable people out there?

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• The core conflict: This is a classic deep-value situation, resurrected by a crucial debt restructuring in June 2024. The central question is whether this deal marks the beginning of a sustainable operational turnaround, or just another couple years of survival for a business in terminal decline.

• Company snapshot: Regis is a leader in the haircare industry, primarily operating as a franchisor of well-known value salon concepts such as Supercuts. Over the course of the past 15 years or so, location count has declined from ~12,000 to ~4,000. SSS have been consistently negative since the Great Recession, up until very recently.

• Recent events:

  • June 2024 refinancing: An existential crisis was averted when Regis renegotiated its debt, receiving an ~$80 million principal reduction while extending maturity from August 2025 to June 2029. This event reset the capital structure (gross LTM leverage went from 7.9x to 4.4x) and put the stock back on the screen for value investors. The stock went from $5 to $20 on the news.

  • December 2024 Alline acquisition: In a strategic pivot (or return), Regis acquired its largest franchisee, reintroducing a significant company-owned portfolio. They paid $22m (~3x EBITDA including $1.5m synergies).

  • June 2025 leadership transition: The CEO who orchestrated the turnaround suddenly stepped down, introducing significant uncertainty about future strategy and leadership.

On paper, the investment case appears straightforward: a post-restructuring company trading at a low multiple of potential cash flow. However, this simple valuation story is clouded by a decade-long struggle with declining sales, a fiercely competitive market, and an abrupt leadership change. All this is made more concerning by a lack of recent insider share purchases. Substantial execution risk is therefore the central theme. The bull case requires new leadership to successfully engineer a turnaround that has eluded the company for years.

Background: A Decade of Decline Followed By A Glimmer of Hope

Going back and reading all the VIC writeups on RGS starting with the first one in 2010 and finishing with the Messages on the latest is an interesting experience. It has been written up seven times (six long, one short).

For our purposes, let’s go back to 2011, when Starboard (an activist with a 4-5% stake) wrote a letter detailing the current situation. Here are some of the facts from that letter:

• RGS trading for 4.6x consensus 2012 EBITDA

• Significant share price underperformance:

• Bloated cost structure:

  

  • “[Overhead] costs have grown over 70% since 2004, while revenue has only increased 20% over the same period.” EBIT margins declined from 9.4% in 2004 to 4.5% in 2011 (LTM).

• RGS owned several noncore assets. Mainly “two wholly-owned business units, Hair Club and 400 International salons, as well as two minority owned assets, Provalliance and Empire Education Group.”

Now, where are we today? And what was the path to getting here?

• SSS haven’t shown any sort of sustainable return to positive territory (though perhaps we are turning a corner now with comps ~flat-slightly positive in the June quarter).

  

• As mentioned, total store count declined from ~12,000 to ~4,000

• The company embarked on an intentional shift to franchising starting in FY17. In FY16, 27% of total locations were franchised. That figure rose to 99.6% by FY24, though it is now back down to 92.4% due to the Alline deal.

• The stock is down ~93% since 2011

• EBITDA declined from $158m in FY11 (a 7% margin) to $25m in FY24 (a 12% margin).

• Regis has seen five different CEOs since 2011 (excluding Interims), with the fifth just announcing his decision to step down a few weeks ago.

So, things were looking bleak last June with the market cap at ~$12m. And then Matthew Doctor, the CEO, pulled off the refinancing and the stock was given another life.

Then, a few months later, management decides to use their newfound flexibility to purchase their largest franchisee. Kind of unexpected! 314 salons were added to the Company-owned salon count. While the company considered it a new lever for growth and a testbed for initiatives, it also reverses that stated asset-light strategy while introducing further operational complexity.

And in the midst of all this, the CEO announced on June 23 that he would be stepping down on June 30.

The Bull Case: It’s “Cheap”

… and maybe there is a clear path to much higher FCF in the near future. Actual LTM FCF is $11.3m, having recently inflected materially higher “driven by Alline operating profitably, lower use of working capital and lower cash interest.”

Let’s build this up another way:

• Let’s say baseline EBITDA is $32m. I could see this coming in a bit lower next FY if a lot goes wrong, or perhaps as high as the mid 30s if a lot goes right. But let’s use $32m. Note - this also includes some noncash items (franchise fees, amortized broker fees, etc.) - but this is meant to be a ballpark illustration.

• Less $20m interest (~$15m of which is actually cash due to the PIK, but let’s use $20m)

• Less $1m for maintenance capex (perhaps this could be a bit higher now that they bought Alline, but in the March 2025 quarter it was $300k).

• Note cash taxes will not be a factor anytime soon as they have ~$490m of NOLs

• This gets us $11m in FCF.

• Some other things that could get you an even higher number

  • Assuming they refinance the debt sometime in the next couple years, while putting FCF toward the principal in the interim, could significantly reduce interest expense. Perhaps by as much as $5-10m between deleveraging and refinancing.

  • Other operational improvements such as those outlined in this investor writeup. And just executing well on Alline. I do not have a good sense for how achievable these are. My intuition suggests there is probably some low-hanging fruit if you get a great operator in here, but I cannot speak to the feasibility of the specific savings sources mentioned in the writeup, nor the probability that Alline synergies are achieved.

So, it certainly isn’t impossible to see a scenario where we are sitting at a sustainable $20m+ within a couple/few years. On a current market cap of $47m, that’s ~2.5x FCF. However, it’s important to remember how much leverage there is here. On an EV/FCF basis, this is ~7.25x FCF. Still on the low side, but not quite as attractive when you consider the long history of operational issues, stubborn negative growth patterns, and the long list of execution risks required to get to that $20m FCF (and prove to the market that it is sustainable).

Complementing the bullish view is a couple of strong datapoints from recent quarters:

• For the first nine months of FY25, cash from operations was up $14.1m year-over-year.

• 6/23/25 PR: “The company reports positive preliminary quarter-to-date same-store sales growth of 3.0% for Supercuts and 1.3% on a consolidated basis for the first two months of the fourth quarter of fiscal 2025 as compared with the same periods last year [note there is some Easter benefit here]. Month-to-date same-store-sales through June 15, 2025 for Supercuts and Regis Consolidated are also positive as compared with the same period last year. Quarter-to-date operating expenses have remained consistent with the third quarter of fiscal 2025.”

  • Bulls attribute this stabilization to specific management initiatives that are gaining traction, such as the nationwide rollout of the Supercuts Rewards loyalty program and new brand excellence standards designed to improve the customer experience.

Finally, the Regis system is arguably healthier today than it has been in years. The painful, multi-year process of closing thousands of underperforming salons is largely complete. This portfolio rationalization has left Regis with a smaller but stronger and more profitable base of locations, providing a more stable foundation from which to build future growth.

The Other Side of the Coin: Risks and a Final Word

Despite the green shoots, the bear case for Regis remains substantial and is rooted in a long, challenging history. A decade-plus of negative same-store sales and failed turnaround attempts has created deep-seated skepticism. While recent SSS data is encouraging, these modest gains are fragile and have yet to prove they can reverse a secular trend in a fiercely competitive industry where rivals like Great Clips have thrived during Regis’s decline. It’s interesting to note that Great Clips is now at ~4,400 locations vs 3,000 in 2011, while Regis’ store count has declined dramatically during this time. Regis has also lost their spot on the Entrepreneur Franchise 500 list, while Great Clips has ascended to #33.

The execution risk is amplified by the abrupt departure of the CEO who orchestrated the refinancing. This creates a leadership vacuum at a critical juncture, raising questions about strategic continuity and the company’s ability to attract top-tier talent. Furthermore, the Alline acquisition, while presented as a catalyst, can also be viewed as a strategic gamble. It reverses the company’s stated asset-light strategy, reintroduces operational complexity, and requires management to prove it can run stores more effectively than the experienced franchisees it just bought out.

Financially, the argument is not a slam dunk. A ~5x EV/EBITDA multiple may be a fair price, not a cheap one, for a business with this profile. There is a long history of operational missteps, stagnant growth, and poor FCF conversion. The new debt, while manageable, is expensive at SOFR + 9.00% and will consume a large portion of cash flow until a potential (but not guaranteed) refinancing can occur.

The bull path sees a new leader successfully build upon the new foundation, optimize the Alline portfolio, and secure a favorable refinancing, unlocking the company's free cash flow potential and leading to a substantial rerating. The bear path sees the company revert to its historical pattern of decline, hampered by operational challenges and leadership turnover, with the high-interest debt continuing to weigh on the equity.

The outcome is almost entirely dependent on execution. While the valuation offers a potential margin of safety, the significant operational and leadership risks make this a classic "too hard pile" for many investors (hence the stock languishing around the level it has been at since the refinancing). There are simply too many moving parts and unanswered questions to have high conviction in either direction.

Appendix and Misc. Notes

• I’d like to better understand whether longs think working capital will be less of a use of cash than it has in the past, and why. This is an important area to deep dive with both management and other investors to better understand the likely future conversion of EBITDA into FCF vs historical rates.

• Be careful to exclude lease liabilities in debt calculation, which are ~90% the franchisees’ (and hit the income statement anyway). They are also all operating leases.

• Don’t forget warrants from the refi in valuation

• Other potential contacts and resources

  • William Charters - part of a now-disbanded activist group that used to own ~8-9%. Articles available on Seeking Alpha.

  • Gary Wyetzner. Part of the above referenced group. Insights available on X and LinkedIn.

  • Galloway Capital - activist.

  • Jeff Moore - investor, active on Twitter

  • EagleFangCapital on Twitter seems to follow it

  • Maverick_Investr on Twitter seems to follow it

  • Industry expert and former exec https://www.linkedin.com/in/eabakken/

  • Industry expert from the group that sold Alline https://www.linkedin.com/in/michael-sarafa-418052120/

  • Michael Reinstein (Regent LP) purchased a large group of salons back in 2017

  • Kent Lake Capital

Disclosure: this is not investment advice, I may own positions in securities mentioned

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Matt's bio: "As a coach, I guide ambitious professionals to cultivate human agency and self-awareness. I also write ⁠More Human Possible⁠, my blog that explores the inner and outer worlds of being human."

Matt's coaching site: ⁠https://mattyao.co/⁠

Timestamps

0:00:00 Bryan discusses leaving his job and exploring different opportunities.

0:00:57 Bryan talks about his newsletter and content creation goals.

0:03:07 Matt shares his recent move to Palo Alto and looking for new opportunities.

0:05:14 Bryan asks Matt about balancing focus and diverse interests.

0:06:20 Matt offers advice for a first-time podcaster: enjoy the process.

0:07:51 Matt discusses the idea of a portfolio career and not being meant for one job.

0:10:48 Bryan expresses his fear of missing out by not going "all in" on one thing.

0:11:56 Matt suggests that focus and multiple interests can coexist by eliminating wasted time.

0:24:49 Bryan discusses navigating career opportunities while maintaining his passion for writing.

0:31:05 Matt mentions the attention economy and honoring the reader's attention.

0:45:47 Matt reveals his potential niche for coaching: people considering quitting their jobs.

0:57:37 Bryan asks Matt about his work with clients on tech addiction.

…

Bryan Wagman: Yeah, so basically, just to kind of jog your memory, I left my job back in March, and so my last day was March 19th. And I still don't really fully know what I want to do, but I'm looking at a consulting opportunity, so that'll be a month-to-month, independent contractor type setup. So, waiting to get approval for that from the guy's boss, basically. And hopefully, that'll pan out. And if so, it'll be, a fully remote opportunity, and just kinda take it one month at a time and see if it works for both of us. So, but there's been, a lot of exploring over the course of the last few months and trying to figure out what I want to do with my life. And I still haven't really figured that out. I looked a lot into entrepreneurship through acquisition and things like that, and potential, other jobs to go to, whether remote data analyst type stuff, things like that. And I'm trying to write a newsletter. That's kind of my main thing. I wanna write an investment Substack. And so I'll be working on that, trying to do two write-ups a month, though when I start this contracting thing that might shift to maybe, once a month. But just trying to, write that newsletter and try different mediums, like podcasting and things like that to see kind of what works the best for me in terms of just putting content out there that hopefully some people want to pay for someday.

Matt Yao: What's the, what do you mean by trying to write a Substack?

Bryan Wagman: Well, I mean, I guess I've been doing it. I've been doing it for probably about two months now or so. I think I've written three or four posts, shooting for a once every two weeks cadence.

Matt Yao: Okay. So you have stuff published. You are doing.

Bryan Wagman: Yeah.

Matt Yao: Yeah. Okay, cool.

Bryan Wagman: Yeah, I've got, I guess the trying part is trying to make a living off of it, 'cause I'm not charging for it or anything.

Matt Yao: Yeah, that's tough.

Bryan Wagman: Yeah, right now, I've got 400 something free subscribers.

Matt Yao: That's a lot. How'd you get so many?

Bryan Wagman: Well, again, those are all free. But I started publishing on there back in 2020, and so most of them are from kind of the early days where, Twitter wasn't nerfing the Substack links and stuff like that, and I got a lot of followers on Twitter, it's 10,000 now. I forget what it was back then, but it used to be, I'd publish whatever, and I get 20 or 30 subs every time, and now it's I'll publish a super in-depth write-up, and I'm lucky if I get a couple. So I don't know how much I want to, let the, let the market dictate what I write about, so to speak, versus just writing about stuff I like. So that's all part of the journey to be figured out over time. But just want to focus on making sure that I'm actually producing the writing and publishing every so often. That's, that's my main focus and priority right now.

Matt Yao: Sweet.

Bryan Wagman: Yeah. Boy. How about you? Palo Alto, right?

Matt Yao: Yeah. I moved to Palo Alto three weeks ago. Feel the big change has been starting to look for new opportunities. I'm still coaching. I'm still very happy coaching. And I also want to have a little bit more stability financially. And I also just have a lot of interest outside of coaching. It's, I'm certainly going deeper with my coaching practice. I'm in a therapy training. Spend a lot of time with that, this weekend it's gonna be Friday, Saturday, Sunday, six to seven hours of Zoom all three days. So, it's not I'm trying to. It's interesting, usually, you see, "Oh, I stop one thing, I go to the next," and it's usually an all-or-nothing type approach. I haven't seen too many people do this type of thing that I'm doing, which is kind of going back full circle, or I don't know what I'll end up being but integrating this sort of past, and then the new thing, trying to make a life where it's more of a portfolio. There's different elements of work. So that's definitely the main thing right now, and then also, just getting settled in, finding a new, establishing a new routine, creating a sense of community. It is. Yeah. I think I took it for granted when I was moving around a lot. But once you actually are in a new place, there's a lot of things to get used to, and I'm in an area that I don't know too many people yet, but I'm starting to, meet new people, starting to get introduced by mutual friends and stuff. So, things are in motion.

Bryan Wagman: Yeah, yeah, that's good, man. You mentioned the portfolio thing, that was actually something I wanted to ask you about. Because I'm curious, because I know, even back when you were doing your sabbatical, you had, a blog, and doing climate writing, and a sublet service, and then the podcast. So how do you think about the tradeoffs between, because I'm trying to figure this out, too, between, different mediums that I can spend time on, and spending time on Substack and, and looking for things to generate income and things like that. So I'm curious what, what you think about kind of the tradeoff between focus and 'cause sometimes I think, "Oh, well, if I go all in on, XYZ, whatever it is, I'll probably get more results from that." But there's so many different things I want to do.

Matt Yao: Yeah, are we starting? Now, this is the podcast part.

Bryan Wagman: Yeah, sure. I don't know. I'll probably, I'll probably edit some of it, some of it out, back and forth. But honestly, just with the podcast, I don't know. I don't know what I'm doing. I haven't done this before.

Matt Yao: First episode, right?

Bryan Wagman: First episode. I've never recorded either as a guest or as a host on any other one. So, I don't know if I'm gonna make this into a written interview thing, or, or just publish the audio, or the video, or, or all the above, so. And I'm open to suggestions, and, kind of ideas and advice. I don't know if you have any advice for a, for a first-time podcaster.

Matt Yao: Advice? Just try to enjoy it as much as possible. That will, that is what will keep you going, and if you stop, it'll be, it'll be because you stopped enjoying it.

Bryan Wagman: Hmm.

Matt Yao: But anyways, let me answer your question, 'cause I think it's a good question. So I actually had this, I'm constantly thinking of new ideas, or just thoughts come to me. And this thought came to me today of, sometimes I think in terms of blog titles, phrases will come to me, and I'll be, "Oh, that could be a blog title," and it's something the phrase, it was, "simple life, complex work." And it captures what I'm trying, how I'm trying to live my life, which is. And also, life and work are not two separate things. Life is the big thing. Work is nested within it. But I just mean, outside of work, I want my life to feel really simple. I want to have, a few close relationships, my partner, few close friends. I want it to be simple and there's a sense of routine. There's a sense of ritual. I'm not always moving around anymore. I eat a lot of the same meals that, I like that taste good, are healthy, et cetera. And there's, also I'm spending a lot of time not on screens, outside of work. Moving my body a lot, doing a lot of things that people did a hundred years ago.

Bryan Wagman: Hmm.

Matt Yao: Playing sports, working out, hiking, being in nature, all that thing, all that stuff. And then I think, when it comes to work, I am probably firmly in the camp of being okay with multiple things. The, I think the phrase portfolio career is the most popular or legible phrase of what we're talking about here. I like it, but I also have a different expression. I just called it elemental work or an elemental career, where you can think of, I got this inspiration when I was watching Avatar. So it was, earth, fire, water, air. Each of the elements kind of has a different thing, and there's not one that's better than the other. But anyways, I think it's just natural. We're not meant to do one job. We're not meant to have one interest. Many of us have multiple interests. And so, if you sort of relax your, if you sort of relax the rigidness on the definition of work, then to me it's just, work could be a set of things that you're intellectually curious about. It could also be things that make you money. But those don't have to be, it's not an and statement. It's not it has to be something you're curious about and make money. It could be one or the other, or some subset. So, I think for this question, it's really important to understand, where's the question coming from? Is it coming from, how can a person structure their work and their career for maximum fulfillment, curiosity, flow, et cetera? Or is it from a question of how to make a living and maximize income? And I think the answer can vary a lot. If you're, if you're trying to maximize your income, it's actually not always the case that you should focus on one thing, because the one thing that you're focusing on right now might not actually be the thing that you could do. It could just be the new, the, the new thing that you haven't tried yet might be the thing that is actually more lucrative for you. But in a, we don't think that way. We think logically, straightforwardly. We try to collapse uncertainty, understand what the future is gonna hold. So that's why a lot of people end up climbing the corporate ladder and staying in one industry. But I think what I'm more familiar with is just what to do, how to approach life in a way where you're able to pursue your curiosity, follow your interests, feel you're being creative. And in that way, in that sense, I think you, you have to structure your work for the sort of natural, unfolding, it would look more like a slime mold, or a bacteria growing into its environment, in all these different nooks and crannies, and all these shapes, rather than a perfectly planned city grid.

Bryan Wagman: Yeah. Yeah, I think for me intellectually, I kind of like the idea of being able to throw a bunch of stuff at the wall and see what sticks, and maybe get more focused over time. But at the same time, I think I have a little bit of FOMO, especially because, I don't know if this is kind of a meme, so to speak, or a hustle culture type thing. But when you, when you hear a lot about, what I would say, entrepreneurs, athletes, musicians, people that attribute their success to a lot of times. They talk about the level of focus, and the dedication to the game or the company. But I mean, and maybe that's different for, people who want to do that, who want to be, the very best in the world at activity XYZ. Maybe that demands more hours and more percentage of your time focused on it. But, but there's still kind of that, that pull for me of feeling if I don't go all out on something, what's, what's the point? It's kind of scared to let go.

Matt Yao: Yeah, I think doing multiple things and focus can actually coexist very beautifully. It just isn't intuitive. What I mean by that is, as a thought exercise, if you cut out all of the ways you're wasting out time, wasting time, that you know it's, it's you that is saying that this is. This is how I'm wasting my time, not, not me or someone else saying this, this is a waste of time. You'd probably be left with, a lot of extra time to do stuff. And so for me, even though I'm someone who has had multiple interests and still has multiple interests, I still waste time. I still watch YouTube videos. I still, go on social media, or sometimes it's a little bit more subtle. I'm just reading certain Substacks that I don't get value from anymore. So if you subtract all the ways you're wasting time, and then you pay attention to your, your state, your energy state, how alert are you? And you're working when, when you are actually able to get things done, and not trying to grind at midnight where your brain's not working anymore. You can get huge improvement just in that. But I also think around these stories, right? These stories of obsession and focus. The ones that, the ones that make it to, so popular, stories are the rare ones where it was, "Oh, from Tiger Woods, right? From age two, he was golfing, and then it was relentlessly obsessed." But there's this other example, this is from this book Range by David Epstein. What's the, who's the, the really famous tennis player?

Bryan Wagman: Nadal.

Matt Yao: The other one. No, it might have been Nadal. He didn't start playing tennis until 10 or 12 years old, and but he was really gifted in a lot of other sports, and his parents were supportive of him trying other sports. So it was a question of, "Well, okay, I think there was a mistake of, these people were the success stories, they focus, so I have to focus," 'cause you don't know if you're gonna be, you might be a success story from focusing, choosing to focus on, on something later. So you might have five different things right now, and it's only because you allowed yourself to explore five things at once, and naturally prune the ones that you're less excited about, that maybe one, three years from now you're, "Oh, this is the thing, and I'm gonna go all out at it." And then that's the thing that ends up being what you're known for.

Bryan Wagman: Yeah. But for me, over the, over the course of these past few months, I think I can definitely relate to the reading a lot of Substacks, things sometimes I'll, I'll sit down, specifically to try to spend an hour or half hour, or whatever, catching up on all my email and stuff. And then there'll be these Substacks, and I'm, I kind of want to read that, but not really. And then I end up spending, 15 minutes reading it, or whatever, and, and that throws off the whole point of, I sat down to get through my email. And, and now I'm not doing it. And so I'm trying to do a better job of kind of just capturing and dispositioning stuff appropriately, but it can be tough to, to let that stuff go. And it's weird, because, in some ways I feel it's, it's similar emotionally for me to the feeling I get when I really want to check my phone or something. I want to, compulsively check my email or my social media to see if anyone's liked my tweets or anything. It's, "What if there's something good in this Substack that, that I don't wanna miss?" But at the same time, it's, even if I were to boil down my life to, try to say five really big projects or big ideas, big things that I'm working on, 90% of the stuff I spend time consuming does not relate to any of them. And so, I'm still sort of interested in, in small business acquisition. And I wanna kinda keep tabs on how things are developing in that space, whether it's, from a legal perspective or just different people to follow and connect with, but one that I've kind of ditched recently is, I was gonna try to do some e-commerce stuff, sell, maybe either yoga mats or, or pickleball paddles with Bible verses on them, or Christian art, or something. And so I kind of ran some ads on Pinterest to test some different designs. But then I kind of narrowed it down. And I was, "Oh, well, I need to really focus on, on this newsletter. So I'm just going to drop that." But it keeps kind of, it's still there in the back of my head, as something I want to try, and I feel maybe I was, cutting it unnecessarily, just again. Kind of this fear of, "Oh, well, if I don't focus on, if I divide my attention between these two things, neither one of them will work, will work out." But that's kind of, not, I don't know how to explain or articulate it, but I don't feel that's actually necessarily the truth in terms of, especially given how early on I, I am in both of them. But I found that, yeah, difficult.

Matt Yao: Yeah. My sense is that you're maybe looking for the feedback loop. The, the measurement on your feedback loop is, is something that is not perfectly calibrated to your own intrinsic. Your own intrinsic judgment of, "Oh, I just like doing this." Maybe you're looking for, people that are interested in buying it, right? So I think it's important to separate, what's for money and what's for just for the sake of it. And it's okay if those blend later on. But at this, at the start, at the starting point, at the trailhead, being really clear, "Oh, am I trying to do this e-commerce thing because I need to make money, or am I just really interested in e-commerce and Christian pickleball paddles?" And what was I gonna say? Oh, the other thing I was gonna say is, this, this topic of FOMO, and, "What if? What if..." I find for myself that it, I hear that chatter a lot less when I'm finding a lot of satisfaction in the other things I'm choosing to do. So, what I mean by is, it's all tradeoffs. Right? So, "Oh, I choose to, I, I chose to stop doing a podcast with a friend. I chose to stop writing my climate newsletter, chose to stop doing this subletting newsletter." And it's not always, "Oh, I feel great now that I did it," but it's always. What always helps is, what I'm choosing to focus my time on instead feels good. And when I am feeling of feeling torn, sort of pulled away from my present experience, there's, it's usually a sign, there's some emotion here that's causing the stuckness. And then another more tactical thing that happens is, it just means I need to focus on the actual things that I'm, that I'm choosing to do. So, for example, I found when I took a six-week break from writing my blog recently, from mid-May to early July, "Oh, I had all these thoughts of, I'm getting kind of spirally." And, and then I just sat down and wrote, and then, now I'm back in the flow.

Bryan Wagman: Hmm.

Matt Yao: And I'm from, I'm trying to write. Well, I'm, I have all these topics to write about. I'm really focusing on it. I'm making sure I feel good about it before I publish it. And I'm, I'm being very focused on that. I'm being very focused on the present.

Bryan Wagman: Yeah. Yeah, the, the money thing is, is interesting. I feel the e-commerce thing is probably more about money for me at this point, because I think that's potentially a faster path to being able to get to a sustainable livable level of income versus writing a newsletter. And I may come to enjoy it more over time. I don't think I've done it enough to know for sure, but one of the things that you've written about along these lines is just kind of your recent transition with coaching, and how you're kind of starting to look for other forms of income right now. And you wrote something to the extent where it was, I think, I think you said something you kind of flip back and forth between not, on the one hand, wanting to just have blind hope that something's gonna show up, and, and on the other it's, grind, grind, grind, and really lock in and focus. And I'm, I'm curious, what would your life look like if you chose the latter? And if, and if you were, "I'm gonna go all in on this coaching stuff," what, what would you do? Differently, specifically, both with respect to your, your business and your life.

Matt Yao: Yeah, I mean, it's hard to say what would have happened. But I think, I'll probably tactically, what I would have done is just spent a lot more time on marketing, the coaching, reaching out. And, what's interesting is, I made this choice to start exploring new opportunities, and I don't know what it is gonna be that I land on yet. And as I do this, I actually am, in many ways doing all the things I'm about to say, right? I'm writing, writing a blog. One of the blog posts I'm gonna write about is very coaching related that might lead to more people hearing about my practice. I'm telling more people about my coaching practice. I, I just had a call today with someone who's starting her own coaching practice. So it's funny that, I took the, I intentionally didn't choose the grind-all-in path. And yet I'm still doing all the things that I would have done if I went all in. And I think maybe what I'm trying to say is, all in depends on, is it all in time? Yeah, I'm not doing all in time, but I am all in energetically on my coaching. I'm even if I get a full-time job, I'm still gonna coach. I had an interview last week for a founding PM role, and the founder was, "You can't. You can't have side, also, you can't coach if you." And then I was, on the spot, "I don't think this is a good fit, then." And so it's about being really clear about, what is we have? What is that? What am I moving towards? And it's a world where I'm still coaching. And what I tell myself is, actually taking off the financial pressure completely from coaching might actually, over the long run, end up helping me and being a more effective coach, because then I'm just, I'm just being there for the client, and I don't actually, if they need, if, if what's right for them is they've reached a milestone. And coaching isn't actually the thing for them anymore. It's I can break that off cleanly. And so I think that's really important to distinguish. It's, I still feel very much all in on coaching. I mean. Practically, I do have limits on time. But it's, a really good forcing function. I think what I'm experiencing right now is probably what parents of young kids go through. I, I hear all, I sort of see these tweets from time to time. People are, "Becoming a parent, I thought I was gonna lose my productivity." And instead, and they became more productive because I just cut out all the bullshit. And I think that's, I'm probably going through that just in a probably less intense way, because I think I don't think I'm not trying to say my life right now is as intense as being a parent of a one-year-old. The other big thing, not just in terms of, would it actually work, is sort of this, the theme of integrity. Do I want to be putting myself in a position where I have to go out and get all these, more clients, right? Am I trying to coach people that I'm not the best fit for, or people that? Am I kind of coercing them into coaching? Maybe there's, not in this season of life, where coaching is the thing for them. Maybe they're good for, they're better suited for therapy, or instead of conversations, right? Which is what coaching and therapy is. Maybe what they need is, to go spend a ton of time out in nature and move their body, right? Different people are, have different, different things going on. So, I think. There was a time, maybe a month ago, where I was going super hard on the job search. And I stopped writing, and I was also traveling and moving. So it's a lot of things in life. And what I took away from that was, I'm gonna do this search and explore things. And it's gonna just take its own time. I've got plenty of time. I'm not gonna run out of money anytime soon, and I'm also still gonna do all the things that I would have done if I went all in on coaching. And also, if, assuming I already had this job, I would still be writing my blog. I would still be coaching. That's how I'm invited.

Bryan Wagman: Yeah, I really like what, what you said about the interview and, and how, you realize where your priorities were and are, and are committed to maintaining the coaching thing. And if, if a certain, role doesn't, doesn't allow for that, or doesn't fit with that, then it, then it's not a fit for you. I think that's, pretty cool, and, and I've struggled with that a little bit, too, just in some of the conversations I've been having. Especially with how tough it is in, in the financial industry, because, there's all sorts of rules around compliance and marketing and things like that. But I've been, so far, I think at least pretty good about trying to be, straightforward about, "I really want to write this Substack. This is really what I want to do over time. I want to be able to continue to grow that while I do whatever else I do." And so, it's, it's tough, though, because, there's definitely been a tension for me in those conversations. There's, there's part of me that's, thinking to myself, "What are you talking about? You're at 450 free subscribers right now. And this opportunity you're looking at could actually, potentially pay the bills." But, but that's not what it's about. And I'm sure you understand that.

Matt Yao: Yeah. And there are also cases where you can. You don't have to choose between either one.

Bryan Wagman: Yeah, I'm, I'm looking for more of those. Some people have, have been, more open to it than others. But I guess it's just. It's part of that whole broader thing. I'm kind of grappling with the, with the uncertainty of, having left the job and kind of pursuing the pathless path, if you will. It just contributes to it, passing up certain job opportunities that I'd take otherwise, because it still kind of requires that same trust in taking the next step forward, regardless and trusting that it'll, it'll still work out. And it'll still, be fine, basically. But...

Matt Yao: Yeah, and also trusting that there might be a time in the future where you change your mind.

Bryan Wagman: Yeah.

Matt Yao: It doesn't have to be kind of what I said at the blind hope thing, right? You could be not ready for a full-time job, or whatever it is, right now.

Bryan Wagman: Hmm.

Matt Yao: And, if you maintain a level of self-awareness, fast forward a few months, or a year, or whatever it might be, a very different situation. I think I sort of in the beginning had to grapple with, "Oh, am I being a hypocrite by writing about quitting my job? Now, I'm trying to potentially. Go back." And I think, I asked my close friend. I was, "Dude. Do you feel I'm being a hypocrite?" He was, "Yeah, kind of." And then when I heard him say that, I was, "Oh, actually, I'm not a hypocrite." It's funny. It was he was telling me, "Oh, I think you're kind of a hypocrite." And then I was certainly asking him to sort of see what other people think. But when I heard him actually confirm, I guess what my fear would be, I actually was, "I don't feel I'm a hypocrite," because all I did was change my mind. If you, if you ask some 16-year-old dude, he's gonna be, "Oh, what do you want?" He's gonna be, "Oh, I want to have ten girlfriends," or whatever. And then you ask, a 30-year-old dude. He's gonna be, "Oh, I want a wife and kids, and I don't want to party," right? So people change their minds. It's just kind of, people don't change their minds that often, I think. And they don't. They also don't do it very publicly. So, it's a bit of a tangent.

Bryan Wagman: I've, no, I've, I've dealt with that same exact thing because I've been kind of documenting this journey on Twitter and Substack. And back in, March or April, I was, "I really want to be an entrepreneur. I just want to start my own business, whatever." And that's still the case. But, I just, first of all, just for financial reasons. I don't know if I'll be able to make that happen in the near term. And so, I've been kind of having to, I guess, come to grips with the fact and, and accept the fact that it's okay, to go do something else for a couple of years if I have to, and, or if I want to, even though, that may have not been what I was expressing publicly a couple of months ago. But I view it similarly to, I think great investors, Stan Druckenmiller or something, is famous for, he'll go on CNBC and talk up, whatever company XYZ that he's buying, and then, turn around and sell it a few days later, because, it's a strong opinions, weekly held, and when, when how I'm thinking about something changes. My actions should change accordingly. So I've been, I've been kinda, kind of wrestling with that, and just the, the public perception of it can be tough, I guess.

Matt Yao: Yeah, yeah, I'm just thinking if there's anything else I have to add. It's not just about changing your mind. It's also it's, it's not just about changing your mind. It's also just, there are certain things that I think we're living in a world that's gonna become increasingly more complex and chaotic. And there's gonna be more change across all levels. Economy, culturally, at a level of work, geopolitically, everything. And so we're gonna start seeing more examples that break the mental mold of, "Oh, it has to be black or white." And now we're just gonna be seeing a shit ton of gray things that sort of just don't fit what we expect to see out there. Whether it's doing a job just because you love it, even though it doesn't pay well. And then, trying to figure out a way to scrap together the rest of the money you need, or if it's quitting your job. Or there's all these examples, even just the fact that, people make millions of dollars creating content. That's already an example that I think has become more accepted by society is, "Oh, this is just the way it works." But five years ago or yeah, five years ago, that wasn't, that was kind of mind-boggling.

Bryan Wagman: Yeah, yeah, for sure. One of the things. So there was an interview I read that you did, I think you were six months into your sabbatical, and you talked about the process of decoupling uncertainty from negativity, and just getting more, more comfortable with, dealing with, I guess, those feelings that come up when you're going on kind of that pathless path type, type life. Where, where do you feel you've? How do you feel you've progressed over the course of the past couple of years with that decoupling? Where do you feel you stand today?

Matt Yao: Certainly it's not a straight line.

Bryan Wagman: True.

Matt Yao: It's ups and downs, constantly have to remind myself. It's a lot of reminders. And remembering that, that it's yeah, what, what you said, uncertainty and negative things are not the same thing. A lot of times we think they are the same thing. I had. I was just talking about this recently with someone of, "Oh, I should keep a list of every time something happens that I didn't expect." And it could be, maybe one of two ways. First being, I did something that was different than how I thought future would go. And then, here's an example. I just moved to Palo Alto three weeks ago. I spent six years living nomadically, not in Palo Alto. I never lived here. Asking myself, "Where do I want to live someday?" I lived in Hawaii. I lived out in Tahoe. I lived in Salt Lake City. I lived in New York City. All these great places. Some of them are great for, surfing, some are great for skiing. Some of them are just great cities. Full-time, I'm trying to figure out where to live. And then in the end, my girlfriend is in the medical field. And so where we ended up living is not even in our. It's not my control. It's not even in her control. And that's an example of, I would probably add that to the list. But there's also situations that happen where something else happens in your, somewhat, some other people or your environment. There's some event that triggers something in your life changes. And obviously, it's, it's unexpected. And, and so it's in this realm of uncertainty. And if you make a list of all these things that happen that are surprises to you, and you could roughly market as positive or negative. You might find that there's plenty of things you couldn't have anticipated that are actually not that shitty. And the other thing is, the whole point is that this is what makes life, meaningful, enjoyable, right? The reason why we watch movies or we play video games is because we don't know what's gonna happen. Video games are fun because you press some buttons. The thing on, the, the person on the screen changes, there's other people, other characters in the game. And then you have to respond. If it was not that, and you knew what was gonna happen, then you'd just be watching something happen. It wouldn't be entertaining. So, the element of uncertainty is not something that should be trying, you should not try to force that into zero. It's more about finding the level of uncertainty that you can tolerate, and then working with yourself to be able to tolerate it more and more until you find sort of an equilibrium. And that level can change over time. I used to be really comfortable with moving every month. And then now, in, at least in this theme of where I live, I want basically no uncertainty. When it comes to food, I want no uncertainty, meaning, my fridge is full. And I eat the same thing every day. I eat the same oatmeal for lunch every day. But when it comes to, the people I'm spending time with, or what I'm doing for work, what I'm learning about, it's, I'm totally okay with that being very open-ended.

Bryan Wagman: Yeah. I forget where I heard this phrase, there's, there's someone it could probably be attributed to. But I, I what comes to mind is the phrase increasing the surface area of serendipity. And that's, that's, that's one of the things that kind of fuels my interest in writing both the Substack, but also just, I've been trying to be more active on LinkedIn and more active on Twitter as well. And so because I think just I don't know what's gonna come out of those things. Ultimately, every job that I've had so far, and internship, has come either directly or indirectly out of writing online. Because I wrote for, Seeking Alpha back when I was in high school and college. And so I just think it opens up opportunities for things that I couldn't even predict. And so, yeah, the main thing that I think about when I think about writing the Substack is, hopefully, I can make a living off of this someday, but I think there's also a lot of room for positive surprise in terms of what else could come out of that between now and then? What could I learn? Who could I meet? What relationships could come out of that? Could other work opportunities come out of it? So in, in having to, trade that the way I have in, in the past, jobs that I've had is just something that I've decided is, is not worth the tradeoff anymore.

Matt Yao: Yeah. Have you talked to any of your subscribers? Have any of them reached out?

Bryan Wagman: I've, I've had some conversations, because a lot of the subscribers are just, people I know. And so obviously, I've, I've talked to them varying degrees. Maybe we already had kinda, a relationship of talking stocks now and then, and then they sign up for the, for the newsletter. And so there's been stuff, some stuff that. And I would say, not, not that much, though, and I haven't reached out to that, many of them either. It was interesting. A couple of weeks ago I published a write-up on just some small, smaller micro-cap software company. And someone who runs a fund that owns, is a large shareholder of, of one of the companies that I, follow closely, and have been invested in the past, signed up for the newsletter, and so, I don't know. I haven't reached out to him yet, but I might end up doing that at some point. So it's just that. That's the other thing, too, that kinda even though the progress on the actual subscriber count and, how am I gonna make this paid has been, has been slow. When I see someone that sign up, it's, it's fuel and motivation. It's, "All right, I'm, I'm on the right track here." If I just...

Matt Yao: Yeah.

Bryan Wagman: Be consistent and keep putting content out over time. I think something good is gonna happen.

Matt Yao: Yeah. The reason why I asked is, it sounds you're writing mostly about stocks. Even just one example of, you could spread your, you could increase your surface area by publishing more often, writing better, right? So it's spread more. You could also increase your surface area by writing about other topics, not, not in a forced way. Things that you're interested in, or, and or, incorporating more of yourself into it. I think that's, I've done. I've, I'm really bad at a lot of things when it comes to the Substack and growing it. I have less than a thousand subscribers writing for a few years. There's people that grow much faster, but I think what I have done well is, I'm very real. I'm very, it's very much me.

Bryan Wagman: Hmm.

Matt Yao: And sometimes it's my judgment, right? But when someone reaches out, they just, they, they're sort of self-selecting. They are just, the fact that they reach out to me, I already am, "Okay, we're probably gonna have a good conversation," because if this person has read enough about me, and they don't resonate with it. They're just not gonna reach out. And yeah, I, I do think there's something about putting out feelers for other people. Paul Miller, right? He, you mentioned. He also has this phrase, "find the others," and I think it's finding the others. But it's also allowing the others to find you. And I think, it's, it's, it's both. It's not what it's not just about it being this, relentless search, looking for random people on the internet that you look up to, because that can feel a little bit one-sided, and it can feel a little bit you're being desperate at times, or I'm just talking about the, the fears that people have or, "Oh, it's, it's pointless." Or, "When is this gonna lead to something?" But if you just, put yourself in a position where you can be discovered, then it feels a little bit more symbiotic, or it feels a little bit less of a power dynamic and more, "We're all just peers. We'll just, peers floating in this space called the internet."

Bryan Wagman: Yeah. Yeah. And, and I've experienced some, some fear about sort of that idea of, posting more, posting about different stuff, because when you talk to, I talked to several people who have started investment newsletters over the course of the past couple of months, and a lot of them will say, "Oh, you gotta be consistent with when you publish, and if you publish stuff that people aren't interested in. They might unsubscribe." And it's, it's definitely been a consideration that's kind of in the back of my head even when I think about, is, I mentioned earlier, I, I don't know if this is gonna be a podcast or, or a video, or written form, or, or whatever. But if I do, do a text form, I'm trying to think, "Okay, well, I'm doing an idea write-up, about stocks every two weeks, and maybe someone signed up for the newsletter because of that. But what are they gonna think if I, release an interview that has nothing to do with stocks on a Wednesday," or something that. And it's just I feel my intuition is that it's not something I should be worrying about. But it's, it's been. It's been slow to put that into practice. Kind of similar experience for me with posting more on LinkedIn. I posted something today about a conversation between Steve Nash and LeBron James. And I was, this feels...

Matt Yao: One of the game.

Bryan Wagman: Yeah, yeah, exactly.

Matt Yao: Yeah, so if you didn't bring that up just now. But maybe something in your head was, "Oh, should I bring this up? Oh, I don't know if Matt likes basketball."

Bryan Wagman: Yeah, yeah, and you...

Matt Yao: We wouldn't. We wouldn't know that. I sometimes watch that podcast, too. And, and so that's just an example. So there is that, yeah, this is again, theme of uncertainty. And there's also tactical ways. So, I've seen podcasts where they have the video, or they have the audio and the text. People have different preferences. Even for me, sometimes I read these text-based interviews. If I just happen to be at my desk in the morning, and it's something. It's a different type of content. There's different types of knowledge that I want to read. And then there's things that it's I want to listen to, because I can go for a walk, and it's more enjoyable, or I'm driving. But I also think, the other thing that's important to mention is, we live in this, you know this phrase, the attention economy, right? Attention is the, it used to be data is the new oil. Now people are, "Oh, it's attention is the most scarce thing." And so I think it's really important to honor the reader's attention, but also not forget, they are subscribed for a reason. They want to hear from you. And so the way I think about this for me is, well, also, you have to consider, it's only gonna be good if you care about it. So, if you're writing about a stock that you don't give a shit about. It's not going to be good. But if you're writing about something that you're obsessed with, and you really enjoy learning about, it's gonna, it's gonna be apparent. So the way I think about it for me is I try to select a topic to write about that I'm interested in. Usually it's about my life. So it's not as hard. And then I try to get to a point where, before I start editing, I feel complete. I feel I've discovered new things. I've learned more about myself. I feel I've covered, most of the territory of the train. And then when I edit, I try to be really aggressive in trimming out the fat. Just the way I write is, I just ramble. There's lots of filler words. And so I use Chat GPT to help me edit and just point out all the areas that I can make more concise. Then that way. I'm honoring the reader's attention by, not subjecting them to read all this extra fluff, but I'm still being very, I'm taking it very seriously on what I choose to write about, and making sure it comes from an authentic place that I'm curious about.

Bryan Wagman: Yeah, no, totally. Yeah. I, I agree with that. That's something I, I try to be 'cause there, there are some times where again. It's that the tradeoff can sometimes be right about something that's popular, right about something that I'm interested in. And that was I, I definitely thought about that over, over the course of figuring out what I want my newsletter to be, and I'm still not sure what, what direction I'm gonna go with that. But another piece of advice I received from some people is to, find a niche and write about that. And so, but at the same time I'm, I don't know. I, I really, respect the work that the guys at Semi Analysis do about semiconductors. But I don't know if I'd want to be looking at only semiconductor companies and never anything else.

Matt Yao: I think, having, having a, having a niche is really good for, it makes a lot of sense for business, and actually something that I'm sitting with right now is I, I'm pretty sure I have my niche identified in coaching, but I haven't taken the action yet. But I think having a niche is actually really bad for finding other people, and being in sort of the, in this, in this, in the flow of the internet, and connecting with ideas. I think this podcaster Dwarkesh called it, the marketplace of ideas. So you could think of it, you're putting something out, and it's getting matched to other people that are interested in it. And if you, if you sort of prematurely restrict yourself, then you are prematurely shutting yourself off to serendipity.

Bryan Wagman: Yeah, what's the niche that you're thinking about for coaching?

Matt Yao: I think it's gonna be something around people who are considering quitting their jobs.

Bryan Wagman: Interesting. Which is.

Matt Yao: It's, it's, it's, I spent a year kind of running around purposely, not having niche, but, at, it was a point where I was, "Oh, what's my niche?" "Let me go look super far out there to find it. Let me go research other coaches. Let me go think about whether it makes sense on paper. Let me do some analysis." And then, it just came to me when I was talking to someone else who's about to start coaching. Yeah, I'm happy to get into it, but it just makes a lot of sense.

Bryan Wagman: Yeah, no, I, I think that's a really good and interesting idea, because, one of, one of the things that, one of the ideas. I had kind of bounced around in terms of trying a podcast was for people who had, quit their jobs with nothing lined up, or were going through some other kind of transition period. Because I think, I really think, and you put it so well that, decoupling of the negativity and the uncertainty. That is something that I think probably, in, in different words. Paul writes about it, too, in The Pathless Path, but I think anyone who's, quit their job, and, and not been sure of what's next, has experienced that, and I feel I had. I did not, I would not have been able to articulate or quite understand it as well when I was still at my job. But talking to other people about that is super interesting to me, or hearing what other people have to say who have actually experienced that feeling, too, would, would be super interesting to me. So I think that's, that's a cool area. Yeah.

Matt Yao: Yeah.

Bryan Wagman: I wanted to ask about the subletting stuff, actually, because there's a part of me that just wants to. I feel the first step might be. Getting getting rid of all my stuff, so that I have less reason to stay put, because I've, I've never, moved around. I mean, I guess I've, I've moved some since I graduate, since I graduated in 2018. I've lived in a few different places, but I've never done an extended period of a month-to-month. Type thing. Which I feel could be really interesting. So I guess if, if you could start just tactically. I'm very curious to hear how you go about finding these awesome, whether it's sublet opportunities or Airbnbs, or whatever it may be.

Matt Yao: Yeah, let's start with this. Where are you now? And where? Where? Where are the places that you, you would consider trying out?

Bryan Wagman: Yeah. So I'm in Chandler, Arizona right now. Right outside Phoenix, and the main two places that I'm thinking of. Well, I guess kind of depending on how you break it down. There might be a couple. One is just somewhere else in Phoenix, so staying in the same metro area, but just trying different neighborhoods and things that. And then the other two, kind of one is basically Austin. But there's also I got a friend who I grew up with that lives in Point Venture, which is a small town about an hour outside Austin, right on Lake Travis. So those are kind of the different areas of interest to me right now.

Matt Yao: Yeah, the first one's interesting. It reminds me of this. I think it was a Substack that this, this girl Ava wrote about. It's this idea that the neighborhood that you live in plays a bigger role in your experience in the city that you live in.

Bryan Wagman: Hmm.

Matt Yao: And I think that's very spot on. You just end up settling into a routine. You're more likely to walk than you are to drive, or you're more. You're more excited to do that, I should say. And so... Even if you just move 45 minutes diagonally to the other side of the city, it could actually change things up a lot. I coach. I coach a client right now who recently moved to a different part of his city. And it's slightly more expensive, nicer place. It led him to changing gyms. He's at a, he's at a gym that he's much happier at. He's met more people, more like-minded people, and then also signed up for a coworking space. And then that, that went, or you, he's a solopreneur. So, sort of before. That was more isolating, you know. Default work from home. Try to co-work with people, but it's sort of ad hoc, sort of stitch together. And then now he goes to his new coworking space, and then he's even trying to form his own office with other solopreneurs, sort of find, outside of WeWork or whatever it is. And then this idea of you just working with your friends. And that was all. Just because he moved neighborhoods in the same city. But yeah, in terms of subletting, I think it's this super interesting thing, 'cause it's, it's just so, it's so not deep on the surface. It's just, "Oh, you don't have a lease, and you just move around all the time." And there's a lot of, I feel there's a lot of depth and, and philosophy in this, in this sort of even just in, in thinking about wanting to do it. And then, obviously, there's the once you're actually doing it. But in terms of tactically, the first step is yeah, your stuff. And I think, even as you get rid of stuff that will probably be a fun, a fun learning experience, of learning how little you need, and you might...

Bryan Wagman: Was there a point where you got rid of a bunch of stuff?

Matt Yao: Yeah. So I was living in SF for a year after college. And I guess it was a good thing that all of, a lot of my stuff was just from college. I went to Berkeley, moved to SF, so just rented a U-Haul. And a lot. Even the furniture I had in college was used IKEA furniture. So it's the cheapest brand, and it was used. And then I'm bringing it as, as a person that makes good money now, as a new grad. And so when I moved out, I just, one of my roommates was staying in the city, and, and actually just moving up one floor in the building. So certain things I just let him have. Wasn't worth trying to sell my roommate stuff. And then for the bigger pieces I, I remember I think I listed my bed for 150 bucks. No one was buying. I just made it free in the last week, and then some Berkeley student came and picked it up, and I felt good about, "Oh, I helped, someone from my Alma mater." So I got rid of all this stuff. And then, fortunately, my mom lives in this area, and I can just basically store all my stuff. So I have. All my camping, backpacking gear, I've got all my ski gear, and then, obviously, different clothes for different seasons. And then, yeah, then you just, you just go off and, and do it. And then, in terms of finding the sublets. It is a skill. And in the beginning you just, you just sort of, learning, right? You just don't really know where to look. So when I found the first sublet in Hawaii. I just went on these Hawaii, Sublet, Facebook groups. There was some real estate agent. He had a basically a, a hotel room that was not serviced by the hotel. So it was privately owned. And so it's, worst of all those situations, right? No kitchen, maids don't come and clean up after it, after me. And so I just eating weird food. I was eating oatmeal every day, and then I was making chicken salad, Costco chicken, shredding it up, and then eating with spring mix. Very simple stuff.

Bryan Wagman: Yeah.

Matt Yao: But then I was in Hawaii, for the first time, and I was doing all these things didn't even matter that I didn't have this stuff, and I paid this real estate agent, probably 500 dollars extra as a premium, just because you know that they have to make money, and then over time I got better at it, and then I was able to make friends, and then I could just ask them instead, and then pay their friends' rent, which is much cheaper.

Bryan Wagman: And yeah, I've been thinking about it a lot lately, and one thing that I kinda recall is, when I moved here to Phoenix. I moved here from Reno, and I drove down here and beat the moving truck here. So for the first week or so, basically, all I had was, I mean, I was sleeping on an air mattress on the floor, and I had, a couple of suitcases of clothes. And I really like the simplicity of that. And basically it was, I needed stuff to cook with, which I could have just gone out and bought, but, honestly, it's, it's, it's crazy to think about it. But I could have just been, "I don't even want the rest of the stuff in the truck." Just leave it. I could have definitely, lived with what I had if I just went out and bought some, pots and pans and stuff.

Matt Yao: Yeah, have you watched the movie Fight Club?

Bryan Wagman: Not in a very long time.

Matt Yao: Okay, but you've seen it.

Bryan Wagman: Yeah, but I don't. I don't hardly remember it.

Matt Yao: Okay. I watched it for the first time, a week ago. And it's, there's a lot of themes in the movie, multiple themes. But there's this theme around anti-consumerism, anti-materialism. And it sort of portrays this in a very violent and intense way. But I think there's a lot of truth to it. It's, think about how much time we think, spend thinking about, "Oh, my life would be marginally better if I updated my desk." Right now, I'm using a white foldable table that I've had in my family. It's, I don't know, ten years or something. I, I mean, I'm, I'm probably gonna get a standing desk, to be honest, eventually. But there's nothing, there's, there's not actually, it's not that bad. And think about how much time we think about, think about how many people get money for working their jobs and then go and spend on something that's not that important. And what I've been doing here. We've moved three weeks ago. It's, there's something actually, really interesting about, I get a new piece of furniture or something, and then I, and then there's a few days where it's a new apartment. There's something that was added. And then, maybe a few days later I, I changed the orientation. We moved where our couch was to the opposite wall. And then I sort of let it linger, and I really sit around. And then I'm, "Okay, actually, I do think this would be worth it." "I have 50 books on the floor. I should get a bookshelf." Or, "Oh, we should get a rug." And it's actually letting myself linger in this mild, very, very mild discomfort, and then choosing to buy the thing that makes me feel good about the purchase that I'm making, and it still feels a pretty simple place.

Bryan Wagman: Yeah, yeah, I like that. I think that's the way to do it. I, I'll probably start by. I don't know. I don't even watch TV anymore. I might try to get or not try, get rid of my TV, my TV stand. The bed is...

Matt Yao: We just picked up a TV. It's so funny. We park our car two car spots away from the, the trash for this apartment complex. And someone just left the TV. And I kind of came home at night. And I, put my phone flashlight all around this TV. I was, "Where's the crack?" There's gotta be something busted, really, nothing wrong with it. And it's also, not in the trash. It's on the floor. It's on the, the asphalt. And we just, have a TV. There's no cord. So we have to buy the power cord. And then, probably HDMI cord. I'm, "Yeah, I guess we just have a free TV now."

Bryan Wagman: Yeah, I'm thinking about doing the same thing, just dropping it out there.

Matt Yao: Yeah, I mean, there, the, it's not even another man's trash. It's not really trash to you. And it's just, but someone else will get a value from it.

Bryan Wagman: Yeah, yeah, you, you write and talk a lot about tech addiction. Is that something that you've worked on a lot in your coaching?

Matt Yao: Yes, it comes up often, but it's not a focus, and I think it makes sense given. If you just think about, let me try and break down what coaching actually entails. Maybe that will help. I think most of it is the central pillar is one's relationship with themselves. This is things around self-confidence, self-awareness. Feeling stuck, feeling confused, feeling frustrated, right? A lot of stuff around, yeah. Just, what do you want in life? Who are you becoming? These sorts of big questions. Another huge part of it is relationships. And it's sort of complementary, right? You can't just be in an echo chamber with yourself. Life is. We're meant to live with other people. And so so much of the work that I do with people is how to have healthy relationships and moving towards healthy relationships actually often involves conflict and not let anything stifle and have it breed resentment. So there's a lot of, "Oh, how can you give feedback to this person? Or how can you, express what you want to this person, or create a boundary," or stuff that. So that's why I think, the topic of relationship with technology is a smaller segment, but it actually, surprisingly comes up with pretty much every client at some point. And the way I structure the sessions is, I'm not saying to this week, "We're gonna do this," or there's no syllabus, right? So it's all about this set today, the client reflected. Sent me notes that say later today, when we meet, they want to talk about this, because for the past two weeks this has been the most important thing in their life.

Bryan Wagman: Hmm.

Matt Yao: And but then sometimes we just end up in a session. And then the common, entry point into this theme of technology is overwhelm, overworking, lack of feeling energized when they wake up in the morning, feeling overstimulated, feeling anxious about things outside of their control. Israel and Palestine, right? The, from watching the news, stuff that. And it makes sense, right? Because we all use smartphones. We all pretty much are knowledge workers for the most part with who I work with. And all of these devices have been designed to maximize engagement. So all these, a lot of these companies, if you think about news, social media, the more time we spend on them, the more money they make from us. And they spend billions of dollars on talent to design these devices to be as addictive as possible, so to counter, to move in a counterbalancing motion. It's gonna require some intentionality. It's not just, if you just let it drift without intention. You're gonna end up doomscrolling, which is what a lot of people are doing.

Bryan Wagman: Yeah. Yeah.

Bryan Wagman: I guess we'll probably start wrapping things up. I wanted to give you an opportunity to just kind of talk, about, where can people find you? And if you want to talk about, your coaching at all, or what sorts of opportunities you're looking for in terms of work.

Matt Yao: Hmm, yeah, I appreciate it. For coaching, my website is mattyao.co, so MATT YAO dot CO. My blog is morehumanpossible.com. And in terms of what I'm looking for, I've been spending most of my time looking for product roles. Product management was my past life. But now I'm actually giving a pretty open, pretty open-ended. I would like to work with either a team or actually an individual who we just have the same values. So I don't know if someone's listening to this, they probably have a decent sense of who I am by the end. I've just been talking about myself, and we didn't have a fixed topic. So I'm just talking about what my beliefs are. So, they could reach out, my website has, a way to get hold of me. Blog can also definitely find a way to get a hold of me. And also, who knows who's gonna listen to this. But if you're, if you're listening to this and you want to chat, just reach out to me.

Bryan Wagman: Awesome. Well, thanks, Matt. I appreciate it. Thanks for your time, man.

Matt Yao: Yeah. Thanks.