AVOID FRAMEWORKS

“I think these are interesting examples because for all these AI agents, you could build a version of Greenlight or Casca or Casetext, like a demo version, in like a weekend hackathon. And I think when college students are thinking about these AI agents, I think what they have in their mind is like the weekend hackathon version of the product. And they're like, I could build that in a week. Like, how could that be defensible? And like the reason is like the version you build in a hackathon isn't useful to anyone. It's like if Casca or Greenlight fail, like the banks will lose millions of dollars. This is like mission critical infrastructure.”

“Patience and caution. Don't jump on the market just because it's going higher. Be patient. Maybe take a small position in something. Start. If your full position is 5%, maybe put 1%. Start there. See if you're right. If it's going higher, okay, at least you have something and you can keep adding to it. But if it goes lower, well, you don't have that much exposure, you're not going to get hurt that much. But that's how you should be thinking about the markets is slow and steady.”

“This space is moved so quickly that in every vertical, many verticals, there's early on emerged one company that's seen as the early winner in the space. Often it's actually like the second movers, at least in the YC context, we have seen over and over again that there's advantage to being the second we were in a space. Stripe came after Braintree and Authorize.Nen, a bunch of things and was able to like actually win by just building a better product. DoorDash came after Grubhub, Postmates, various other delivery services and eventually went on to win.”

“I mean, something sort of emerging that's very interesting in a bunch of YC startups like Avoka, for instance, they're doing customer support software, kind of like Service Titan, but for HVAC. And I think Service Titan has something like 1% wallet share, 1% of the gross transaction value of a given HVAC company, which is very small, right? But the wild thing that Avoka discovered is that they can come in as software, but then over time, they're actually getting a bigger and bigger chunk of the wallet share because they can get the HVAC people to pay them actually for the customer support piece, which is not 1% of their spend, but 4% to 10% of their spend.”

“Let's talk about credit college loans. If you've got a $72,000 cost of attendance, but this is a real world example of a family that we worked at with, a $42,000 executive scholarship plus an $8,000 music scholarship. And by the way, the fluent families aren't filing FAFSA. They got a $2,000 scholarship just for filing FAFSA, so it pays to file FAFSA. And they got another $2,000 referral credit. Oh, by the way, their parents could refer the child. So the referral credit certainly didn't take some outside party. They could refer themselves. That was $54,000 right off the top of that $72,000 cost of attendance.”

“If you're investing in tech, especially the Mag-7, here's something you should keep in mind. Now, this is we call CapEx. So this is the amount of money they're spending. So historically, Big Tech has not had a lot of capital expenditures, because they don't need it. It's a very scalable model. They generate a lot of cash and they don't have a lot of expenses. Up until right around when AI started to pick up, and now you see that the CapEx starts to pick up. If I own a company and they make $100 and my earnings as an investor is $30, but then they take $29 of those dollars and go spend it on a data center that earns them no money, I'm not going to be happy.”

“When you think of investing, you have to think of the world in terms of frameworks. We as human beings are not good at all at predicting the future. We all do it. Our brains operate like a prediction engine. We all try to predict the future, and we're terrible at it. All of us are terrible at it, because if you're good at it, you'd be a bazillionaire, but we can't predict the future. But our brains naturally go there. So rather than trying to predict the future, a better way to handle it is to look at the world in terms of frameworks.”

“And I think Varun from Windsurf, who we hosted some time ago, he said it himself, the early stages at the beginning, the only moat that startups have is really just speed. Once you pass that and build something people want, then you figure out and go deeper into these types of moats that we're going to discuss.”

“One way where this is playing out in the counter-positioning is that almost all of these house incumbents, their pricing model is they charge per seat, i.e. per employee. And this is, I think, a very big Achilles heel that they have strategically, which is that if their AI agents do a good job and actually work, those companies will need fewer employees doing this work because the work will be automated by AI agents. And in a simplistic way, that will just actually reduce, the more successful they are, the more they will reduce their revenue.”

“The markets over many, many decades, they tend to have certain correlations. If you look back 20 years, there's a inverse relationship between stocks and bonds of negative 0.5, which is pretty good, stocks and bonds, which means when stocks go up, bonds go down, stocks go down, bonds go up, it's an inverse relationship. And that's how most people have their portfolios. Problem is starting in 2022, when interest rates went up, stocks went down, prices of everything went down. And since then, now we're at a positive 0.5, which means when stocks go up, bond prices go up, when stocks go down, bond prices go down. That's a weird thing to consider. So what's the point of diversification? It doesn't work.”

“So if you think of the investing world is like the Titanic, all the investors are on the Titanic. It's going in one direction. Now, if you're changing from scenario one to scenario two, well, that Titanic's got to make a really a beeline, like a sharp turn all the way around. That doesn't happen. It takes a while. It's not like a quick nimble ship. It has to go slowly over time. So pretty much that last month, slowly the markets turned and started to go negative. Then once Trump's like, hey, the war's over, even though it's not over, all of a sudden you had to do the big turn again all the way around. Well, the problem is everybody's chasing the market higher because they don't want to lose out on that return.”

“Like the thing that still stuns me is OpenAI, ChatGBT has more consumers using it per day than Google's Gemini. I think anyone who understands the models and uses them daily would say that Gemini Pro 2.5 and Gemini Flash 2.5 are like equivalent models. Google was already one of the biggest consumer brands on the planet. It was almost certainly the biggest consumer brand on the internet. And yet somebody else came along and built the brand as the consumer AI app, and Google is like playing catch up.”

“The incredible story about Cursor, when we hosted Michael Truell to come talk to the batch, he was sharing how his product development cycle for shipping features and sprint cycles were one day. At the beginning, during 2023, 2024, around era, they would start to, every day would restart the clock and try to ship things every day. I mean, that's like insane speed. There's no big company that could ship something at that speed.”

“Or try to use it to pick between two different startup ideas because they're trying to forecast five years in the future, which one will have a greater moat. Which just isn't how it works. I mean, literally, you shouldn't do that. Like a moat is inherently a defensive thing, and you have to have something to defend. Otherwise, like... If you have nothing to defend, don't worry about your moat.”

“The problem is, is what typically happens, is you earn a dollar a share, and Wall Street says, oh, earnings are going to be tough next quarter. It's going to be real tough. We're only going to earn $1.10. And then it comes out with like $1.25, and everyone's like, oh, my God, you did great. Well, the expectation was always $1.25. They just told you it was $1.10, so they could walk over that bar a lot easier than if it was higher. So they lower the bar, and then they walk over, and they're like, look at us, we won. It's like a professional athlete playing against somebody's little league.”

“At the end of the day, it's neither bullish or bearish. This is late-cycle behavior. And that data doesn't show that a booming economy, it doesn't show a collapsing one. It does show sign for caution. Late cycle is an area in which it's time to start getting your financial house in order and trying to keep it that way from the things that can hit. Late cycle economy has credit still growing, but concentrated. Business growing, but maybe defensive. Consumers active and inconsistent. And housing is starting to weaken from being flat. That's what traditional late cycle looks like.”