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How I Invest · 5 min · Oct 26, 2026

Steady venture pacing helps limit cycle-driven risk

Matthew Harris says a venture-return downturn is possible, but fund outcomes remain hard to predict in a power-law market.

In this episode

Full analysis
  1. 1:58Valuation discipline can make venture firms miss power-law winnersPro pick 5 min
  2. 17:35AI labs may avoid competing with their biggest customers6 min
  3. 32:44Anthropic's growth could support its reported $2 trillion valuation4 min
  4. 11:53Bain's AI strategy centers on robotics and AI-native services6 min
  5. 8:51AI market leadership can shift despite consensus investing3 min
  6. 27:59OpenAI's open Codex strategy could win the application layer5 min
  7. 52:38Steady venture pacing helps limit cycle-driven risk5 min
  8. 39:48AI agents could expand the market beyond human users3 min
“I do know from our perspective, we try to keep pacing even. So we invest the same amount 500,000,000 a year.”
MHMatthew Harrisat 55:48 · How I Invest
55:48

Takeaways

  1. Harris puts the chance of depressed vintage returns above 10%.
  2. Bain invests $500 million per year at an even pace.
  3. Steady pacing reduces the behavioral cost of investing at market peaks.

About this segment

Matthew Harris says a venture-return downturn is possible, but fund outcomes remain hard to predict in a power-law market. Bain keeps annual investment at $500 million to avoid chasing cycles.

MH

Matthew Harris

Matthew Harris is a Partner at Bain Capital Ventures focused on financial services and technology.

From “Anthropic at $2 Trillion? The AI Bubble, and Why the Best Startups Always Look Overvalued”, Oct 26, 2026. Watch the full episode

Transcript

From the transcript How I Invest publishes with the episode.

  1. 52:51

    Speaking of dystopian possibilities, we earlier talked about this concept of a bubble and how if you keep on overpaying and everybody keeps on chasing momentum, at some point, you're overpaying. And at some point, the bubble bursts. Today, if I use analogy of a baseball game, what inning would you put us in terms of the bubble of AI? It's probably a disappointing answer for podcast, but I just have to plead ignorance.

  2. 53:17

    And I actually go further and say nobody knows. No one has ever seen anything like this. I'll I'll answer one way, which is to say if this is like other technology waves, we're in the eighth inning. And all it would take is one misstep to sort of blow the top off this bubble, like, you know, November 2021. If this is just like any like the SaaS transformation, which I would say sort of started twenty twelve, twenty thirteen and then ended in extraordinary fashion in November 2021, aided by COVID, by rates going down, all sorts of factors.

  3. 54:00

    And then it was an excruciating eighteen months after that. If AI turns out to be like SAS, which is to say yet another chapter in the book of technology, but not a game changer per se. That it probably won't be November 2026, but we are definitely like months and quarters away, you know, in terms of my, like, pattern recognition about What do you put the odds of that at? And percent? I mean, I I just think that's How how would it even be possible?

  4. 54:30

    Because unlike other types of technologies, I feel like... And this is a... Another question I ask people, which is if everyone's getting so much more productive, why hasn't it showed up in GDP? So we'll we'll handle that in a second. But assuming that I'm not myself hallucinating, How is it possible that I'm getting all these productivity gains? I'm getting better, doing more episodes, doing more investments, not using as many resources in terms of human capital, and and at the same time, we're in a bubble?

  5. 55:03

    How's that even humanly cost? I don't think it is. That's why I meant, you know, this tiny percentage. On the high end. Yeah. I think... I mean, now are people systematically overpaying because of this power law chasing dynamic in a... So it might be a bubble from an investment side, not necessarily from adoption. Correct. So I do think are there's a chance that venture returns are depressed in this vintage?

  6. 55:27

    Yes, that's greater than 10% chance. But we also have this phenomena where the winners are arriving at a scale that no one's ever seen before. So in a power law industry, just because you make goofy decisions against, you know, 49 companies in your portfolio and you systematically overpay if you get one of them right and it ends up being 25 of an anthropic, you're still good and your LPs are still good, even more importantly.

  7. 55:57

    So I can't even say with great certainty how venture returns look like in this vintage. I do know from our perspective, we try to keep pacing even. So we invest the same amount 500,000,000 a year. I don't think this is 2021, but I do think you never know. And you do generally know that when you wanna do more, everyone else is having the same animal. It's a Stanley Drunken Miller, which is nothing looks as cheap as after it's gone up 40%.

  8. 56:21

    Right. It's exactly paradox. It's a huge paradox. And so... And the opposite is true too. Something goes down 80% even if there's fundamental value, it looks expensive and you want to sell. Right. So those human factors act on us and all we can do is recognize them. And the conclusion we've come to is you just got to pace. Just give up some of the potential upside for staying in the game. Yeah. And avoiding some of the massive...

  9. 56:46

    The other the human factors of of investing a ton in a given ventures that ends up being a bad one is really significant. Like, there are firms out there who tripled their pace between '20... The industry tripled its pace between 2020 and 2021. So that just means there's like legions of partners sitting on boards that they massively overpaid for, and they're probably terrible SaaS companies that aren't gonna be worth anything.

  10. 57:08

    Like, the human factors of that actually go well beyond the returns of the vintage. They can actually cripple. It's the other side of the survivorship bias. Yeah. You only hear from the survivors. Well, how do you know you weren't lucky? You don't think about the the people that did not survive. Yeah. Exact. So I think, anyway, this is what we've resolved to as a kind of a behavioral, you know, thing that we can put in place to discipline ourselves.

  11. 57:35

    And it's... It is challenging. Going from the existential dread of not knowing where AI is going to the existential dread, you