Why the VC Hype Cycle Always Gets It Wrong | VC Roundtable | E2307

Summary

Podcast Summary: Why the VC Hype Cycle Always Gets It Wrong | VC Roundtable | This Week in Startups (E2307)

Date: July 1, 2026
Host: Alex (filling in for Jason Calacanis)
Panelists:

• Aileen Lee (Cowboy VC)
• Mike Maples (Floodgate)
• Ben Lear (Lerer Hippeau)

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Episode Overview

This episode’s central theme explores how the relentless cycles of VC hype—especially during the explosive growth of AI—skew founder and investor behavior, and why this cycle “always gets it wrong.” The panel dives into the landscape of recent venture liquidity, the implications of massive early-stage funding rounds, evolving exit opportunities, and the challenges of building enduring companies amid compressed boom/bust cycles. Throughout, the conversation is honest, fast-paced, and laced with sharp insight, real-world anecdotes, and a dose of weary comedy about the madness of 2026’s VC environment.

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Key Discussion Points & Insights

1. VC Communication, Social Media & Personal Balance

• The panel jokes about departing Twitter/X life. Aileen and Ben both stopped active tweeting, prioritizing sanity and family over FOMO and brand-building.
  Ben: “In general, social media is…not great. I have young kids, I feel the FOMO…and I just, like, decided to pull out.” [03:36]
• Mike and Alex are more vocal, noting how cycles of news and investment have grown “kinetic” in the AI era.
  Alex: “Cycles of business have been compressed dramatically in the AI era.”

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2. Venture Liquidity & LP Perspectives

• Despite a tough few years for liquidity and LP returns, the mood is brightening with recent IPOs (SpaceX, Anthropic et al). Larger institutions care more about big returns from major unicorns than modest exits.
  Ben: “Most of our LPs are large institutions…they need the SpaceXes and Stripes and OpenAIs…to go public, versus me returning $10m on a $150m fund.” [05:35]
• Aileen highlights the “denominator effect” and how LP venture exposure soared from paper gains, sometimes making them reluctant to reinvest until real cash returns.
  Aileen: “We have one LP…at 45% venture exposure. What will happen when they get the money back?” [07:19]
• Mike emphasizes the “exit optionality” of smaller funds and the importance of seizing liquidity opportunities early, versus being locked into holding out for mega-unicorn exits.
  Mike: “Seed funds can proactively take advantage [of exits] in ways the big guys can’t.” [08:15]

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3. M&A, IPOs, and Reimagining "Old" Startups

• There’s excitement that M&A is reviving, led by vehicles like Bending Spoons, which go after “pre-AI” companies that missed the AI hype boom.
  Aileen: “A lot of us are working with [pre-AI portfolio companies] to make the transition to become much more AI native, or figure out what the exit's going to be.” [09:05]
• Deals like Ignite’s sale to private equity are framed as good timing/luck, with founders doing the hard math around going public in tough markets.
  Mike: “He’s been doing this company for almost 20 years…you miss one quarter and it’s like you just get eviscerated.” [13:05]
• Ben and Aileen both describe re-engagement with old angel/seed portfolio companies; with later-stage investors dropping out, early-stage funds must motivate “sleepy” boards and sometimes drive a full strategic reboot.
  Ben: “We are finding that even as a seed investor, we need to go re-engage with companies from 8, 10, 12 years ago…we have some pretty dysfunctional boards with real companies, but a bunch of people asleep at the wheel.” [14:41]
• “Burn the boats” pivots—shutting down old products to build new, AI-native suites—are happening for companies like Mutiny and Intercom/Fin.
  Aileen: “They basically…had to cut a lot of the people, went back to the drawing board, built a whole new product suite and are selling it now. And it’s incredible.” [18:22]

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4. Growth Metrics & New Funding Realities

• The panel describes a dramatic acceleration in growth expectations:
  • Old “triple, triple, double, double” revenue sequences have shifted to “quintuple, quadruple.”
  • VCs expect breakneck growth to justify huge (>$100m) A and seed rounds. Aileen: “If you’re a founder that wants to raise seed or A or B…right now it’s probably one to five or one to four and a half, depending on what you’re doing.” [25:00]
• Ben points out that this changes what’s fundable; capital is going to businesses with quick, “easy-come-easy-go” revenue, not to difficult or defensible problems with slow sales cycles.
  Ben: “It is preventing capital from flowing into certain kinds of businesses…where the moat is more difficult. It’s forcing money into companies solving problems for right now, for the next few months.” [25:55]

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5. The $100M+ Early Round Phenomenon & Kingmaking

• Seed and A round sizes have exploded. Dozens of AI startups raise $50–300m with little traction, driven by “kingmaking” from major multi-stage VCs trying to lock down the winner in a category.
  Aileen: “Never seen more people start a business three weeks ago and decide they’re going to raise a $20m seed round at $100m pre.” [38:32]
• The risks are high: these founders lose optionality, over-capitalize too early, and may not survive when the hype fades and the “blowups” start.
  Mike: “Nobody…in history has ever had a greater than $10b exit raising that much in their seed round.” [42:19]

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6. The AI Model & Infra Shift (Open Weights, Model Routing)

• Intense cost and defensibility pressures as startups confront rising model/tokens bills; companies are rapidly adopting or preparing to switch between open weight models (e.g., GLM 5.2) to cut expenses. Aileen: “A lot of our portfolios have been playing with [GLM 5.2] and they’re getting equivalent results for a fraction of the cost…they’re all getting ready…to be model agnostic.” [54:51]
• Investment is pouring into AI infrastructure—chips, data center cooling, model routing, and eval—and many see higher defensibility there than in yet-another-agent/wrapper consumer applications.
• But the ecosystem is brutal: hyperscalers themselves will roll out new infra and products, further compressing what’s defensible for startups.
  Ben: “Everyone’s business model is predicated on token prices going down and down…which is actually why Anthropic, OpenAI, Google are so scary—they’re aware of [this dynamic].” [56:19]
• Mike introduces the concept of “acceptance AI”—not just generating but validating work—predicting trusted third parties will become essential.
  Mike: "If slop is abundant, then you start to ask, well, what's scarce? And I think what's scarce is correctness and proof of correctness." [53:48]

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7. Hype Cycles, Contrarian Bets, and the "Theme of the Year" Fallacy

• Aileen shares data on how the “theme of the year” never matches the best companies founded that year: Aileen: “2013 it was wearables. 2018 it was VR. 2019 it was scooters. But then the best companies … never match what the theme of the year is.” [47:41]
• The panel cautions founders: don’t chase what’s hot now—most great companies marinate quietly for years, often in uncool or overlooked categories.
• The best bets may come from “off Broadway founders.” Aileen: “We love pedigreed founders. We also love what we call off-Broadway founders…When you look at the list of the companies...they are not perfect pedigree founders.” [48:44]

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8. Policy, Regulation, and Society’s AI Fears

• The panel is worried about regulation—both overreach and absence—and sees no clear government solution to the risks AI brings. Mike: “[AI models] are so important now…that they've got the attention of the government, and that's always a very mixed blessing.” [63:43]
• Ben reflects popular discontent around AI and economic discontinuity: Ben: “The wealth gap is only getting worse by the minute…I don’t know how this ends anything other than terribly.” [67:25]
• The group also regrets the lack of early regulation on social media (“…negatively impacted by the fact that there was no oversight whatsoever…” [71:13]) and fears making the same mistake with AI.

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9. Notable Quotes & Moments

• Mike, on fund size: “Your fund size is your strategy.” [29:58]
• Aileen, on founder traits: "Hopefully how you also build your reputation as an investor is being there through thick and thin..." [18:22]
• Ben, on reengaging with old investments: "...coming in...and not even active board members and shaking the thing...if we just hang out and grow 10%, 20%...this company might be worth nothing. It's time to get serious." [14:41]
• Mike, on profit-first approaches: "Growth is a combination of ambition and acceptance." [24:03]

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Timestamps for Key Segments

• 02:44 Social media and VC FOMO
• 05:35 Liquidity outlook for LPs and fund managers
• 09:04 M&A activity and "pre-AI" company exits
• 14:41 Later-stage VCs stepping back; early investors taking charge
• 18:22 Burning the boats: full pivots to AI-native products
• 25:00 Exploding growth expectations in AI
• 29:58 “Your fund size is your strategy”
• 38:32 $100M+ seed/Series A rounds and kingmaking
• 53:48 The rise of “acceptance AI” (validation layer)
• 54:51 Moving to open weights and model cost strategies
• 63:43 AI, government, regulation, and risks of complacency
• 67:25 Wealth gap, economic disruption, and social fears of AI
• 71:13 Social media regulation lessons for AI

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Tone and Language

The conversation is frank, sometimes self-deprecating, and threaded with veteran investor realism—and a fair bit of cynicism toward the current "hype for hype's sake" environment. Panelists are transparent about their own experiences, mistakes, and philosophies. There’s camaraderie in their frustrations and optimism, with occasional teasing and laughter breaking the seriousness.

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Closing—Where to Find the Panelists

• Mike Maples: X/@m2jr, www.floodgate.com
• Aileen Lee: X/@aileenlee, LinkedIn, cowboy.vc
• Ben Lear: LinkedIn, www.lererhippeau.com (“best place”)

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Takeaways for Founders & Listeners

• Don’t confuse big rounds and hype with long-term success or optionality.
• Building defensible, lasting companies means resisting the siren song of today’s “theme.”
• Infrastructure and trust layers may offer better opportunities amid commoditized AI generation.
• Expect more painful shakeouts as the hype cycle unwinds.
• The adult conversations about technology, regulation, and social impact are more urgent than ever—especially in an era when neither government nor the industry seems fully prepared for AI’s consequences.

Transcript

[A]

Hello and welcome back to Twist. My name is Alex. It's Wednesday, which means it's time for yet another venture capital roundtable. This time I do have to say we have an incredible panel and as you can tell from the backs, underneath my eyes, there's more than a little bit going on. So today we're going to be looking into strong second quarter exits including a number of IPOs, the return of Anthropic's Mythos and Fable models, rising demand for open weight Chinese models including GLM 5.2, what to make of $100 million Series A rounds and even larger seed rounds and how our panelists are navigating investing in yet another boom this week in startups is brought to you by CLA. Innovation takes balance. CLA's CPAs, consultants and wealth advisors can help you get from startup to where you want to end up. Get started [e-mail] with you northwest registered agent. Get more when you start your business with northwest in 10 clicks in 10 minutes you can form your company and walk away with a real business business identity. Learn [e-mail] twist and agree.com stop chasing invoices and automate your entire contract to cash stack. Go to agree.com and tell them Jason sent you to get 50% off for life. Now today I have with me Aileen Lee from Cowboy vc. Aileen, how are you doing?

[B]

Oh, great. I'm excited to be here.

[A]

Now your firm raised a $230 million fund for and a $140 million opportunity fund back in 2023. You guys have backed Drata Standard, Ker Binti, amongst others. How goes fundraising for Fund five?

[B]

We're not raising for Fund five right now. We're still investing Fund four and it's, I mean, we're going to talk about it. It's a wild time right now, but a lot of exciting things to look at right now and some I think founder quality is incredible right now.

[A]

It's always good to hear. We also have Mike Maples from Floodgate. Mike, how are you doing?

[C]

Can't complain.

[A]

Now you filed with the SEC to raise a $130 million fund 8 in May. Floodgate has backed Lost Energy, Hadrian and Applied Intuition. Have you filled up that new fund?

[C]

Well, I'm not sure I'm allowed to say but you know, we're, we're, we're pretty good shape.

[D]

Good.

[A]

And then finally we have been there from Lar Hippow, which closed a $200 million fund 9 last year, Larry Hippo is back to Zipline, which I've had on the show a number of times. Palmetto ends in business, amongst others. Ben, how are you?

[E]

I'm doing okay. I have more to complain about than Mike, I guess.

[A]

Oh, okay. Well, do you want to start? We can start with a therapy session and then get into the conversation.

[F]

Let's get into it.

[E]

We got time. We have time.

[A]

Actually, before we do anything serious, I want to point out there's two. There's two of us here who tweet all the time, Mike and myself. And then there's these two people on the show today who apparently have lost access to their Twitter accounts, namely Aileen and Ben. So from Mike and I, how do you two manage to shut up when there's so much going on that both infuriates and delights us? Like, how do you. How do you not just constantly go at it?

[B]

I mean, I definitely have become a little bit more of a lurker. I used to be a lot more of an active tweeter.

[E]

So I actually, I was an active tweeter back in the day and actually a pretty active social media user. And I think it was probably during COVID that I sort of felt that the trade was no longer worth it. Like, there was it. I just sort of like hit a wall and went cold turkey. One day I went to a dinner with a friend. He told me that he had sort of pulled off all social media and was living his best life. And I sort of, you know, had like a second and third drink and was like, I can do it too. And deleted, like, deleted the apps and. And really, like, didn't go back at all. I have become a little bit more of a lurker of late, like Aileen.

[F]

But

[E]

look, I just, I wasn't getting the joy out of it. I. I really do think that, like, in. In general, social media is, like, not great. I have young kids. I like, feel the sort of FOMO that comes from it and angst that comes from it. And I just, like, decided to pull out. And I understand that, like, there's probably some trade offs in terms of, like, brand building and, you know, puffing out my chest that I lose as a result of it. But I try to put that sort of time and energy back into other productive things.

[A]

Yeah, maybe Mike and I will eventually grow up and join you guys, but in the meantime, we're mad about everything. So I feel like Mike.

[E]

Well, I'm super pissed too. Don't get me wrong. I just like you know, take it out on my children and colleagues.

[A]

Oh, that's Mike. That's much healthier.

[B]

So what have you guys ranted about recently?

[A]

Mike has ranted about, let's see, everything. California mom, dummy. Foreign policy, domestic policy, tax policy, immigration policy. I mean, Mike, you've been. I went through all your tweets, guys, before the show, and Mike's been on a bender.

[C]

Yeah, Maybe I've got 4th of July on the brain, but I guess, I guess some of these, Normally I just stay out of it all, but I guess lately I've been thinking that there are some things that if. If they happen would be very, very bad. And, and I, I think I'd have regrets if I didn't say anything about it.

[A]

Yeah, well, I bring this up not just to be a brat, but to point out that there's so much going on that I feel like cycles of business have been compressed dramatically in the AI era, and we're seeing things become true in the Q1 and then not true in Q2. So it's a, it's a very kinetic time. I think it's a good time for us to chat and figure out where we are. And from that vein, I want to start with how much has recent venture liquidity helped you guys on the LP side of things? For the last couple years, VCs were raising less money than before. People were raging about a lack of exits. Things have gotten better lately. So I'm curious how that's manifesting in your future fundraising plans and how you're thinking about allocating capital. And Ben, I thought we'd start with you.

[E]

Sure, yeah. I mean, you know, like Aileen, we are not raising right now. We raised our last fund last year. We're in the sort of, you know, generally early innings of deploying that, uh, you know, I think probably like a lot of folks, we had a few years of slower liquidity following. Sort of like a bunch in 21 and early 22. Things have picked up, but I don't, you know, I never feel like I am. Our liquidity is, is what is really important to RLP's. Most of our LPs are large institutions that have a bunch of exposure to multi stage and sort of, you know, gigantic funds that they have huge checks with. And I think like they need the, you know, SpaceX is and stripes and OpenAI's and anthropics to go public to sort of feed money back into their system in large scale versus, you know, me returning 5 or 10 or $15 million to LPs on a, you know, 150 or $130 million fund or whatever it is. And so, you know, I don't get a ton of grief from LPs. I think also I'm very early stage. Like people who are signing up with us and probably with Mike and Aileen understand that this is like the best companies take a long time to mature. I understand we have this like weird very short term view on companies are worth a trillion dollars in 15 minutes. But I still think probably over time we get back to some general sanity around the idea that building great companies takes time. And I've, you know, I think we're lucky that we have LPs that are sort of signed up for that alien.

[A]

I'm really curious about this because Jason has been complaining for several years about a lack of liquidity. He said, you know, the venture industry was under just so much pressure. Yeah, seems that Ben saying that maybe some LPs are just less concerned. So how does that manifest over on the cowboy side?

[B]

Oh, I do, I think it's going to be interesting because obviously a lot of folks are locked up still. Right. But there's a lot of money that's going to get distributed with Space x. We have one LP that had a target venture exposure of 25%. But because there's been so much appreciation from some of the larger fund holdings, they're at 45% venture exposure. And so what will happen when they get the money back, you know, will like the percentage of. It's probably, you know, they want to have diverse portfolios. But I think it will help because they, I think some of them have been a little hesitant to commit more to venture when they weren't getting money out. So I think it's good news for the venture business that they're going to get money back and hopefully they'll put it back into a diversity of funds both large and small.

[E]

This is like back to the denominator effect, right? I mean we're back to sort of like the 21 denominator effect. Paper gains that hopefully turn into not paper gains and hopefully have more staying power than the 21 paper gains did.

[A]

Mike, do you think they're going to.

[C]

Well, we try really hard to have liquidity, you know, regardless of the environment. So we've, you know, we've returned a little over 350 million in the last two years. But, but like our, you know, that's nothing compared to what Founders Fund will get from Space X. But our fund is tiny compared to Founders Fund. Right. Our, our fund is like 150 million. And so we're trying to. I think one of the things that seed funds can do is they have more exit optionality. And there are times when I think that the seed funds can proactively take advantage of that in ways that the big guys can't.

[B]

And that's why I actually, I think we're going to talk about this. But I'm encouraged by the Bending Spoons ipo.

[A]

Yep.

[B]

Because that's a vehicle that's been kind of gobbling up older companies and not necessarily AI native companies. And that's the thing we need because a lot of, I mean, obviously everybody for the past few years has generally been investing in AI native companies. Right. But you've got a bunch of portfolio companies that were kind of pre AI. And so a lot of us are also working with them to actually make this transition to become much more AI native, in some cases burn the boats and build a whole new product suite or figure out what the exit's going to be. But while traditional SaaS companies are trading at such crappy multiples, they haven't been very acquisitive. So I think it's exciting that M and A is coming back and I assume that 27 will be maybe even more active and so there'll be more exit opportunities for what we call pre AI companies.

[A]

Yeah. So just to put some notes behind that, The Bending Spoons IPO price last night went out today priced at $29 per share, up from its range of 26 to 28, worth about 18.5 billion. Non diluted lost valued at 11 billion. And if you want to go read the S1 actually it shows a company in pretty rude health, frankly. Doubled revenue year over year. And I think it had positive operating and net income on a GAAP basis in Q1 of this year. So doing quite well now. Alien, it bought aol, it bought Evernote and Vimeo and I don't know, probably like Caveman Inc. These companies are so old. Do you think that's a vehicle that actually can provide real liquidity to the old unicorns from the 2000 era that are just seemingly drying out on the vine?

[D]

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[B]

Well, they're not all drying out on the vine.

[A]

I apologize. What percentage are.

[B]

But I mean, I think bending spoons and others.

[G]

Right.

[B]

Like maybe bending spoons. There's a lot of PE firms, right, who are going to do this, I think more actively as well. But I did notice like I am still an Evernote user, which people give me shit for, but they just jacked up their price a ton, year over year. So it'll be interesting to see how they balance being public and needing to grow revenue and keeping user bases.

[A]

Are you going to churn?

[B]

I don't. Haven't decided yet.

[A]

Okay. Well, I have to say that you probably are a little bit less price sensitive than the average Evernote user. So I think that if you're on the fence, then that's not really good news for them. Now, I was going to save this for later, but we're talking about it now. So Mike Floodgate backed Ignite back in the day.

[B]

Yeah, that's a good one.

[F]

Yeah.

[A]

Shout out. Vineet Jain, one of the nicest guys in technology. Yes, period. Love that guy. They sold to private equity early last year, February 25, for I think $1.5 billion. And at the time I was a little bit disappointed by it because I'd known Vineet for a while and I really like the company, how he ran it. It's focused on frugality and profitability and all that. But looking back, it actually seems kind of pressured given what we've seen, as Aileen mentioned with SaaS multiples, how common are deals like that going to be? Or are we going to see more like the roll up strategy we're seeing from bending spoons in the next couple quarters?

[C]

Well, well, I think they were a lot more common when it happened. So it was. And it was interesting. Right. And, and I Remember, actually, you were at a dinner we had with Ignite one time.

[A]

That's the one time.

[C]

Yeah. Like, maybe more than 10 years ago, right?

[A]

It was before I quit drinking, so, yes, it was more than 10 years ago.

[C]

So I was on the. So I've been on the board of Ignite since 2008, and, and, and then we exited, you know, last year. And I think that, that Vineet really wanted to go public, but I think that the, the, the, the, the challenge for him was, you know, he's been doing this company for almost 20 years, and you miss one quarter and it. It's like you just get eviscerated. And, and so, you know, there, there was a lot of interest in his company, and, you know, there was just. He'd put so much time and effort into it that I think that he thought that he could create more value being part of this private equity concern. And I don't think we had any idea of what was going to happen to SaaS multiples. I think that's just us getting lucky. But I think in hindsight, he probably made the right call.

[A]

Yeah, I think so. Ben, I know you don't care about liquidity because your timelines are infinite.

[E]

Oh, my God. Let's have that be the thing that comes out of today.

[A]

I've just never heard a VC say, My LPs are so patient. I've literally taken them out.

[E]

That was really not what I said. I. Forget it.

[A]

I'm so glad we're all.

[E]

This is why I don't leave my

[A]

house or participate in any of these things. You're. You're on zoom. You didn't even have to leave your house to come here today. No. Given that you're not under, let's say, undue duress on the liquidity front, I'm curious how you think about private equity or non IPO exits for your portfolio companies today. Are you encouraging companies to look for them if they're not going as quickly, or do you think that multiples will rise in the future and therefore holding on a bit longer before trying to find a landing place?

[E]

It makes more sense to what Mike said earlier. We are also obviously, always trying to figure out ways to create liquidity, regardless of whether or not we have people screaming at us about it? That's the job. Like, that's why we're here. And my philosophy is that companies get bought, not sold. I think it's really hard to go out and decide that it's time to go, like, ship off your slightly broken company. And have somebody pay you not even a good multiple for it, but like maybe anything for it. And so, you know, maybe. And now to reference what Aileen said, like we're spending time with companies from past generations that we think are good companies with still motivated, serious founders, hopefully like unfair data advantages and lots of customers, but maybe that were built for a different time, reimagine what their company needs to be. Sometimes it is burning the boat, sometimes it's building some new products, sometimes it's changing some talent. But I think this is a moment where if you just sit around passively and look at your old companies and say, well, I hope these, I hope they figure out AI, we're going to be very disappointed. And actually this is, there is something that I'm experiencing. I'm not sure if Mike and Aileen would agree, but we are finding that even as a seed investor, we need to go re engage with companies from 8, 10, 12 years ago in ways that I would not have expected because the later stage investors are not stepping up. And I think a lot of it is because they're at funds that have raised enormous, enormous, enormous newer funds. They are very focused on the sort of, you know, investing in the next trillion dollar company. Today they've had a lot more turnover because that's what happens at big funds. The people who made the investments aren't there. And we have some sort of pretty dysfunctional boards with real companies, but a bunch of people asleep at the wheel. And so we're coming in maybe as quite small owners and not even active board members and like shaking the thing and being like everybody, you know, there's a real company here. But if we just think we're going to hang out and grow, you know, 10%, 20% and make a little money or lose a little money, this company might be worth nothing. It's time to get serious. And so we're spending the time doing that and, and then maybe just a little other sort of thought on liquidity we have and maybe this touches on the, on Mike's company that sold last year. I tend to think that if, if you have an outsider come and make a real serious approach, you should take that very, very, very, very seriously that, you know, Eric Hippo, my partner, has this philosophy which is sort of your first offer is probably your best offer and if somebody really wants you, yes, you should of course go run a process and see what else is out there. But there are not all that many moments for companies that are not extraordinary companies to create liquidity. And when Opportunities present themselves. Don't be dismissive and greedy.

[A]

All right, we're going to get to Aileen in her response to Shaking the old Startup Cage. But first we have to do a quick little segment about our dear friends over at Plod. Jason and I are big fans of Plod. They are beautiful little AI note takers that I wear on my wrist, he wears on his lapel. We have, we run tons of notes here at Twist. And to not forget everything, we record it all. If you work here, you're always being recorded and that means we never forget a darn thing. If you want to be cool like us, you can get a plod notepen S at plod AI twist. Use the code twist, save 10%. And if you think AI hardware doesn't work, well, bad news. It actually does. Eileen, back to you. I want you on going to startups that are maybe with dysfunctional boards, shaking the cage and getting them back on track.

[B]

I mean, I totally agree with Ben. There are definitely a lot of board members that are kind of MIA or just, I mean there's been a lot of turnover at firms and it's hard. You've got orphan companies where in some cases CEOs optimize more for valuation in years past than kind of active board members or experienced investors. And a lot of the folks who were newer and had a new checkbook aren't there anymore, which is really disappointing. But I mean, I think that's hopefully how you also build your reputation as an investor is like being there through thick and thin and being there in hard times. That's what it's interesting actually after kind of like ZIRP and post zirp, I definitely feel in competitive situations when we're talking to founders, when they ask to do references, they will ask founders how did they handle a downturn, how did they handle things when things weren't good? Because they know that that's obviously there's a lot of talk right now about data center financing and whether it's going to fall over and this kind of somewhat circular economy and what's going to trigger something to fall over. And we kind of saw this with.com and so I think people got a little bit of the jitters. I'm going to try and raise as much as I can right now, which can be is a double edged sword. It gives you a big war chest to be able to hire great people and to be able to go for a long time, but going for a long time without actually a feedback loop from the market can Also be a negative we've definitely worked with. And in one case, we have a portfolio company called Mutiny that's been in the news quite a bit because they burned the boats. Gel A had a really nice growing product, but it wasn't completely AI native. And they were like, we could continue to milk this and try and tweak it, but it doesn't feel like we're really capturing the moment for customers to really give them an AI native product. And so they basically, unfortunately had to cut A lot of the people went back to the drawing board, built a whole new product suite and are selling it now. And it's incredible. But I think they feel strongly that they would not have gotten there if they hadn't burned the boats.

[D]

Okay, so you have identified a real problem and you put together a solid solution and a business model that you believe in.

[F]

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[A]

Notes now on the Burning the Boats front. Oh, I know how to type. On the Burning Boats front, we saw Intercom become fin and then sell for a pretty quick number. And that was very much a We are going to start over. We're going to become AI first working on, I think their own models as well, if memory serves. Owen said about that. But that was a success. Aileen, how many companies do you think that are pre AI companies can execute a pivot like that and actually land the plane? Because to me that sounds incredibly challenging. But I also, I don't want to be a hater and underestimate founder potential.

[B]

A lot of it depends on who the customer is and what the problem is that you're solving. So there are some customers where they don't want like a completely innovative product. Right. They're not in that trust zone yet where they want everything and you've got especially depends on like the customer base and how big it is. But in Mutiny's case, I think it just felt like there's so much opportunity to support sellers in how they prep for like whether it's getting a lead and then building the relationship to close that could leverage AI that they really wanted to take the time to figure out how to make it, make it work.

[C]

One factor in some of this that I think is interesting, many years ago I was involved with a company called KeepSafe. And we were doing well, but not set the world on fire well. And one day we, we all get in a room and we said, you know, maybe we should stop thinking about being growth first and become profit first. And like what if, what if we operate this company in the rule of 70s, so for it break even, we've got to grow 70% a year. If we're growing 40% a year, we got to have 30% margins. But, but that's just going to be our immutable rule. And so then what we would do is every month we would say whatever our profit target was, we'd put that much money in the bank and whatever we had left was what we could run the business on. And it's funny because a couple weeks ago I was having lunch at Philip Berner's ranch in Petaluma, who's one of the founders of KeepSafe. And yeah, he's probably made somewhere between 10 and $20 million, maybe more, just dividending out the profits over the last decade. And so I like to say that growth is a combination of ambition and acceptance. And it's like, you know, you're, you're entitled to burn venture capital money if on the other side of it, you create enough growth and category dominance to justify that burn. But if you have no path to doing that, I think a lot of times you're better off accepting the reality that you need to be a profit first company and you know, make as much profits as you can. And that company, had they not done that, probably wouldn't exist anymore. But now they're, you know, every, every quarter, you know, we get another dividend check. So I think, I think floodgate put in like a million and a half bucks and I think we've gotten more than $10 million of dividends from them.

[A]

That's a hell of a return. Slow RR, but lovely amount.

[C]

And, and to some degree that's really what bending spoons is doing, right? They're they're kind of, you know, I like to say that a Startup starts at 0 to 1 and they have to have proof they have an insight about the future. Then it's get product market fit, then it's one to X, then it's grow at a rate that's predictable, that justifies your burn. Then there's profitable growth and then there's profitable decline. And I think part of my job as a VC is to help the founder locate where they are in that sequence. And where you are in that sequence has a set of laws of gravity and space time. Right. If you're in 1 to x rapid growth mode, for every dollar of burn that you burn, you have to achieve a certain amount of growth to justify that burn or you can't credibly claim that you're a growth first company. And so I think that a lot of people are growing not fast enough relative to their burn.

[B]

Yeah. One thing I think that's important for founders who are listening or watching is there was for enterprise software this rule where 1 to x was like triple, triple, triple, double, double. Right. That was best in class. Right. You'd go 1, 3, 9, 25, 27, something like that. Right. But that's because of what's going on in AI. The bar has really changed. So if you're a founder that wants to raise seed or A or B, you need to know that basically, I think right now it's probably one to five or one to four and a half, depending on what you're doing, and then probably five to 20. So you really have to be growing to be able to raise venture capital from the folks who do A's and B's. The growth curve looks very different in 26 and 27 than it has before.

[A]

So quintuple, quadruple. Not triple, triple. That's a lot harder.

[B]

What do you guys think?

[E]

I agree. I don't think that it is overall a good thing for the ecosystem that we've moved into this sort of. I think it is preventing capital from flowing into certain kinds of businesses that want to do harder things and that want to, that want to enter businesses where the moat is more difficult or where the sales cycle is more difficult. And I think there's sort of, it's. I honestly think one of the big problems is it's forcing money into companies that are solving problems for right now, like problems for the next few months. I see so many companies that are building based on what the models do today and they're solving a problem that is like A problem that exists for the next 11 days days and raising a bunch of money and going and chasing it and getting like very easy come Easygo revenue. And it's, I, I find it to be very frustrating and, and you know, we as a fund have a little bit of a sort of bias to being gluttons for punishment and like liking things that feel a little harder. And the problem is right now when I want to go be brave, you know, bravery is maybe not the right word, but when I want to go sort of encourage something really difficult, but if it works, there's an actual moat around that business I have to do so into the void. I sort of fund that business knowing that I can't take it or there's a very low likelihood that Sandhill Road is going to be interested in the next round and that I think there's a big gap right now in where we can go take really interesting great sort of hard things with teams that don't look like they're out of central casting for Fallen Capital. I assume you're seeing the same thing, but you know, you guys are in San Francisco and closer to the sun and you know, I'm here in New York and you know, see some of what's going on and feel like, you know, I don't want to say bubble because I do think AI is the most, you know, fabulous, you know, innovation that I've seen in my career. But there's just some, you know, this idea of consensus seed rounds getting done at 50 and 60 and 70 million evaluation. I mean we could go into next topic. But I, you know, this is, this is why I come in grumpy today. Alex.

[A]

No, I, I, I'm here for, for, you know, old man Ben, you know, stamping on the ground. Cool.

[D]

Thank you.

[G]

Yes.

[C]

Good.

[A]

Well, this is all insane to me. I love this. So Mike says rule of 70. When I was taught this by the guys who founded HubSpot, it was the rule of 40. Rule of 70. Dear God. Now it's no longer triple, triple, double, double, double. Now it's 5x4x. And Ben, you're saying that everyone's trying to solve the problems for this minute. So are we just essentially not everybody.

[E]

But I think that that's a general, I'm generalizing.

[A]

Yeah, yeah, no, I'm not trying to, I'm just trying to summarize here. So essentially it seems that only the things that have instant takeoff today are attractive to the multi stage funds, which is changing what you can invest in going back to the top of the show. I didn't think it's going to be that pertinent, but why don't you then raise more money, Ben? I mean, if you're not going to be able to go get Sandhill to take the next round lead, why not do it yourself?

[E]

I have had some of my LPs ask me that question recently. You know, I think that for me, that has to do a little bit with building. You know, each fund we've raised has been a little bigger than the one before. Our eighth fund was 145, our ninth fund is 200. We have grown. But, you know, I don't know that I can solve the problem for these businesses if I have a $300 million fund. And I don't. You know, in our bones, we are an early stage group. We are really about talent. That is sort of like what we're built for. It's what we know how to do. It's what we love doing. Frankly, I'm jealous of people that manage many billions of dollars because I think that, like, those fees are probably super sweet, but that's not. That's just not like who we are or what we aspire to. I want to do early stage. I don't suddenly want to be the, like, series B lead. I think it's a different skill set.

[B]

Yeah, I think, Mike, you're famous for saying your front size is your strategy.

[C]

Yeah, I guess that's my story and I'm sticking to it.

[G]

Yeah.

[E]

By the way, Mike, like, you're. That's a huge inspiration for me and I really, I think it's true and it's something that we try to live by here.

[F]

One of the themes we talk about over and over again on this week in startups is making sure you do your chores. I'm no expert on these things. I have some experience. Stephen Estes from cla is an expert. Let's talk about being cash efficient. Tell us about efficiency and what you see in the, in the top tier startups in your practice.

[G]

We're seeing kind of an interesting trend out there where companies aren't needing to raise quite as much as they had in the past. You really have to be careful as a founder to only take on as much money as you really need. You've got to do the forecast and you've got to do the modeling and you got it dialed in and get it right. Otherwise you're going to end up either not raising enough capital to get to where you're going and you're going to have to go get venture debt or go back, have an extender to the round or you're going to give up too much of the company because you just didn't recognize how much money you actually needed.

[F]

Yeah, very important to get this stuff right folks. And that's really a bummer when startups don't do things in a button up. I always have a great partner, a good partner to have on this adventure while things change. My friend Stephen over at cla.

[D]

So if you want a trusted advisor by your side or who will navigate you through taxes, accounting and everything in between, it's time to take action. Visit claconnect.com with you and don't forget to drop a mention that your boy JCAL sent you. That's claconnect.com with you. Start today.

[A]

Mike, same question to you. Why don't you just raise more money and solve the problem of backing outlier people and just take on those later rounds yourselves? I'm not sure if you have a different answer than Ben, but I want to get more than one perspective on this point.

[C]

Yeah, well, so the way, the way so I do believe your fund size is your strategy. So you know, and the reason is the power law is real. So to me your fund size is a commitment to your LPs about what your largest exit will be. So let's suppose that you have a fund and your aspiration is to have a 5x fund. I believe that what you're really saying is your biggest exit will be 2 1/2 x the size of the fund, terms of exit profit. So if you, if you have a $100 million fund, your best exit needs to be 250 million if you're going to have a 5x fund. And so then it's just a function of what you own and what you get in at and what you get out at. But, but I, I guess the, the in today's world, I don't know if others would agree with this. I'm really seeing two kinds of projects. One is what I would call hot projects. And hot projects are, you know, the multi stage firms love them and they may not necessarily have any momentum at all. It may be somebody peeling out of anthropic or OpenAI rock star credentials and a few good white papers and stuff. And what I believe is the non consensus play for hot deals is the upside's even bigger than you thought it could be. And so it's, it's not that nobody thinks it's exciting, it's that it's even more exciting than you thought it was, in spite of the fact that it's exciting. So Anthropic was not done at a cheap price early, but I don't think most people thought it was going to be worth a trillion dollars. And then there's what I would call weird projects. And those projects aren't even on the radar of the multi stage firms ever. So my colleague Anne Miraco invested this company called SmarterDx in 2022 and it exited for a billion dollars. And that's, that's good living for a seed fund. But I, I don't think it even matters if you're a multi stage fund. I don't, I, I don't think even if you had that exit, it's interesting. And so, so I think that there's, there is a different strategy for each type of project. Right. If you're going to go after something hot, you got to work your way in. You got to build a relationship with a founder. You have to count on the fact that the multi stage guys are going to de risk it financially. And in the weird stuff, I think you got to be prepared to go it alone or to get enough momentum for its own sake. But you can't count on the Silicon Valley echo chamber bailing you out. Right? You've got to, it's got to make it a, it's, it's almost like venture capital in the 80s or something, you

[A]

know, or the 90s. Before we move on, Ben, I think Larry Hippo backed Board, the digital board game company which I quite like. I have a picture here of it. Oh, wait, no, I'm sorry. That's the original Microsoft Surface table. Here it is.

[E]

Oh, okay. I see what we're doing here.

[A]

I did think that up before the show and thought I was brilliant.

[E]

I knew something snarky was coming there.

[A]

I am a big lover, but it is my job literally to sprinkle some sprinkles on top of VC stuff.

[B]

What's a physical product?

[E]

Yeah, it's a physical product.

[A]

It's super cool.

[E]

It is doing extremely well and people love it.

[C]

Yeah, I bought one for Christmas.

[E]

Have you been using a mic? Yeah, it's Bryn Putnam who built Mirror, the workout device that she sold to Lululemon and it's, it's, it's her next business and it's a, it's a very. Look, you know, I love consumer. I've always loved consumer. I've done a bunch of consumer. I think, you know so much of consumer over the last few years has just been very incremental. And so even though there was this Microsoft product from a long time ago, I think in general there's a lot of novelty to the way that Bryn is building this and the way that over time the community will be building their own games and the physical pieces and the creation of new kinds of ip. And I think there's also some big sort of tailwinds to get people and kids off of screens or at least the screens that we are currently addicted to and move to more collaborative play. And so. And by the way, the usage data, which you're always terrified when you invest in something like this pre product and it goes out and you start to sell and you're like, is anyone going to actually use it or did people click on Instagram ads? The usage data is, is pretty stunning. People use it with extreme regularity and it's a fun one but you know, there's still plenty to go when you

[A]

combine board the product with the ability of people to now make their own software, which is still a little bit nascent. Today we're working on making games with cloud code and so forth. But I can absolutely see in the future my children, you know, thinking of a game idea or taking pictures and then having that kind of baked into it. So I think it's a really cool company. But Microsoft is talking about, you know, stuff that doesn't really resonate on Sandhill. And if I was thinking about a category that's out of favor right now, it would be children's games. You know, I mean like it's not agentic orchestration for the usc did the,

[E]

the last round there. It's not so wildly out of favor, you know.

[A]

Mike, where is USV based?

[E]

I don't know, I'm not sure.

[F]

I can't remember.

[A]

Yeah. Is it, is it, is it, is it on the West Coast?

[E]

I think there's probably a Union Square in San Francisco as well.

[A]

Well, there is, but I mean it's

[E]

definitely based in New York. Anyway, I, I will say that this is the. Brynn is the kind of founder who maybe to, to Mike's earlier point, Bryn has some of the qualities that I do think are very attractive to the sort of multi stage Sandhill vibe. And, but, but the product itself is definitely, you have to be sort of a creative thinker to get your head around it.

[A]

I'm just glad things like this are getting funded straight up. Like, I mean, first of all, I loved the original Microsoft service. We had one in the old TechCrunch office right in the entryway. And it was fantastic. And I was a longtime Surface user, so I just like that some things are a bit early and then when the technology is a lot better, this is not the size of a couch, it can really meet its mark. All right. Now, we were talking earlier about enormous seed rounds. I also prepared some notes on what I'm calling the $100 million Series A round. So a couple names from recently. Star Cloud, 170 million Series A. General Intuition, I think that was 320 scale, Cognition, 100 million Scout, AI, 100 million, etc. Lots of these companies going on. How should founders think about these insanely large seed and Series A rounds and what they say about the state of the company and its prospects ailing? Because I don't even know how to describe them because the dollar amount so does not match the stage as I understand it. I don't even know what to tell people when I read these headlines.

[B]

Yeah, I mean, I think they're, they're calling it a seed or an A because it's their first institutional round or their second, but it's not a seed or an A in the sense of how much they're raising, the valuation, who's going to do the next round, and the metrics that people are eventually going to hold you accountable to when you go out again. So if you're raising at 400 or you're raising at 800, you know you're raising a seed at. Yeah, in 2026. I can't. It's. Of all the years I've been doing this, I have never seen more people who started a business three weeks ago and have decided that they're going to raise a $20 million seat down 100 pre. It's wild. And like Ben said, a lot of them are very tuned to like this point in time and this point in time, generally every idea, every problem that people are facing has 15 or 20 competitors. And you know that like the ecosystem is evolving so quickly. You don't know what free tools, the hyperscalers or the, the frontier models are going to give out and wipe you out quickly. And I think when you raise some, and I think people are also planning on spending a lot of it on tokens, which that's also a moving puck where I think the number of models that are coming out that are going to be like the open source models, the open weight models, they're a lot cheaper and they're getting so much better that I think also token spend, hopefully for startups will go down. So that won't be the reason why you need to raise 20 million bucks because you won't need 10 for tokens. But it just sets you up. If you're at 120post after your seed, then you and your employees and your investors want to feel a markup. So you probably want to be at 200 or 300 for your next round. So you're calling on people who are basically doing 50 to $100 million round sizes and they're going to be looking for traction and customers. And I think what Ben alluded to you earlier about revenue quality versus just like everyone trying stuff and the renewal is not looking great and a lot of people falling out because they're trying everything right now. You just have to really be on your game and know what you're signing up for when you raise those prices.

[A]

Yeah, I keep seeing companies doing like agentic security, like giving agents identities and so forth. And I'm like this is cool, but I think I've lost track of the number of companies that have raised $50 million to do that.

[E]

Well, a lot of these early rounds though Alex, this is like there's, there's king making going on in a way that has never, that I've never seen before. Or queen making or, or they, or,

[A]

or, or them making, they making whatever you want.

[E]

There, there is, there is makings happening where you know, it like a company gets knighted as the, you know, the one or a big multi stage, you know, puts in the first check and sort of likes what they're seeing but it's a competitive category and they, they want to communicate something to the market which is stay away, watch out, we've got this. And in some categories you have two or three kings or queens or whatever.

[B]

But it doesn't always work like no, no, no, no.

[E]

By the way, we are still in the part of the cycle where right now people, we have, we don't have the blow ups yet. We don't have the collapses of the companies that have raised the $100 million Series A's so everything only goes up and to the right at this moment in time. At some point in the next 12 to 36 months, the rubber meets the road and we figure out what companies are real and what companies raised hundreds of millions of dollars and don't have anything. And if you're going to have companies that are worth tens of billions of dollars in a year, then you are going to have companies that are worth tens of billions of dollars that also go to Zero. Which traditionally, like wouldn't happen on the speed. You know, it has to happen.

[A]

Yeah, yeah.

[C]

You know, it's interesting if you look back at the dot com days, where did the big exits happen? Everybody remembers Amazon, Google, companies like that. But most of the people got really rich in that era are the people who got exited in a window of time at the end of 98 until early to mid 2000. You know, if, if Mark Cuban had raised $100 million for a series abroadcast.com we wouldn't know who Mark Cuban is today. Right. And so I think that what a lot of the founders are missing is that, great, you can raise $100 million in your seed round. Nobody that I can find in history has ever had a greater than $10 billion exit raising that much in their seed round. The biggest seed round I can find on record with the exit that size is whiz, and it was $21 million. And so what happened in the dot com era was people raised money at these crazy prices and then everything crashed. And the venture firms are like, okay, I've got to figure out which companies are real and which aren't real. And a lot of these companies had to give the money back or pretty much had to shut down because there's just no way that even if they executed perfectly that they could ever be what they raised their seed round at. And the venture firms are trying to figure out who the winners are, who to stick with. And so I think that a lot of people lose sight of the fact that you lose an amazing amount of optionality by raising rounds this way. And if your goal is to create generational wealth and you believe we're in a bubble, this is the last thing you would do. You know, you would position yourself to profit in a wide variety of scenarios.

[A]

People keep throwing the phrase generational wealth around. It feels like it's like a TikTok theme. I don't even know why people don't realize that 10 million is generational wealth. You don't need to have 500,000 trillion billion dollars anyways. Alien, you mentioned raising 20, spending 10 on tokens. That to me implies that the startups that are raising relatively outsized seed and series A rounds are doing so not simply because they can, but because they have a relatively high cost basis. So do you think that startups are kind of forced into raising this type of capital early because they have expenses they need to meet? Not just humans. Now you also have your token budget or are they just making a mistake and kind of just Getting over their skis too soon.

[B]

I think it's both. I mean it's, it's getting better, I think. I mean if you chat with your portfolio companies right now, like I think one of the interesting things is obviously like Claude Cowork is amazing and tags is really fascinating and it's smart because it can create lock in. But a lot of folks know that they need to build layers so that they can switch models. Right? Because I mean most of The Frontier model CEOs will say like you don't need to use the best, most expensive model for everything. Right? So you actually have to build things that you can swap things in and out. And meanwhile the labs are going to try and lock you into using their model as much as and using their tokens as much as they can. So I think that there is just what is exciting for investors and founders is like there's a lot to be built for this new ecosystem of AI. There's a lot of infrastructure, there's a lot of security. I mean there's a reason why those are hot areas is because we need a lot of new stuff.

[A]

Yeah, just to throw some notes on that, Etch just announced that it's raised $800 million for its transformer specific ASICs. Light Matter has raised 850 DG Matrix raised 20 million for solid state transformers, which none of us here ever thought about until like 20, 20 minutes ago. There are even a number of companies, startups that are working on data center cooling alone. So Aileen, do you think that those companies fall under the companies for this

[B]

moment or my old, my old portfolio company Bloom Energy, which I worked on at Klanner, is one of the beneficiaries of this incredible data center because people need power. And so yeah, there's a whole, yeah, you do a map of all the things you need in data center or for AI, compute and like memory. Like look at Micron's numbers is incredible.

[A]

Yeah, go, go read Micron's earnings. I'm telling people, just go look at them, it'll blow your top. Now Ben, you're slightly more consumer focused. So how much of this translates over into your world?

[E]

I mean I am more consumer focused. As a fund we are probably, you know, 75% sure. I look, I mean I'm very excited about consumer right now, albeit I'm still searching for the sort of like application layer.

[B]

Boom.

[E]

On the consumer side that feels really differentiated. We see a bunch of lightweight rappers that, you know, have a bunch of explanations for why they're not lightweight rappers. That are still lightweight rappers. And you know, it's obviously unclear what chatgpt or Anthropic or Google or whoever will, where they will sort of extend their products. I am very open for business on the consumer side. I would love to find but, but I really to find companies. I really do think though that building a, you know, an another agent to do something that is built on everybody else's infrastructure is just like not that exciting. I keep getting to not the finish line on this.

[A]

Yeah. Now Aileen, you shared this back in May over on X.

[E]

Back to your best share of the year, Aileen.

[B]

It wasn't my chart, I think.

[E]

Well then I give you credit for reading. But I love this.

[A]

Aileen, for folks who are on the audio version, can you just quickly sportscast what this is what it shows?

[B]

There's this. It's funny. I would love to work with anyone who wants to build like a tech gestalt machine because every year there is a hot theme. So 2013 it was wearables. 2018 it was VR. 2019 it was scooters. But then the best companies that are actually founded in those years never match what the theme of the year is. So anthropic was when crypto was really hot in web 3 Wiz was when we were talking about future of work. So yeah, you just can't. First of all, to Ben's point, it usually takes a long time for a great company to be built and a lot of these companies for the first three to five years, no one's heard of them, they're not cool, they're kind of baking. And so you kind of have to have faith and take these leaps of these risks. We love backing to the earlier point. We love pedigreed founders. We also love what we call off Broadway founders. People who don't have the perfect pedigree. And when you look at the list of the companies who founded the founders of a lot of those companies, they are off Broadway founders. They are not perfect pedigree founders.

[A]

The founders of databricks were academics and open source software kids. You know, hard hardly your.

[B]

I think in today's world that's considered pedigreed.

[A]

Okay, but at the time that was kind of a non consensus but I know we've, we've raided academia and now there's like three people left. Yeah, yeah.

[B]

So it's like a whole venture firm strategy is just spending time in university labs.

[A]

Well, you've sold me on venture at last, Aileen. I volunteered. That sounds like. That sounds like A hell of a good time. So why is the conversation so wrong? And in this case what are the categories that are hot now that are not going to manifest great companies later on? Because I know you guys place bets, but a lot of founders listen to this and I just. If we can give people a way to not go down the wrong path, I think it'd be very helpful. So. So Mike, what do you think is the most overhyped thing to build today? Apart from agents of course that founders probably should stay away from? Oh boy.

[C]

Yeah, it's. It's a tough one for me to answer because I root for all of them, you know. You know I think that, that I would say that agents that improve productivity and the function of agenc workflows I would stay away from. So I think that you've got to have something that's attached to it that creates some type of path to network effects or some type of cumulative increasing returns power. So I would stay away from any type of AI productivity or workflows that doesn't embody some type of increasing returns mechanism at the core design. And most of them unfortunately don't. Right. You look at it and you say that's awesome. I can totally see why I would want that. But I don't know why Sam Altman is not going to have that in his next demo. So that's, that's what I would look for.

[A]

I just realized that I made my agent trust point and aliens company firm is back to Drata. So yeah, do you want to, do you want to tell people why my slander was incorrect?

[F]

Sorry.

[B]

Well, I know I was going to say. Well actually like, I mean I think that's an example of a company that was started before LLMs but it's not that old of a company. It's grown really quickly. Drata. But trust is really important. So I think when you have, when you've got mid market and enterprise relationships and you are helping them with compliance and trust and visibility because so many companies are interconnected and you need to. If you're going to poke a hole in some and pull data in or out of a company, you need to make sure that they're doing it securely and they've got the right business processes in place. Like that's not a burn the boats. Whoops. We're replacing everything completely tomorrow because you need to have. These are relationships where I think consistency and trust is really important. But Drata obviously is going to be helping people monitor agents and the trustworthiness of agents so that's kind of more of an evolution of the relationships they have with customers and what their customers want. So we're really happy to see where that's more of an evolution than a burn the boat situation. And I think it's smart one to

[A]

prevent Ben from thinking I'm only picking on him. Alien. Tell me why that the either major AI labs themselves or the current owners of enterprise workflows won't do that themselves and consume what Jada is trying to buy.

[B]

I mean, I think like, I don't know, Mike is so good analogies. He'd be kind of like, that's like letting the fox watch the hen house. Is that the analogy? Like you want to have a trust, you want to have a trusted third party that isn't your current vendor that's trying to use all your data.

[C]

Yeah, so, so I'm, it's funny because I've been work, doing a lot of thesis work lately and Drata was one of the companies that I kind of regret missing based on some of the work that I've been doing.

[B]

Not too late, Mike.

[A]

It's only a $2 billion valuation. Get your money in now.

[C]

So the way, the way I've internalized it is that AI creates abundance in terms of work products. It, it creates generative. AI is generative. But what people are going to want to start having is what I would call acceptance AI. So like, like for example, when you have financials, you have an audit firm audit your financials. It's not enough for you to just say I'm really good at doing my financials. You have to have some trusted third party certify and that, that, that credible neutrality is important. And I think what's going to happen is there's going to be a lot of AI generated slop across the board. And it's, it's no longer going to be just the work that gets outputted. It's going to be the work that counts. It's going to be the work that is that there's a consensus mechanism for validating. And quite often you're not going to want to trust, you know, the, the Frontier labs to do that. You're going to want a credibly neutral third party. So I, I agree with Aileen. It reminds me a little bit of why we invested in Okta back in the day. We thought that, you know, identity management should have a neutral trusted person. Right.

[B]

Yeah, that's a good one.

[C]

So like to me, if slop is abundant, then you start to ask, well, what's scarce. And I think what's scarce is correctness and proof of correctness. And if you can, if you can be seen as a credibly neutral network effects scalable provider of that, I think that that's in many ways that to me is where the application layer is going to come alive in a lot of these.

[A]

So we're talking a lot about costs here, controlling them and kind of owning your own data. And Alpha. A lot of people in the last couple weeks have been talking about moving to open weight models, especially GLM 5.2 seems to be quite hot and this is due to the government essentially precluding us from accessing the latest models from both Anthropic and OpenAI lately. Can we just kind of look through the headlines a little bit and tell me how prevalent is it that startups are actually either rolling their own models or simply turning to existing open weight models to either reduce costs or to ensure that their data doesn't go to training Anthropic into building what they've already put together. And Ali, why don't we start with you, then we'll go to Ben, I

[B]

was just thinking, I keep thinking that GL1 was like the, was the new. Is the new GLP like, you know, like this, the gestalt of this year is like GLP1 and maybe we had this deep seat moment and now we have this GLM moment. Right. Which is. It's quite good. A lot of our portfolios have been playing with it and they're saying they're getting equivalent results for a fraction of the cost. And I think that's why they are all getting ready if they're not to be model agnostic and to not spend as much time fine tuning because you could spend a lot of time and money fine tuning something. And how long is that going to by you? A month. It's not a great use of time and money because stuff is moving so fast.

[A]

So unpack that for us. So essentially if you train, if you fine tune Kimike 2.5 as cursor did to make composer 2 and 2.5, by the time you're done with that they'll have Kimike 2.6 and then 2.7. So you're always, you're chasing a ball that's going faster in front of you. Yeah, that's almost dispiriting alien because I would love it if founders were able to take the best from the open way open source world and then really turn it into a weapon they can take to market. But it Sounds like you have to kind of take what they offer, just the whole cloth.

[B]

I don't know. Others should weigh in here. But from what we're hearing from portfolio companies are not I think some people considered it and they started doing it and they're like wait, this is not a great use of our time and money. There's a lot of other ways we can benefit customers.

[A]

Ben, jump in here from the firm enterprise perspective. And also if you have any consumer notes on this particular topic, I would love to hear them.

[E]

I don't know that I have consumer specific notes. I think in general in the everybody is building everything multimodal and has to out of the box be able to say I am not beholden to any one model and everyone's long term business model is predicated on token prices going down and down and down and down and down. And so I think, you know, I mean generalized models are going to get better and better. The fact that this conversation is happening is actually though like the flip of it is it's why anthropic and OpenAI and Google are so scary because they are aware of the quality of open source and the fact that they're not going to be able to just go and endlessly charge more and more and more and that they're going to move further in the application layer and like they're going to do it too. Which makes the application layer right now just like a finicky weird space to invest in because it's not clear where infra and application layer sort of bump into each other. And you know I do think though we will move to and actually a colleague of mine wrote an interesting little sort of substack yesterday.

[G]

This.

[A]

I wrote it.

[E]

I thought it was well written. I was.

[F]

I gave him a hug.

[A]

You're talking about the end of decisions by Maurice Rosa.

[E]

Maurice and just the idea that we are sort of real high level decisions are starting to be more possible with with AI. And you know I, I don't know exactly. Like I think that's where we end up with like the most expensive models having a real expansive market for a kind of decision making that I don't know is really that we're, we're quite yet relying on AI for to summarize

[A]

what we're talking about here and if you're watching this later on it'll be in the show notes a link to the the post the End of decisions. But what Maurice argues is that we've seen the effect of essentially computation in fields like chess and most recently in poker, if you play cards, you know about GTO and so forth. And he says that AI is quote, the first general purpose reasoning layer that can start to function as a solver for domains that have historically been too qualitative for software. Now if that's true, Ben, then to me, the actual incremental or marginal intelligence gain you can get from a new frontier model version is incredibly valuable. Because if you can literally have the brain that runs their entire business be smarter, that's quite useful.

[E]

That's quite useful. And that's why I think the like, that's where that business model makes more sense than doing the, you know, checking my inbox and preparing some drafts for me and, you know, whatever.

[C]

Yeah, yeah, the way I've kind of internalized it. And I really owe this thinking to my partner Anne Miraco. So Anne's been doing all this work with companies that she calls AI pilled. And an AI pilled company basically thinks in terms of what processes, what decisions, what mechanisms do they have that define competitive advantage. That could be thought of as an ever improving compounding loop. For that you want to use the best models and you're using those to gather customer feedback, come up with new product ideas, ab test different things. You want the most intelligent models possible. That I think is different from what goes in the bill of materials of the product you ship. And so sometimes you can get by with not the very best model for certain functions, sorting email or performing certain functions within a product. And so what I'm finding that once people create new knowledge with the frontier models, they capture and transfer that knowledge with the cheaper models. And so it's kind of like how do you turn a deep work discovery into a checklist, manifesto deliverable and you progress down the ladder of model expense as you do that.

[A]

Do you think most startups are capable of building the routing mechanism and collecting the necessary context to actually enact something like that? Or is this only the companies that are the most AI pilled? No one's sleeping, everyone looks frazzled, they've got Alex carp hair going on and they're just wizards, you know, at the top of the tower.

[C]

Well, I think when you're an AI pilled company, you're not, you're, you don't mind spending money on the frontier models because you're, you're, you're token maxing as a person or as a C level manager or as a, as a team. To me that's a separate issue from, you know, I'm shipping an AI travel agent as A consumer app. And I want to know what aspects of that travel agent need the frontier models versus what aspects of that can be adequately solved right. With open source models. And I think that that's where, I think that's where the open source models really come in.

[E]

And there'll be a bunch of interesting companies helping with routing and evals. And you know, I don't know that, I don't know that companies will have to build that infrastructure themselves versus buy that infrastructure and focus on like their core value prop.

[A]

Then what are, what are they owning if they don't own the routing? They didn't build the model, they're not doing the compute, they don't have the customer data. Then what the are they for?

[E]

Well, hopefully they have the customer data.

[B]

Yeah, good job.

[E]

They better have the customer data.

[A]

So they're just, they're just a bucket of data that isn't even theirs and they're just doing whiz bang stuff with it and that's the whole jam. That does not sound defensible. That sounds like this is why the

[E]

job is hard right now, dude. Frustrating.

[A]

Okay?

[E]

We're looking at so much non defense sensible stuff every day that by the way then goes and gets done at 50 by someone who looks pretty smart.

[C]

But like, let's just take an example, right? Like applied intuition, you know, they're, they have a very differentiated product and they're doing very well. But they, they're AI pilled in the sense that they've created a real time performance feedback system where you know, they, they can get input about which managers are most effective and what's working best and things like that. And they can, they can implement these systems at enormously fine grain detail that you could have never imagined doing in the past. And so, so they're not, they're not necessarily AI pilled in the sense that they're doing all this to make their end products different. But the, but they're, the way they do business and compete is fundamentally impacted by it because they're, they're embedding AI into the, just the lifeblood of how they force multiply every employee.

[A]

Have you seen Bedrock Robotics?

[C]

No, I haven't. Well, I've heard of them, but I haven't spent time there.

[A]

We had them on the show the other week. They're doing something kind of related to this and I really love them because what they're doing does seem defensible because they're going to a very specific part of the world where there's no other companies maybe Applied intuition. And they're building essentially Waymo for diggers. And it's a great idea. What an enormous industry that no one cares about because no one adventures ever held a shovel in their life or startups, you know, tech people. So I think it makes a lot of good sense now. Okay, we're going a little bit long, so I want to do a couple of final questions for us. And Mike, we're going to start with you, and then we're going to go around, give the Trump administration a grade on how it handled mythos and fable. And do you think that major AI labs have been actually harmed in the last couple of weeks, or do you think this will blow over?

[C]

It's hard for me to grade the Trump administration because I just don't know all the things behind the scenes. And so I'm reluctant to. I do get nervous about. These frontier models are so important now that they've got the attention of the government, and that's always a very mixed blessing. And so I get nervous about the government sort of backdooring its way into regulating AI in the way that I was afraid that the Biden administration was to.

[E]

Going.

[C]

Going to do. And I think that would be very bad in terms of our competitive posture with China. So I, I do, I do hope that we can resolve this, but I. It's hard for me to give a grade because I think in some ways it is a work in progress. And I don't, I don't think that the hyperscalers have done themselves any favors in the discussion either.

[A]

And so I point fingers at Amazon, but it was definitely Amazon.

[C]

I think, unfortunately, this is an example of us muddling through a situation where you're seeing the sausage be made in real time. And it's hard to say that there's an optimal strategy. You know, Alen, you were going, yeah,

[B]

I said better than Mike. I mean, it's hard to know. Obviously, we're not behind closed doors. We don't know what those guys know about what can be done with the models. And, you know, there's. Yeah, there's. There's a lot of history here, right, about like, whether it was developing nuclear weapons and the scientists who were building them having concerns and wanting to talk to people about what should we do about this? Should we build this? We not build it right there. So we obviously want the United States to maintain its edge, but we also have to be prepared for there's a lot of nefarious actors who can do a lot of bad things and a lot of Our companies, both our federal institutions and companies are not ready for the fact that basically we can be trying to hack into systems 247 with agents.

[G]

Yeah.

[A]

The struggle that I have with that, and thank you both for answering that with such clarity and honesty, is that the rest of the world isn't stopping. And so unlike the Manhattan Project, when we were very much ahead of the Soviets, of the Germans, China's really banging on. I mean, we all saw the GLM 5.2 headline about how they think that it's going to be roughly commensurate with maybe Fable, maybe Mythos. I wanted to you next. Your question is very simple. How's Crunchbase doing?

[B]

I think great. We love Crunchbase. We're proud of Crunch. Tell me more.

[A]

I own a lot of shares of Crunchbase, so tell me about how it's doing.

[B]

I'm not. They have raised quite a few rounds and we were early investors, so I am not as close to the latest and greatest. But I think, like you were saying before, having data is really important. Having proprietary data is really important. Crunch. A lot of proprietary data and private. And a lot of private company data, which is, as you know, like, it's. It's very valuable. A lot of VCs will use the models to ask for competitive intelligence and information, but private company data is one of the hardest things to find out about.

[A]

I'm really hoping that comes good and that way my children can eventually go to school where I went to school. It'll be good. All right, Ben, to round us up here for you. I'm curious what you think we should do at the startup level, the venture level, the technology industry level, and maybe even the government level to ameliorate what I think we can all see as rising discontent amongst the populace against AI. And this is often seen in data center protests and so forth. But what are some proactive steps that the tech industry can do to get on the right side of public opinion before this becomes an electoral issue?

[E]

My question is so much harder than this is. This is like a setup. I'm like, I. I can't believe that you just laid that on me.

[C]

It's like you're being punished.

[E]

Like, I came here, I was fun.

[B]

When Ben's on the hobbit trying to be nice.

[A]

Well, the cool thing is about me is that I don't want your money, so I don't have to be nice.

[E]

Okay, great.

[D]

Cool.

[A]

So everyone else has to kiss your ass.

[E]

Look, that is a. That is a great question to which I do not have A great answer. I, I think that I am always amazed by how negatively AI is viewed by people that don't work around this business. Like friends that I have that are 1 or 2 degrees removed are generally terrified. And I think think of, by the way, there's also this narrative that you know, somehow like I think people actually think anthropic is like pretty good, but OpenAI is like totally the, like you know, the Empire in Star wars or something. And you know how these stories get told. I, I think it's a, I think it's a big issue maybe to touch on the question that the other two answered. I don't, I don't trust our government to know how to monitor this and to, to sit over and to figure out what, how we should or shouldn't use AI models or like what the rule should be. At the same time we're in a, like we're in a cold war and have been for a while and you know, even though it's not called that and like this is national security but against what's best for jobs and the economy. I mean the wealth gap is only getting worse by the minute in a way that is like, I don't know how this ends anything other than terribly it is that we're set up in a, in a really unfair, awful way right now. And this is an AI is, is not going to make this better in, in any short or medium term.

[A]

Yeah. And if you're on the video version, I just pulled up a chart from our dear friends over at Fred which shows the, the share of labor comp as a percentage of GDP and if you go back to the 50s, the era that people like to kind of pine for fairly or not, it was up in the high 60s and it's fallen down very sharply lately. All the. Down to about 57, which I think is really the root of a lot of discontent. And I don't have a solution either. But I think it would also be incredibly sad if we ended up shooting our own feet or tying our own shoelaces and preventing a lot of future economic gains because we couldn't figure out a way to share the pie a bit more effectively. Now that just seems to be a non GDP accretive approach. But you guys are not by the

[E]

way, maybe but like going in, you know, some of these, you know, I'm not in California, but the billionaire tax and some of these sort of, you know, very brute force measures feel like you know, at best band aids or punishments, they. That does not feel like the solution to figuring out how we fix this problem?

[A]

No, because everyone's going to leave. I'm already talking to founders who live in Nevada just across the border because they want to get away from the tax.

[C]

It's interesting because, like, when you think about it right now, if you're a free market capitalist wanting to make a pro common sense argument for it, you have no home. You know, the, the left is becoming Democrat socialists and the right is MAGA and saying we hate immigrants. And so, you know, like, you can't even make a credible case for why AI is good because the, the people driving the discussion don't want to hear it from both ends. And so that, that part of it really bugs me is that there's no, there's no natural home for the adult in the room. Conversations about what the right answer is.

[E]

Well, there's certainly no party for it and candidates for it at a, you know, like, I don't. Let's, let's see where we get in 200.

[B]

Although, Ben, what you were saying about, I don't know if I. It's not about the trust or the effectiveness of the government, but I certainly wish, looking back, that we had had more regulation of social media.

[E]

Social media, Yep, yep.

[B]

And that we have a whole generation of kids that have been so negatively impacted by the fact that there was no oversight whatsoever for social media. And obviously the ramifications from a security perspective are so much more grave with AI if we weren't able to.

[E]

It's a fabulous point. It's a fabulous point. And I, I, having young kids, you know, we've been left holding the bag to try and, you know, make them the only kid in the grade without access to Snapchat or something to punish them for the fact that nobody got in front of this.

[A]

Yeah, I'm not looking forward to those days. I literally had a question in my fun section at the bottom of our notes today that was how are you teaching your kids to thrive in life and the post intelligence era? And I wrote that as a joke to myself, but I really meant the post AI era. But I think post intelligence actually may kind of better encompass. One thing I'm really concerned about is that a lot of people just can't read and can't do math. And I don't think that giving people during their learning years access to tools as powerful as AI is going to encourage them in a lot of cases. And I don't think parents know what the hell they're doing either. And now that I have kids that can reach for things. I see how they react to screens and it's made me rethink my entire relationship with technology. But here's some good news. Technology historically has made things better and I think it's going to keep doing that, even though there will be some bumps in the road. I'm a long term optimist and I think that this is all going to end up being very good. I just hope we don't throw a couple of generations of kids into the MA as we get to that point. This is not where I thought the show was going to end. I'm not going to lie. Maybe I should have shaken up how we did things. But, guys, an absolute, real treat today to have you on to talk about all this stuff. Just before we go, where can people find you online? And is there a category your firm is looking to invest in? And Mike, let's start with you.

[C]

Yeah, I guess you could find me on exit M2JR. And then our website is www.floodgate.com and basically I'm investing in companies that complement the abundance of generative AI. I call it acceptance AI, but it's, it's the companies that ensure the correctness of the work rather than just generating more stuff. And so that's, that's what I'm looking for.

[A]

All right, Aileen.

[B]

I'm Aileen Lee on X and also on LinkedIn. And we're Cowboy VC and we're generalists like these guys. We've been doing this for a while, so some of our best investments have been things that we never would have had on kind of like our shopping list. It's really what founders have insight about and so open for business.

[A]

And Ben, take us on.

[E]

Yeah, as you mentioned earlier, I'm not very active on Twitter, but I am benjlear and I use LinkedIn a little bit more, but not a ton. And we'[e-mail] but probably LinkedIn is the best place. And like Aileen, we are generalists. We're looking for great people early.

[B]

Yep.

[A]

If you guys are doing the investing, I think the future will be okay. Thanks all for coming on. This has been Twist. My name is Alex. We'll see you all next time.