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VC 01: Inside the New Exit Economy: IPOs, Secondaries & AI with Meritech’s Alex Clayton

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Who we sat down with

Alex Clayton is one of the clearest minds in growth-stage investing, the person elite founders turn to when the market is noisy and the stakes are high. A General Partner at Meritech Capital, Alex has built a reputation for breaking down complex businesses with uncommon clarity, from his legendary S-1 teardowns to his frameworks on power laws, secondaries, and AI-native growth. Before Meritech, he honed his craft at Spark Capital and Redpoint, backing breakout companies like Braze, JFrog, Outreach, Pendo, Duo Security, and RelateIQ. A former ATP tennis pro and Stanford team captain, Alex brings that same discipline, pattern recognition, and competitive fire to evaluating the next generational companies.

Discussed in this episode

  • Why GAAP revenue and cash burn are the two metrics that quietly govern everything.
  • How AI is changing growth rates, margins, and what “good” looks like in SaaS.
  • The rise of secondaries, and why they now rival or exceed IPO volume.
  • How to read an S-1 like a pro (and what Alex looks for first).
  • Founder ownership, fund lifecycles, and how long companies really stay private.
  • Why power laws in venture are getting even steeper in the AI era.
  • How AI is reshaping pricing models from seats to usage and outcomes.
  • Which iconic private companies are most likely to go public in the next 3 years.

Episode highlights

02:40 — Is the IPO window really back?

05:10 — Secondaries quietly outpacing IPOs

08:10 — The only two metrics that matter

10:56 — AI growth that breaks SaaS mental models

26:20 — From “software” to “SaaS” to “AI”… and back again

29:25 — Seat-based pricing vs outcome-based AI pricing

34:55 — The capital tidal wave & longer private lives

44:00 — Bubble vs biggest opportunity of our careers

57:17 — What the rest of the 2020s look like

1:03:41 — Why GAAP revenue + cash burn still win

Key takeaways

1. Gap revenue is the ultimate reality check.
Investors can argue over ARR definitions and experimental budgets, but GAAP revenue is the money that actually hit your bank account. Founders anchor on that number to understand whether customers are truly using and valuing the product, not just signing ambitious contracts or pilots.

2. Cash burn is the compression of every efficiency metric.
CAC payback, magic number, gross margin, and sales efficiency all show up in one place: how much cash you burn to generate that revenue. In an AI-native world where metrics are in flux, burn remains the cleanest summary of whether you’re building a business or just buying growth.

3. Secondaries are now a core part of the exit stack.
With companies staying private for 12–17 years, secondaries have exploded to 5x over the last decade and in some years surpass IPO volume. That reshapes incentives for founders, early employees, and seed funds who can get meaningful liquidity long before a traditional IPO.

4. The “10-year fund” is breaking under private-market reality.
When iconic companies compound privately for well over a decade, rigid 10-year fund structures stop matching how value is created. Growth funds increasingly need flexibility, both to hold winners longer and to use secondaries as a pressure valve for LP liquidity.

5. AI is blowing up traditional SaaS growth benchmarks.
The classic “triple-triple-double-double” playbook is being replaced by companies going from zero to $50–100M in ARR in under two years. That creates more tolerance for imperfect churn or margins at the growth stage, as long as the demand curve is clearly non-linear.

6. ARR is getting fuzzier, just as stakes get higher.
From experimental AI budgets to GMV being labeled as ARR, revenue definitions are loosening precisely when dollars are scaling fastest. Sophisticated investors are digging into what’s recurring, what’s usage, and what’s one-off experimentation rather than taking headline ARR at face value.

7. AI won’t turn software into a toaster market.
Yes, some categories will commoditize, but the best founders will use AI to deliver exponentially better outcomes, not just parity features. Venture returns will accrue to markets where the buyer deeply cares about the product and where the best product can capture outsized share, not just compete on price.

8. Pricing is shifting from seats to outcomes and consumption.
As software starts to replace work, not just workflows, buyers think in terms of headcount saved and outcomes delivered. That naturally favors platform fees plus usage-based pricing, aligning revenue more closely with value and creating bigger long-term upside for true category leaders.

9. We’re in a bubble, and that doesn’t contradict massive upside.
There’s clear froth in AI, but that can coexist with the creation of the largest technology companies we’ve ever seen. The job for investors is to hold both truths at once: be disciplined on unit economics and durability while staying open to non-consensus, power-law outcomes.

10. Focus is a superpower in an AI-saturated deal flow.
With a firehose of new AI companies, tools, and narratives, it’s easier than ever for investors to chase noise. The edge shifts to funds that stay anchored on their core stage, sectors, and strengths, and say no to great-sounding deals that sit outside that strike zone.

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VC 1 Episode Transcript

Alex Clayton: 0:00

The only thing I would say that really matters at the end of the day is what is your gap revenue and cash per. If those two metrics make sense, you can create an incredible business. In the early 2000s, it was called software. We’re an on-demand company, we’re a SaaS company, we’re a cloud company, now we’re an AI company. It’s probably just going to be called software yet. I think it’s the race to the best product. I don’t think it’s the race to the bottom.

Max Altschuler: 0:20

All right, last question.

Max Altschuler: 0:21

I don’t even want to know the answer.

Max Altschuler: 0:23

Welcome to the GTM Now podcast. We’ve got a very special episode for you. It’s part of a new series that we’re doing. I’m Max Outchuler. This is Paul Urban. And we get a ton of amazing feedback from our GTM leader LPs that tell us that they really enjoy learning about all the kind of intimate details that we provide in investing. And that we should be sharing it more publicly. And so what we wanted to do with this series of podcast episodes is provide a little commentary on the markets, but also bring on some of our VC friends to give a little bit of insights into how they think about investing, how we think about investing, and how you should think about investing in your careers, whether it’s sizing up an opportunity for a company to work for or make an investment of your own. So thanks for joining us today. We’re really excited about this um slate of guests that we have coming up. And uh we’ll kick it off with me and Paul, and then we’ll get right into the show with Alex. This week’s episode, we had Alex Clayton on, a partner at Meritech, uh, old friend of mine. So uh I think you’ll see a little bit of the rapport there, but also the king of the S1s. Yep, right? So both of us have admired Alex for a long time. One of the things that he’s led is the S1 teardowns. So I think he’s done 60 or 70 of these IPO S1 teardowns, where he essentially uh when a company is IPOing, they follow their S1. It’s a detailed report of all the information that you need to decide if you’re going to invest in this company or not as a retail investor. And uh Alex does a fantastic job on his deep dives. Uh year the episode. Yeah.

Paul Irving :1:59

So what do you think? It’s a good one. Well, it’s great to have Alex back on S1 teardowns. Uh it felt like he had a hiatus when the public markets were not really participating in the exercise that he is so good at. Yeah. Um, but he’s had a few to do this year, which was great. Uh Alex was, you know, I I’m gonna break the cardinal sin here and uh overpromise uh instead of underpromising and over-deliver. But we got a great set of guests uh coming up, really excited for the series, and Alex was the perfect person to kick it off with. Not only because um, you know, we get into some of the metrics that are really important, get into, you know, the AI investing era and how they’re looking at it, the growth stage, uh, but also diving into a couple of the recent IPOs. It’s been apt if he’s you know, the the whole team at Meritech’s been busy.

Paul Irving:2:40

Yeah, it’s you know an interesting season in in tech right now. I think we’re starting to see honestly the IPO window open back up with Digma, Bigger, NetScope. There’s a couple more. Clarona, I think, was the other one. Hinch Health, Hinge Health. So we’re starting to see that open back up. Obviously, MA activity has been pretty crazy with Wiz and um Windsurf and you know some of the other ones that have been in the the news lately. But um also secondaries. Uh I think that was a big part of the episode is secondaries have never been um more on fire than they are today. It’s a huge shift that nobody’s caught about.

Paul Irving :3:16

Yeah, we we talked about it a bit at AGM in June, but it feels like of those three things, which of course it’s fantastic to have the IPO window back up, are open at least to the best of the best companies. Uh the real sign of its back to its full roar would be that your median IPOable company is able to go out, file, um, go through the process, raise capital in the public markets, and trade um, hopefully up after they end up going public. The the underappreciated or probably uh under talked about aspect of the exit economy, if you want to call that, or the exit market would be the secondary transactions. So, you know, we looked at some data that industry ventures have put together um at our AGM in June, secondaries as a vintage. So just how much capital is that uh available every single year in the secondary markets. 5x growth over the last decade. Wow. Um, and then Alex mentions it in the episode, which is even more fascinating. Uh, we’re on track right now, even though it’s been a pretty good IPO year, especially compared to the last few, to have more transaction volume on secondaries uh than you will have in the IPO primary for uh which I think it does a couple of things. I’d be really curious, Kate Your Take fund is as well. I think it changes seed investing and pre-seed investing, even some Series A investing. Um Alex talks about the challenge of a 10-year fund life cycle, which is the typical fund life. Companies are staying private longer. Uh, if you invest in a company early, they might be building and compounding in the public private markets for 12, 15, 16 years, 17 years and um some iconic cases like Stripe and and uh SpaceX. But if you’re an early investor, there’s now an available pool of capital that only seems to be growing. And I would say a growing acceptance among investors that are around the cap table, and then I think even some founding and early team members of hey, there’s gonna be people that need to get liquidity before Gail, the company reaches full maturity.

Max Altschuler: 5:10

Yeah.

Paul Irving :5:10

And now it’s open to everybody.

Paul Irving:5:12

Now that the question is, is there a need to go public? So what do we see with Stripe and Canva and uh Databricks, SpaceX, OpenAI? So this was another part of the conversation with Alex. He had some free input on, but um, I think, you know, you and I have interesting takes on this in terms of like, I don’t know if there is uh a reason to go public anymore. Um uh Alex seems to think there is, and so you’ll have to listen to the rest of the episode. He’s an optimist, he’s an optimist, but uh yeah, it’ll be interesting to see how this continues. Um, I think it’s great for early investors like us in the the seed stage and the pre-ced stages where you know we’ll get opportunities to do secondaries and some of our best company to decide. You know, do we take some off the table, return some to our investors? EPI is always nice. Do you ride, you know, with the full way? I don’t think there’s necessary that like um, okay, it’s IPO, it’s six months later, the lockup ends. Uh, you know, you you you give everybody a stock, you know, some some funds do that, right? Where it’s like, okay, now it’s up to the individuals to decide if they want to sell. So um, I think there’s kind of a lot of different ways to do it, but we’re gonna see.

Paul Irving :6:24

I I think you’re just getting optionality, which is great. It’s the maturity of the venture ecosystem or the private market ecosystem more generally, is that there’s multiple pathways. There’s not one way to do this, there’s not one way to build it correctly, there’s not one way to manage liquidity, whether you’re an angel investor or an institutional investor, a fund investor, or if you’re an employee. And that was something I was actually curious to get your take on. You’ve been an operator at some iconic companies, uh, some that have IPO’d. Uh I wonder, does that change if you’re an operator at an earlier, early growth stage company? Do you change the risk reward profile about joining a startup now that you could get liquidity on some of the shares that you’re besting over the course of your time as an ex executive or an operator at that company? Like, does that change the math at all for you? Or do you think people are still gonna make a pretty similar calculation, which is, you know, you get a chance to work at great companies. That’s the highest upsay version of company building from an operator perspective. When it hits, there’s nothing better, but not every single one of them is gonna hit. It seems like there’s more opportunity uh to cash in.

Max Altschuler: 7:26

Well, I think data absolutely changes the math. And I think what you’re seeing with open AI and and some of these other companies that are creating millionaires, decamillionaires in two, three years, maybe even less, uh and allowing people to actually participate in liquidity, yes, I think it changes it changes the math quite a bit. Um some other topics that we talked about with Alex, uh his two favorite metrics. Uh yeah, what do you think on on his two favorite metrics? So two favorite metrics had pre-seed and seed. Uh we asked him for one, he gave us two. He said can’t have one without the other. So if you have these two, it’s uh gap revenue and cash burn.

Paul Irving :8:10

Gap revenue and cash burn. No, it’s I I will say what I do like about it, uh, which which I do agree with, Alex. It’s it’s it’s the idea is if you get those two right, there’s a lot of other metrics which people focus on to talk about that will fall into place. So gap revenue being how much revenue do you actually bring in the door, not contracted, not future-looking ARR, but what is the revenue that went in the door? Uh, how are you performing sales, you know, from from a customer perspective and how much cash do they generate? And then how much cash do you burn to get there? So it’s the you know, archetype of an efficient business. You need to have one in a healthy place and hopefully you do it as efficiently as possible. The thing that I really like about it is it seems like the archetype of a business in an AI native world is taking more forms than it ever has before. And the playbook of, you know, what’s the typical range that you would see for NRR, for gross margin, uh, for growth in a software company uh five, 10 years ago is now a much broader spectra. You have companies growing faster than they ever have before. You have margins that maybe don’t look like traditional software margins for some of these companies. And so what I like about Alex’s framework is it does simplify it in the sense that if you really boil it down, what matters? Cash in the door, cash out the door, are you building an efficient business? And in a world where the aperture of what does a typical venture backed business look like is getting broader and broader, it’s nice to have something that anchors anchors the conversation for an executive team or an investor.

Max Altschuler: 9:41

Yeah, well, right now we’re seeing I think two different metrics matter a lot more, which is growth rate and uh growth rate.

Paul Irving :9:49

It turns out growth rate still matters.

Max Altschuler: 9:51

Yeah, exactly. Well, the thing is like cash burn, um, you know, with a lot of these companies that are going in a unprecedented zero to a hundred, zero to two hundred, or whatever it is, million in ARR in what, under two years? Yeah, in some cases under a year. That’s insane. Um and it’s different than traditional SaaS metrics uh have ever been. So uh I do think though, you know, what you’re seeing is a lot of these companies raising a lot of money, and it’s uh, you know, a dollar in, but it’s two out the other way. So they’re paying, you know, the model companies a lot of money, and that revenue keeps climbing, but the burn is is tough here. I think what everybody’s thinking is okay, we’ll right size that at some point, and then we’ll have you know, the revenue coming in. The margins will get better, the you know, the credits will be quite become more cost effective. So uh we’ll see where that nets out. Uh I and again, like gap revenue and cash burn. Uh, you know, I wonder if that is a relic of SaaS days, and now we’re in the AI days, and we’ll see what the the the new metric or metrics to look at.

Paul Irving :10:56

We we talk to investors about this all the time. We have you know GTM fund portfolio companies where we’re investing in the early stages, and great companies are breaking out and growing and raising future capital. I am hearing more flexibility from later stage investors than we ever have heard before on you know, uh a certain level of churn being previously completely unacceptable for a B2B software company. There seems to be a little bit more flexibility because the growth rate is also 5, 10x, anything they’d ever see before. And so I I think there’s seemingly a wider scope of what could be acceptable, with the cornerstone of it all being what you mentioned at the top. If you’re growing fast enough, um, there seems to be appetite from a capital perspective, hiring great talents, and hopefully building an economic product along the way.

Max Altschuler: 11:41

And then there’s the uh the new age-old ERR which ARR debate uh which is happening. So uh we’ll see where that reconciles too. Uh that was not a standard SaaS uh I’d say topic uh that we talked about. You had you had POCs, you had paid pilots, but you know, now you’re starting to see um experimental revenue calculated as ARR. You’re starting to see even in some cases, you see like people computing uh calculating GMV as ARR. I mean, it’s just a crazy wild less time right now with AR.

Paul Irving :12:19

So Yeah, you at the MIT did a study earlier in the summer, near the end of the summer, uh talking about how you know something close to uh up north of 90% of a lot of these experimental AI budget uh tools that were purchased and revenue that was generated by companies on the other side isn’t delivering ROI. Now, there’s a lot of, I think, debate to be had of how they’re defining that, where you draw the lines, what that means. Uh, but I agree with you. What you have is a lot of companies that are growing quickly. You don’t know exactly how much of that is experimental revenue. You don’t know how much of it is permanent budget that the company intends to have in the future. Uh the thing that you do have driving some of that, and the real question is how much ends up sticking, and then how are startups reporting it? But we are seeing more demand from a customer standpoint than I feel like we’ve seen in years. People want to try things, they’re open, they’re moving procurement cycles faster, they’re creating budget that didn’t exist before. It does make it hard to underwrite that long term. Um, because you you do have to be discerning on what’s going to stick and what’s not. But the demand is there.

Max Altschuler: 13:26

Well, you’ll have to tune into the episode that’s coming right now. Uh, we talk more about uh power laws, we talk about a little bit of rationality in the markets, talk about which IPOs we think are gonna happen or not happen in the next few years. Uh, we go deep on founder ownership and what he likes to see in an S1, especially in the founder letter uh pricing models, cost structures, uh legacy companies are re-accelerating with uh, you know, Oracle’s up 6X of 2022. Okay. Um just incredible. And then breaking down the S1 and so much more. Um it’s an action-packed episode, and you’ll have to stay till the end to find out how many maxes or too many maxes to have in one person’s life. Um, all right, let’s kick it over to the interview with Alex. How did we build the GTM fund back office? Easy. We leveraged Angelus rolling fund product for fund one, which was the perfect vehicle to scale up GTM Fund in its first iteration. This structure allowed us to build our network, add revenue leaders, and deploy capital all at the same time, which was crucial for getting early points on the board and building relationships with founders. For fund two, we transitioned to a traditional closed-end fund structure through Angelus, this time with institutional investor support. This model allowed us to be more intentional about our portfolio construction. We worked closely with the Angelus team throughout this process and they were incredible. Always there to support us and our LPs every step of the way. If you’re raising a fund or looking to migrate your fund, we highly recommend you check them out. You can do so at Angelist.com slash GTM fund. That’s Angelist.com slash GTM fund. You are. It’s just such good quality stuff for anybody who’s interested in both private and public markets. Um I find myself just kind of going into rabbit holes on a lot of the things you’re talking about, especially the S1 deep dives. But yeah, every time there’s an IPO coming, which finally feels like we’re uh we’re back. What do we got?

Max Altschuler: 15:21

Klarna, we got NetScope, Figma, Figma, Circle, Chime, Sailpoint, Service Titan was last year, late last year. So your job I heard Devon or Trip Actions might be uh coming out soon as well.

Alex Clayton: 15:34

As the uh as the S1 guy, you’re feeling like you’ve got a whole new boatload of work coming your way?

Max Altschuler: 15:39

Yeah, uh fortunately, uh we have a small but great team at Meritech who helps with a lot of that stuff. So I gotta give uh uh a shout out to my colleagues uh Tanner and Kathy and Austin, Anthony who’s into that because they’re so robust.

Alex Clayton: 15:53

I mean, they’re they’re like fancy.

Max Altschuler: 15:54

Yeah, I mean, I’ll give you some of the history. I my first job out of college I worked at in investment banking at Goldman Sachs. And the first day I was staffed on the Yelp IPO. That was in 2011. That ended up being nine months of my life. So all I did was pretty much work on that. Uh, it was a ton of work, and we started from nothing. And so we essentially, back in those days, companies, while they were sophisticated, not as sophisticated or as scaled as they are today, Yelp was under 100 million in revenue. So to ask a sub 100 million dollar revenue company to come up with all these metrics and do all this writing is a little bit of a foreign concept at the time where companies today are so much larger going public, so much more sophisticated across accounting, strategic finance, you know, sort of uh in terms of the lingo of the metrics. And so at that time, it was really the, it was really the banker’s job to do a lot of that work. So I ended up doing that. After that, when I got to, I were I ended up working on three IPOs from Lead Left to Finish, Rin Software and Gigamon. And when I was at Redpoint, I would always do write-ups for the partners around new IPOs. And people really uh enjoyed it. Uh and then when I was leaving Redpoint, I used to work a lot with Tomash Tungus, who was a very prolific blogger. And he told me, he said, Hey, Alex, why don’t you post some of those things in there? That wasn’t really my personality at the time. And uh, I took his advice and so sort of had had been doing that ever since. I think I’ve done like 60 or 70 of those by now.

Alex Clayton: 17:22

Yeah, they’re incredible. And uh, you know, you go pretty deep into, you know, the kind of the background of these IPOs. Like, what what are you looking for, I guess, as an investor, you know, when you’re digging into those? What are the most important methods to look for? What are the most important acronyms that people should know and should be watching out for? And there’s obviously, you know, rule of 40 and things like that. Is that still a thing? Is 40 the number? What, you know, what are you seeing these days?

Max Altschuler: 17:47

I’ll get to that in a moment. Yeah. Um, if 40 is the right number, because I think that’s changing, particularly uh in AI pretty dramatically. Um, but I the first thing I do is I look at the, I go to these quarterly PL and I download the table and look at the non-gap metrics. Because I think that’s the most important thing where irrespective of what your unit economics look like, your net dollar retention, your customer growth, your, you know, CAC or sales efficiency, everything is pretty much going to be consolidated into that non-gap PL just on revenue growth and then your margins and sort of operating margins. And so I think that’s everything kind of comes to that, um, even though it’s often overlooked and it’s usually on page like, you know, 150 or something of the S1. They have the annuals up front and the prospective summary, but I like to look at the quarter over quarter. Um, so that’s really what I’m looking for. I’m looking at the risk factors, I’m looking for customer concentration, I’m looking for, or I really like to read the CEO letter, which I find is really interesting. Um, the way the founder talks about the business. I also want to know is it founder led? I think that’s really important. Um a lot of times I’ve had the benefit of spending time with these businesses in the private markets. And so I do have context, but when I write, I just use things from DS1 or like their pricing page, et cetera. I don’t sort of induce any um of my own uh sort of prior, you know, knowledge of the company in these. Um, and you know, the management’s discussion analysis is an area where sort of everything is laid out in more detail. That’s where all the non-get metrics are when you think about things like net dollar retention or gross dollar retention or customer counts or customers over $10,000 or $100,000. Um, and there’s a lot of nuance. Like, I think there’s like 40 or 50 different ways that companies calculate net dollar retention. So it’s pretty complex. Everyone just thinks about, oh, it must be 125. Well, it there’s obviously an aspect to it, like most things, where some companies only calculate net dollar retention based on customers over a certain threshold. Interesting. And while that might make up 90% of your revenue, it could theoretically be overstated against other companies. Yeah. For example. But overall, um, it does kind of there are some goalposts to it. So I’m just looking at the finer details, sort of the fine print. Um, and with that, I generally have a pretty good understanding of where these things will be valued. There’s no projections in S1s. It’s only what you’ve done in the past. Um, and there’s no valuation information that’s posted initially. So um the range usually comes out a few weeks later. So I like to kind of think about what that might be when I look at the company.

Alex Clayton: 20:23

It’s interesting to hear you say actually one thing I want to pull out of that or, you know, uh pull thread on is listening to how the CEO talks about their business, yeah, these CEO letters. Um I spend time in the really early stages of, you know, most of our time at GTM fund is in, you know, precede and seed. And so um sure, you need to make sure that this is their baby. This is like really the only thing in their lives that they want to work on. They’re gonna give their all to it and they’re gonna take it the distance, and you know, there’s nothing, nothing else to really think about. They’re not thinking about exit strategy or anything like that. They’re thinking about building a business, building a company. When you read these ones that are happening in a in an IPO situation, what are you trying to deduce or parse out in there? Because you know, I’ll speak to actually uh just yesterday spoke to CEO, public company, and he’s been with the company almost 20 years now uh since founding it. And the way he talks about the company is very um much like it’s his baby still, very emotional about the company. And I’m not necessarily sure like if I’m a shareholder in that business. I like that. I want to know that uh, you know, if somebody gives you an offer you can’t refuse, you’re not gonna refuse it, right? For you know, your shareholders, uh, your fiduciary duty, your shareholders. So at a certain point, it’s kind of like, okay, on one hand, you really want them to have that passion and that like it’s my baby feeling around it, I think, at the IPO stage and beyond. But on the other hand, it’s uh they’re going to do the right thing for the shareholders. And it’s not just them anymore, you know, it’s retail investors, it’s institutions, it’s a much bigger game now, right? So what are you looking for in those, in those messages?

Max Altschuler: 21:58

I think there’s also some huge selection bias in companies that are actually going public. If you think about the type of founder, the quality of business, the tailwinds in the end market, the market timing, et cetera, the companies that are filing are like extraordinary. They’re the best of the best. So generally speaking, those founders are in it for the long term. Because I guarantee you, like at least we know from the companies that we’ve been in from up until getting public, they could have sold the company long before, done extraordinarily well financially, as well as the entire company, but they chose to go public for various reasons. And I think that’s a really important fact pattern in a lot of these businesses, particularly the ones that are founder led. And you can also see how much does the founder own of the business in the principal shareholder section. So I think that’s always interesting. Is there a number you like to see there? Um more is better.

Alex Clayton: 22:50

Yes.

Max Altschuler: 22:50

And I think it also shows just the capital efficiency of the business. Like Clavio, a couple, you know, Andrew, I’d spent some time with them in the private markets in their first equity round. And, you know, they they burned 15 million bucks to get to almost 700 million of run rate in SMB and mid-marking market automation, right? Which is incredible. Um, so clearly the way he was running the business, and he owned a significant amount uh at time of IPO, the way he was running the business was his own perspectives were deeply ingrained across the entire company culture. So there’s not a specific number. More is generally better. Um, but it also depends. Like, did you have a tough fundraising history? Were the tailwinds there for your business? They might not have been. There’s no straight line to success. Even though when a company goes public, it’s like, oh, they must have always been an incredible company.

Alex Clayton: 23:43

Yeah. Most of the time they were. But Intercom is such a good example. Yeah, right. Look at what Intercom is doing. Yeah, it went, you know, straight up and then kind of was like, uh oh. Yeah. They found figured out a second act.

Max Altschuler: 23:53

Yeah, they figured out a second act with AI. Um Owen came back as CEO, right? I think a year or two ago, and the company’s doing great. And so um, you know, I think there’s there’s many stories like that. Or look at um, you know, look at Netscope, who just filed a few weeks ago. Um, I remember spending time with Sanjay when I was at Redpoint in the Series B and Series C. And it was just a CASB cloud access broker at the time. It was a fairly small market. Most of the companies were acquired. Sanjay has willed the company, starting in their initial web in CASB and moving up to be sort of a broad security and networking platform. And it’s probably going to be an eight to ten billion dollar company. And what he’s done is absolutely incredible. Um, they’ve raised a ton of money. They’ve needed it. It’s been really expensive to do what they’ve done. But look at the way they’ve changed the business in six quarters and durable revenue growth, dramatic increases in efficiency. Um, so I think those are kind of the things that I triangulate around around where where did the business come from? What are the headwinds that they saw? How did they get out of them? And how do they win a market?

Alex Clayton: 25:01

Yeah.

Max Altschuler: 25:02

Uh, I think that tells you a good story around how the CEO is going to behave as a public company.

Alex Clayton: 25:06

Yeah. And then also, um, do you care about scrappiness? You know, the is that going to translate as a public company? And I think one of the things that’s even part of that now is like leveraging AI early in the cycle. Uh, you’re seeing, you know, uh private companies get bigger, faster with less headcount, which means less dilution. Now you’re seeing public companies kind of do the same thing. Robinhood recently uh is a great example of that, unbelievably. That was able to write, like do a big buyback, uh, you know, uh create a lot less dilution for the company, hire a lot less people to get to um, you know, a point of future growth that is, yeah, I guess unheard of or unthought of before that, right? Using AI. So you know what are you seeing in public and private markets around that? And do you are you looking for that when you’re investing as a private market investor? And then when you’re doing these S1s, is that something you’re digging into?

Max Altschuler: 26:01

It’s interesting. On the last point on the S1s, look at the evolution of how people talked about software. In the early 90s or the early 2000s, it was called software, it was mostly licensed on-prem models. Salesforce IPO 2004, it was called on people called it on-demand software before SaaS.

Alex Clayton: 26:19

Yeah.

Max Altschuler: 26:20

Then it was called SaaS. In kind of the late teens, everyone has called it cloud. And then now it’s called AI. It’s probably just going to be called software again. And so everything is evolving in that way. But how are people using AI technology? Not just what you say in the first sentence of your S1, um, used to say we’re an on-demand company, we’re a SaaS company, we’re a cloud company, now we’re an AI company. Uh and I think the, I mean, AI is undeniable. It’s sort of coming at a pace no one really expected. It will be infused into the fabric of every piece of software over the next five to ten years, although it will happen unevenly across sectors. And it’s also going to create a lot of new companies. A lot of the new businesses being started aren’t even what you would describe as kind of classic workflow companies. They’re actually creating new markets. And I think that’s the most exciting thing about new platform shifts, also the scariest. But for any cloud 1.0 or SaaS company, I think those the best businesses are not reinventing themselves per se, but evolving with having AI infused into their software. So um and the markets at a very simple level are pretty distinctly different, where a lot of the best AI companies are sort of replacing manual labor or knowledge work in some cases, where workflow software was built for users to do work or systems of record. So I think it’s um the markets are different. They’re converging in some areas, not yet converging in others. And look at what Oracle’s though.

Alex Clayton: 27:50

Yeah.

Max Altschuler: 27:50

They’re up 40% today.

Alex Clayton: 27:53

Larry passed Elon for uh Larry passed Elon as well as man of early.

Alex Clayton: 28:00

Yeah.

Max Altschuler: 28:00

Everyone thought Oracle was left for dead years ago. I mean, it was an EPS company, like EPS focused company. It wasn’t a growth company.

Alex Clayton: 28:08

Could have put a bunch of money into that in 2022, been doing it.

Max Altschuler: 28:10

Yeah, they’re up uh they’re up uh 6X since 2022. Yeah. Which is and now they’re one of the preeminent AI infrastructure providers. And so legacy companies will reinvent themselves. Um, AI native companies will do the same. I think it’s gonna be really interesting to see how it all plays out. A funny stat, um I looked at of all mid to large cap companies over the past five years, Salesforce has the most mentions of AI in the earnings transcripts, which is kind of interesting, even above marketing company maybe. No, I know. Yeah. Marketing company, but um you can’t accept it. Everyone’s talking about it. I think we’re gonna see a ton of um, it’s gonna be cool to see how I’m most excited, obviously, about all the new companies, but how are the kind of quote legacy or cloud 1.0 companies that are currently public going to reinvent themselves for the AI world? Look what Palantir has done. Um, look at Oracle. There’s a there’s a few other examples, but there aren’t a ton yet.

Alex Clayton: 29:06

Well, there’s, you know, the marketing side of that, there’s the sales side of that, there’s the product side of that. What I’m most interested in, and you know, it’s kind of goes in line with our investment in our friend Manny Medina. But what’s gonna happen with pricing and packaging? Yeah, are we gonna be still doing C pricing like Salesforce has been doing for a very long time? Uh or are we gonna move into kind of that workflow-based, outcome-based pricing, especially as this moves into kind of replacing um, you know, you’re no longer going into and saying, well, what what pro what tech products or SaaS products are you ripping out to buy this one? It’s well, which headcount are you gonna be able to replace or not need to hire? Um, and now that you have the budget, you know, for this piece of software or uh or this AI, you know, product. So what are you seeing there?

Max Altschuler: 29:53

I mean, I think there’s a couple areas, customer support as well as coding. There’s been undeniable changes in hiring threads because of AI so far. That is likely only to accelerate across industries as the products get more advanced. Think about it’s already happening, but foundational model companies, whether it’s you know OpenAI, Claude, ChatGPT, they can’t even log into applications and do work on your behalf yet. That’s not, we’re not yet there yet. And we’re already seeing higher impacts on customer support and coding. That’s all it’s it’s only going to grow. So I think the seat model will likely slowly die out. But again, it’s going to be uneven and happen at different times, but it will die out. We’re going to move towards probably like platform fees and consumption, some combination of that. I actually don’t think it’s a bad thing for software companies because you’re more closely aligning value with the customer. Yeah. Where the seat model, think about it, like in any software, there’s going to be power users, there’s it’s asymmetric in terms of the usage. Some of the seats aren’t even being used at all. You’ve seen, I mean, there’s a lot of companies out there that help businesses do audits of software that’s not used. And a lot of software is not being used. So I actually think aligning the pricing models with the customer is actually going to be better for the industry over the long term. It will create more uh alignment. So I think that aspect in AI is a really positive thing.

Alex Clayton: 31:25

Yeah. It’s a really good segue into something that’s been on my mind that we haven’t had to cross the bridge on necessarily yet, but you are on what number fund right now?

Max Altschuler: 31:36

We’re on fund eight.

Alex Clayton: 31:37

So fund eight. In let’s say the last 20 years, maybe in the early 2010s, uh the technology innovation cycles were like seven to 10 year cycles. So you’d do a Series C in a company, that company would IPO, you’d realize the value of that company, and then you’d be able to invest in a new fund, maybe two funds later, in a company that was maybe in the same space. Yep. Now those cycles are shortening to maybe three years, two years, one year. So how do you invest in a company in a space and then a fund later you might see another company that’s in that space that may be potentially competitive to that company invested in a fund ago, but you’re realizing like wow, I don’t want to miss out on this kind of like new version of this, right? Um and maybe the new version is is an AI play and it’s outcome-based pricing and the old one was a seat-based pricing uh company. Yep. How do you manage that at a company where you have multiple funds and you’re investing across I guess multiple stages of growth and uh across multiple years and you don’t want to miss out on the latest and greatest, right? But you still want to be founder friendly and whatever else.

Max Altschuler: 32:51

Yeah, a few things on that. First of all, um we don’t want to be investing with conflicting dollars. Yeah. Right. It just doesn’t make sense from a fund perspective. We keep it pretty simple. We just take a founder first mentality to this. If something is too close for comfort, we for the founders we’re not going to press it. And so particularly if we’re you know on the board of some of two companies, that’s not something we would want to do. I would say the lines are blurring on that a little bit in this day and age as the venture industry is becoming much more industrialized. Yeah. Where some firms are of the scale of which you know a partner might be working at the same firm but in a different fund that doesn’t even have information rights. It’s almost like two, it’s it’s the same name of the firm, but it’s two different entities. And so I think there’s a lot of nuance to it now. But yeah, we we do not try to invest in competing companies. And the interesting part a lot of these new technologies, they’re new markets. Or it’s a completely different way to solve the same problem. So in that case, there might be a new buyer there’s a new pricing model and you’re not actually competing with the current at the same time any company that we’re in, we’re encouraging them if there are upstart startup competitors in the AI world, we want them to aggressively build out those features and functionality to compete too. So um but we yeah we don’t we won’t invest in uh competitors generally speaking well now more than ever it’s a power law game. Yeah.

Alex Clayton: 34:20

Right. So I think that’s probably something that’s got to be on your minds all the time. So I wonder, you know, in a uh again we’re we don’t invest at the same stage as you’re on fund, you know, going on to fund three. Yeah. A little bit different. We haven’t experienced this problem. I can imagine you know there’s certainly situations where you know this is going to be the winner. Do we have to do an audit of the 20 years of companies that we’ve invested in previously and understand, okay, can we make this investment? Do we don’t want to miss out on this one company as a flight to quality and there’s, you know, it’s power law more than more than ever before.

Max Altschuler: 34:55

So how are you thinking about you know the power law game right now and yeah the state of venture capital that we’re in yeah I think there’s so many um trends going on just to kind of name a few there’s more capital than ever in the private markets. That’s one. And so a company that used to go public at five billion dollars in market cap or even one billion dollars in market cap when I was working on IPOs at Goldman we would spend nine months a two week roadshow to raise a hundred million dollars that’s now could be a seed round for a private company. So capital has shifted companies are then staying private longer. You look at sort of the age of companies before they go public because they’re getting larger and larger the thought that there could be a company like Databricks you know raising money to $100 billion in the private markets 10 years ago people would say you’re crazy.

Alex Clayton: 35:49

Yeah.

Max Altschuler: 35:49

Honestly, I think um so that’s changing it’s the stripe it’s yeah I mean Amazon went public at you know I think a few hundred million in market cap yeah now it’s trillions of dollars. So a lot of that value appreciation is now happened in the private markets. So if you’re a capital allocator, you want to be a part of that what where does the most value accrue to any what is the single most important value uh factor in value creation? Growth. AI and private technology is the fastest growth sector of the world, broadly speaking. So all those dollars are flowing in fund lifes are going to extend dramatically the idea of the 10 year fund is becoming less likely given how long companies are choosing to stay private. Although liquidity instead of an IPO is more and more happening through secondary transactions about that.

Alex Clayton: 36:41

Maybe we’ll go into that next but how you’re participating in secondaries there’s both the buying and the selling side of that being aware of you know is my uh investment wildly overvalued on the secondary markets and I should be selling now or um hey can we get into this at a really good deal and buy more of this company on secondary markets.

Max Altschuler: 36:58

But continue I’ll cover the power law dynamic. We’re actually just looking at some of this because last year at our annual meeting we talked a lot about this factor of there’s like 1500 unicorns. The vast majority of them won’t create value, unfortunately but the very few that are the largest will create more value than industry has ever seen. We talked about this concept last year at our annual meeting that has only radically accelerated where you have companies like OpenAI, Anthropic, Stripe raising Databricks at like hundreds of billions of dollars in valuation and they’re consuming more and more of the venture funding. And that was like more capital than all of the largest companies rounds in a single year for like 10 years. Yeah. So it’s just you know it’s it’s astounding um and the opportunity is huge. And so it’s not that no one cares about the average company anymore. It’s just there’s no real public market sentiment for it right now. Or I guess you know if no one cares it implies that but um that’s just not what people are shooting for. They’re shooting for grand slams. Base hits don’t matter anymore in this end market. And so back to your point on the secondary markets would we consider selling we tend to be later stage investors. So we’re coming in post product market fit companies are in the in revenue they’re generally doing in the low millions of revenue and that’s our entry point and because of this outlier effect when we’re in a winner we want to keep investing yeah more and more versus pairing back. So um we’re willing to take the risk with exceptional founders exceptional end markets where we’re in a market leader to hold on until the approach exit generally speaking I’m hypothetically this but like let’s say fund three was in Databricks’s you know Series B.

Alex Clayton: 38:58

Yeah. Are you taking anything off the table at a $50 or $100 billion valuation? I mean like you can return the fund and then some and still probably keep half your position, right? So you know do you do you look at that and say like hey is a good time for DPI like regardless if we think this is going to be a half you know half a trillion dollar company um and then on the flip side I guess you know second question is well are you taking advantage of the secondary markets to buy more into some of these companies? Like if you’re continuing to put money in the flock safety and framework and things like that, maybe there’s opportunities where company doesn’t want to take on more dilution but it’s a good opportunity to get some people out that have been with the company for five or seven years and you can do $20 million worth of secondary for you know employees and get more access.

Max Altschuler: 39:42

We do tenders all the time for companies and so that’s a very common um some of our most exciting investments we only bought secondary data dollar data for example uh Tableau software they didn’t need any money and so we led a tender offer. But back to your point if we’re in a 2003 fund and it’s today and the fund is 22 years old and you know Kenley we might have already sold some Databricks at that point. But I think that’s those are questions that will be asked going forward versus today because really this cycle kind of changed in the past few years where this like capital kind of title wave came into the private markets. And so I think uh more and I think there was uh this year there’s been more exits through secondary than through IPOs for the first time ever. And will that accelerate? Probably so given the stage that we’re at we’d probably be the ones buying a lot of that secondary. Yeah. Um but if something were to happen like can never say never I guess yeah on the sell side.

Alex Clayton: 40:45

And there’s certainly going to be I think plenty of seed stage funds that are looking for DPI companies do really well. It’s like hey this this is plenty we can take half our position three quarters our position off here sell it to a fund like y’all who are buyers at that stage like I think there’s a lot of opportunities in the marketplace for both sides when the companies are going this big this fast and it’s different than 2021. I was having this conversation with somebody the other day but you know you’d see a company raise three rounds of funding in one year and it’s like well they went from like one to three to ten million in revenue like this is it’s crazy that they’re raising like this but now you’re seeing companies go from zero to a hundred million in a year. Oh yeah all right they are getting a $10 billion valuation or three or five billion dollar valuation at least it’s at least there’s the revenue there to back it up.

Max Altschuler: 41:30

Yeah you know companies are growing so much faster now. Yeah even in our portfolio that are more AI but I think it goes back to the markets are just kind of fundamentally different the market structure where if you’re selling a software product to a mid-market company that has a thousand employees, their software budget is sort of like anywhere from five to eight percent of revenue, roughly speaking, but 70% of their costs are headcount related. So you think about the AI markets, it’s just it’s 10x bigger. And that’s why I think we’re seeing in the private markets this concept of the triple triple double double doesn’t really make sense anymore for the best companies. Yeah. We’re seeing many businesses go zero to 100 million, zero to 50 million, zero to hundred million within 12 months because the TAM and the demand is so, so much bigger. Also there’s this other concept of a ton of experimentation happening. Yeah. Like everyone’s excited about AI with very good reason by the way. And so everyone wants to buy these products. Every Fortune 500 company CEO has told the market they’re going to have an AI story that filters down to C-suite, to VPs to directors that’s saying we need to AI ify our companies and so what does that mean? We need to go experiment with software. Who’s selling all this software? It’s private venture backed companies and so they are seeing explosive growth. OpenAI is what 800 million MAUs I mean it’s like insane yeah it’s like nothing we’ve ever seen before so I think the um the excitement around AI is there. The budgets are there um and that that’s also a reason why these companies are growing so quickly but also the markets are just so much bigger.

Alex Clayton: 43:11

Well do you worry at all that we’re going to have a 2022 style reckoning where you know markets turn a little bit maybe it’s next year maybe it’s the year after but you know uh CFOs, uh C level executives all say, okay, we’ve got this sprawl again that happened in 20 at the end of 2021. We have you know 70 different software for each function in the business and we got to cut these down to the need to have all haves only like do you think that that happens at some point again or um you know are we really in a period where we’re replacing so much labor and it’s you know so efficient and you say it’s experimental so that’s my worry is that you know we we have all these organizations that experiment with a bunch of this and then they say okay let’s get back to reality here.

Max Altschuler: 44:00

Let’s consolidate let’s make sure we’re being efficient and you know we the the winners have kind of sifted out we know you know we want to use hey there’s a lot of froth in any new platform shift I’m not gonna argue that um 2022 wasn’t that far away right the software recession was real yep although the best companies have bounced back dramatically off the lows that aren’t even in AI. I think um to your question there’s a lot of cognitive dissonance in the market where it’s obvious we’re in the bubble but that’s okay. It doesn’t mean that the largest companies ever in technology won’t be created because I think that fact is also true. And so the market is really grappling with that concept and I do think the dust will settle here’s the thing I don’t it doesn’t matter what platform shift you are whether it was the internet the semiconductor or you know clean tech or SaaS the vast majority of companies don’t make it um irrespective of the platform shift. Will that be similar in AI? Likely so uh but there’s huge excitement around it for all the reasons we discussed so I think there’s going to be um how do you as an investor manage those two facts of being in a bubble but not wanting to miss or not be a part of the largest technology companies ever. Yeah. And it just comes down to what strategy you’re employing at your fund. And so um I’m not sure that there’s going to be like a AI recession because of the fact that the markets are so big and the technology is getting cheaper while the capabilities are improving and there’s such high demand for this technology. But not all these companies are going to be successful. Yeah. But but in any given category like there’s probably going to be some monster companies and there already have been created in just a few years. Yeah. We’re just getting started. Yeah. Like I said you can’t even use an AI lab to log into third party software yet. Yeah. Think about if I told you hey Max I’ve got someone who I’ve I’ve got an agent that would book this entire event here today for you on one simple prompt and you didn’t have to do ever anything. You probably pay a lot of money for that. Yeah. So there’s millions of those use cases across our daily lives, across existing technology workflows that haven’t even been tapped yet.

Alex Clayton: 46:24

And the cogs the cogs are only, yeah, everything’s getting cheaper, margins are getting better right over time. Yes there’s kind of a little bit of a race to the bottom between a lot of these uh I think it’s the race to the best product.

Max Altschuler: 46:35

I don’t think it’s the race to the bottom. Okay. Yeah. Explain that a little bit where I think there’s this fear that oh if everyone just does the same thing um it’ll be a race to the bottom. My old boss at Spark Capital would ask a question is it a toaster market? You’ve got a toaster everyone has a toaster you don’t really care which kind of toaster you buy you probably buy it at Costco or Walmart or Target. They’re all kind of the same they plug in they have various different features they’re all like 20 or 30 bucks. Yeah. No one really cares. But it’s a multi-billion dollar market and there’s companies that make a lot of money selling toasters. Being a venture capitalist, we’re not in the business of investing in commodity products. We want to be in the best product. And I think this concept of will it be a race to the bottom is just another way of asking will it be a toaster market where it’ll be big but no one will really win or be super valuable or trade well because it’s all commoditized. We take the perspective that the best companies and the best founders will figure out a way to create an exponentially better product experience in their end market that they will be extremely valuable. We’ve seen that time and time again in other technology markets where it is very easy to say there’s 20 competitors, there’s not likely going to be a lot of value creation. That might be true, but what about the one company and special founder who had a unique approach to the market that had the best product and they might create they might take most of the market share and create a create a company that’s worth tens of billions of dollars. It’s our job to figure out which side of the spectrum that’s on. So I think the only race to the bottom are going to be in markets that weren’t all that exciting to begin with.

Alex Clayton: 48:21

Yeah. Okay.

Max Altschuler: 48:22

So you don’t see it like cloud where it’s like oh I can use Azure I can use GCP I could use AWS you know well you still could but those three companies are $260 billion of revenue run rate growing accelerating growth at 30% with 20 to 30% operating margins. And so they’re pretty great businesses. Yeah yeah well I mean there’s still going to be great like right there’s Grok and OpenAI and Anthropic and meta and all these and uh but I don’t think I don’t think the race to the bottom on price will be the reason that a company is not successful. I think that’s the output of the market structure not being as exciting or it’s an end category that the buyer doesn’t really care about like if someone goes to build a new type of toaster, will it really be s like do people really care about a new toaster?

Alex Clayton: 49:16

Maybe well I think the question on a lot of people’s minds is like does it get to a point where a bunch of these companies that are growing you know zero to a hundred million or zero to two hundred million in like such rapid pace, when you look under the the hood a little bit, it’s like okay well the all that money is just being passed through to the LM, right? So it’s like at what point does that become affordable enough for those companies to actually start making money on top of that layer where it’s a dollar in two out instead of every dollar in you’re paying two you know I think that’s gonna be one of the most interesting fact patterns of how this market will develop is if you’re in an end market where the only way you can grow is by giving a customer something that’s that you’re paying $2 for for a dollar, that’s not sustainable.

Max Altschuler: 50:09

Obviously that’s not going to work. And so the founders that are or the companies that are doing that, do the founders take the perspective of I’m gonna parallel process growth while building out my product suite so I can actually charge $5, even though I’m paying two over time. There’s been some companies that have proven that already in very impressive ways. But in any new market environment it’s a land grab particularly with the amount of capital that’s flowing in that I don’t really blame founders for wanting to you know accept a dollar for something they’re paying two for for incredible growth if people are willing to give them a lot of money for it. It’s just sort of basic capitalism. So I think the the the thing will be how does that evolve over time? I still think the best founders will figure it out. I mean we we have had uh you know we’ve had examples of companies where we invested in where we didn’t even know what the gross profit was because it was so negative. Yeah the company wasn’t even really sure but we knew they had a great founder and it was a great end market that had some unique tailwinds behind it. And now they have incredible gross margins and we don’t even really talk about it anymore. Yeah. So I think um that will happen in AI but that’s not to say there’s not a lot of froth in the ecosystem too, right? Like like I said there they’re the the kind of what we talked about the cognitive dissonance of being in a bubble versus the largest companies tech in technology will ever be created now is like that’s a tough thing to grapple with and on the margin you see a lot of these things come up.

Alex Clayton: 51:43

All right so you know I worked with Meritech at Outreach I know you guys are pretty cutting edge. What how are you using AI in your day to day right now and at the fund?

Max Altschuler: 51:52

Yeah we’re doing a lot of experimentation um we’re using um my favorite products are whisperflow and is it’s probably the one I used to speech to text which is speech to text. It’s an app where you just if you’re on a Mac you just hit FN FN and you speak and wherever your cursor is it will input the text intelligently and it saves up your dictionary over time. So I think that um it’s one of my favorite consumer products where I can send a long email from my phone or computer without typing. It’s pretty awesome. And the Siri and those other like it’s really an 80-20 like the last mile of speech detectation is really hard. And I think packaging that up in a seamless consumer experience is really hard and Whisperflow has done a really good job at that Siri’s really dropped the ball.

Alex Clayton: 52:40

I mean we can go probably on an extreme tangent on uh Apple’s AI or lack thereof strategy but I mean it’s it’s crazy every time I’ll say my wife’s name Ashley and it’ll say it they’ll spell it the wrong way, which is like not the most common way to spell the name and also like nowhere in my phone. So you’d think that it would know to like see how it’s spelled in my phone and just spell it that way or at least spell it the most common way. But no it’ll go like A-S-H-L-E-I-G-H yeah I don’t know yeah but with so Whisperflow fixes a lot of this they do they do yeah it’s it’s pretty awesome you should give it a try yeah and I think Apple um I’m probably a little bit more bullish on Apple even though they seemingly have maybe I don’t know maybe they’ve dropped the ball if you just read about their perspective I mean I think they’re grounded in consumer privacy.

Max Altschuler: 53:29

So interesting they actually can’t train on you because they want to protect your data. Interesting. And given how widespread Apple devices are used, I think if they open the spigots on using people’s data and training on people’s data, what could that lead to? I think there’s a lot of fear around that and Apple’s not a company who takes a ton of risk, right? They’ve generally done buybacks.

Alex Clayton: 53:54

Yeah.

Max Altschuler: 53:54

They don’t make huge acquisitions.

Alex Clayton: 53:56

Yeah.

Max Altschuler: 53:57

So there’s a bit of a cultural element. They’re probably waiting. I mean I don’t I I don’t have any inside information. I don’t buy it safe. But yeah they they they play it safe and but no one’s getting rid of an Apple iPhone anytime soon. And I don’t think people are going to get rid of an iPhone for an open AI appended. They might also buy that one yeah but I don’t think they’re getting rid of an iPhone. And it goes back to another point which is this concept of software is dead. Every single AI company we meet also has an app. It’s still software. Yeah. Goes back to sort of the you know history doesn’t repeat itself at rhymes. But anyway we’re also using a lot of the foundational models for various tasks and I think like if you’re transcribing a PL into Excel or copying and pasting or doing a lot of these like small really uh minutia tasks I think that we’re finally getting to the point where there’s some really product products to help speed that up. We’re starting there. I think um AI is never going to make investment decisions at least not for the foreseeable future. If it did I think that um it would just turn into the ETF market. Yeah. Which which maybe that’s where we’re going. But uh it’s still dramatically driven by founder relationships.

Alex Clayton: 55:14

And are you using anything like uh harmonic or crunch base or things like that?

Max Altschuler: 55:18

Yeah we use and there’s their AI we use a variety of those tools that are really good. I’d say they’re just for research. For research yeah and like tracking company like there’s more companies than ever now and we’re a small team. So Meritech there’s only 11 investors for a $1.4 billion fund and there’s a lot to do with very few people. So we’re definitely leaning into how do we become more efficient using AI. We only have 23 full-time employees yeah at the firm. Wow um and all of us are experimenting and using in our in our day to day uh and trying to push the boundaries there.

Alex Clayton: 55:52

We built our own internal tool uh we called it Xval stands for exponential value because it’s a little put on top of our flywheel it’s like a one plus one equals three tech thing so we’re able to take the community the media and the fund and uh essentially maximize every aspect of it by layering on this our own like custom GPT so we can type in there like hey surface all the employees surface all of our LPs that have experience with sales compensation planning and it’ll surface all the LPs. It’ll give a little dossier on each one of them and if we have a portfolio company that asks us for that type of help we can just copy and paste it into the email and send it and they’ll get an email like hey here are the 10 people we can introduce you to here’s a little bit about them and oh by the way here’s like you know links to three different podcasts or newsletters that we’ve produced that’ll talk more about sales compensation planning.

Max Altschuler: 56:42

Very cool.

Alex Clayton: 56:43

That’s so you’ve got your own kind of glean nice man oh very exactly exactly and it’s trained on all of our stuff and um so that was that was cool. We use harmonic a couple other couple other things as well I mean obviously all of the software companies now have AI components like Air Table and everything else has got souped up but um I’m excited where the market is going for all this stuff but yeah yeah speaking of make our jobs a lot more hopefully easier but uh yeah harder it’s it’s always getting harder. Well speaking of where the market’s going yeah where is the market going? Where do you where do you see the next frontier being you know we’re in the first inning of AI.

Max Altschuler: 57:17

Yeah but what is what are what is the rest of the 2020s look like you think I think there are factors beyond just the technology markets that will influence that whether it’s geopolitical risk risk of of war uh other instabilities around the world um but if we’re just talking about tech I’m extremely bullish I do think the like I said that AI wave and the cognitive dissonance around yeah we might be in a bubble or we probably are in a bubble but the largest companies that have ever been created will probably be created in this in this cycle. So I’m uh myself and Meritech our team we’re we’re uh we’re incredibly bullish about the future yeah you have to be an optimist if you’re in this industry.

Alex Clayton: 58:03

You have to yeah right and what’s the what’s the saying it’s like optimists uh pessimists sound smart but optimists make money uh some variation of I’ve heard that one uh or you know what what is our job you know you could argue are you paid to see the future clearly or paid you know to or are you paid to see the present clearly or paid to see the future?

Max Altschuler: 58:24

Yeah you could argue for both yeah exactly um so but yeah we’re uh we’re bullish great where are you getting um I’d say most of your learnings from are you reading books you listen to podcasts or are there people that you’re following on Twitter that you you’re soaking up a ton of knowledge from and to me uh recently two of my favorite followers are you and then uh Jammin Ball who does the great writers for episode judgment um I I you know I just try to soak up as much information as I can uh Twitter’s been super helpful yeah obviously there’s quite a few podcasts uh out now that are uh very relevant but well what are you what are you getting information from yeah I a bunch of different places I find um by the way Jamin’s awesome we we’re on the Stanford tennis team together oh wow so I know him very well known for them good friends uh he’s great um I’d say I think X is good for sentiment on certain things um that’s really helpful or the summarization of things on X. Uh I like to read I like to read sort of uh random kind of market books to sort of because when you’re in this world of everything goes up not everything goes up but everything is exciting. We’re in a huge platform shift how do you stay grounded in helping history frame what’s going to happen in the future um recent book uh that I love is called The Price of Time by Edward Chancellor just talks about the history of interest which is really the history of markets and you look at asset bubbles throughout history and why they were started and how they were started and it really talked about the um the advent of the central bank controlling interest rates over time and the history of interest Uh it would just really fascinating book about market cycles as well. Um, and then meeting with founders. I think the smartest people in technology are founders. Undoubtedly so, and and their teams. And so I feel really fortunate that I get to spend my time and my day meeting with founders who are really shaping the future of not just technology, but how, you know, given the breadth of how technology impacts the world, really shaping the future of the world. So um as an investor, that’s that’s where I think you can learn the most.

Alex Clayton: 1:00:37

It’s funny you say that. I actually posted on LinkedIn today. I’m not sure if you saw it, but uh Oh, cool. I I think one of the most fun things about our job and really what compounds our flywheel even more is um oftentimes we’ll bring our best practices and um, you know, our our GTM leaders and everything to support our portfolio company. Yes. And they’re the sharpest, fastest moving, um, like tweakers and tinkers of everything that you end up working with are these the spounders you’re invested in. And so they’ll take what we give them from like a best practice or a playbook, and then they’ll come up with something even better. And then we’ll be able to take that and then replicate that across our portfolio. So it actually makes us better at our job. Uh and it’s just it’s consistent like that. Um, you know, we’re working on some really cool stuff with paid right now. Manny’s coming, and just some of the things we’re doing there on self-serve to uh kind of enterprise sales allows us to really like you know get in the weeds with them on it, bring kind of our best practices to the table, but then also when we are able to see what they do with it, you know, take that back and repackage that and duplicate that across the pool flow. So that’s very cool.

Max Altschuler: 1:01:45

Yeah, good uh very pressing timing. I I I couldn’t agree more. I mean, it’s uh think about it, you have to run a company, yeah, and everything that’s involved in doing that while also influencing and really being the uh the leading uh product, the product leader at a company, as well as the leading go-to-market leader, as well as a CEO. You know, there’s it’s um it’s a really difficult job. Uh, have a lot of respect for people who who who go and do it. Uh and yeah, it’s it’s it’s fun to learn from them. Yeah. Great. What’s the signal no one’s watching for right now that you’re watching for? I think it’s very easy in today’s world of AI where companies are growing faster than ever, have different types of metrics to get lost in the patterns of Cloud 1.0. Not in a bad way. History um, you know, doesn’t repeat itself. It tends to rhyme, right? So you think, well, if companies grew this way, then they must look like this in the AI native world to be successful. And I think the finding the balance between those two fact patterns of just being principled about what do you think is a great business and a great founder with great tailwinds is really important. And I think think about how fast this AI world is moving. What is the most important thing as an investor that is the hardest thing to do is focus. There’s so many things you could be doing, chasing on a daily basis. There’s so many companies, there’s so many people you could be meeting, there’s so many new products coming out every single day. If you don’t stay focused on what you’re really good at and the core of what you do, I think it’s very easy to be distracted. So I think it’s actually um the hardest thing to do in market environments like this is to stay focused. And that’s something that we are really aggressively trying to do.

Alex Clayton: 1:03:33

So early stages, seed series A, if a founder could only obsess over one metric, Lord Big Ross.

Max Altschuler: 1:03:41

One is impossible without the other. Okay. But I’ll how about two? Let’s get two. The only thing I would say that really matters at the end of the day is what is your gap revenue and cash burn. With those two metrics, if those two metrics make sense, you can create an incredible business. I wouldn’t worry about if those are the only two, wouldn’t worry about NDR, I wouldn’t worry about margins because it will be captured in cash burn. If you just think about how to grow your business and how to do it efficiently, uh, everything else will take care of itself. Of course, easier said than done. But if given you only had one or two metrics to track, those would be the ones I do.

Alex Clayton: 1:04:17

And you like that for C and Series A only, or does that apply to all status?

Max Altschuler: 1:04:22

I don’t see how it can’t apply to all stages. I guess if I ask myself that question, because at some point those metrics are really going to be all the ones that matter. And so why not start focusing on them early? I understand there’s other leading indicators of the business that could be more important, but at the end of the day, it’s all about what is the value, what is the product that you’re offering and the associated value that your customer is willing to give you in revenue. And can you do that sustainably over time? It captures all of those things. I feel very fortunate.

Alex Clayton: 1:04:56

You guys have this um is it the the entire culture over there of athletes turned venture capitalists? Because he was a lacrosse guy and you were tennis. That’s true. Yeah. Alex Kernan also was a baseball player at USC. Oh, wow. Yeah. So that’s that’s how they recruited.

Max Altschuler: 1:05:10

It didn’t, it worked out that way. Uh I think athletics growing up is a really uh helpful thing. It teaches you how to prepare, teaches you how to win, and also how to lose and how to get better. So I think those are really important attributes that you know can be applied to the to the business world. So it didn’t happen um purposefully, but uh happened by chance, I guess.

Alex Clayton: 1:05:31

I think it does teach you accountability, extreme ownership, determination. I mean, there’s so much that comes out of it from playing at a competitive level um at the earliest ages.

Max Altschuler: 1:05:41

So 100% agree.

Alex Clayton: 1:05:42

Yeah. Do you think, if you’re a betting man, uh that Figma, Klarna, NetScope, the IPOs that are happening right now, are they above or below their IPO price this time next year?

Alex Clayton: 1:05:57

It depends on the company. But I would say the companies that you mentioned, I think they’re based on what I know, probably above.

Max Altschuler: 1:07:50

All right, last question. Who’s your favorite Max from Long Island? Oh, well, now I don’t even want to know the answer. I’m actually I’m actually worried it’s not. That isn’t easy to hip out, you know.

Max Altschuler: 1:08:00

Yeah.

Alex Clayton: 1:08:01

Hope you enjoyed this episode. We’d love to hear your feedback on this new special series. It was a lot of fun. We’ve got some great uh guests lined up for future episodes. So check out the fund, a GTM fund, and more of our content at GTM Now. If you like this episode, definitely subscribe to our YouTube channel, GTM Now. We have a lot more amazing guests coming and can’t miss them.

Picture of Sophie Buonassisi

Sophie Buonassisi

Sophie Buonassisi is the SVP of Marketing at media company GTMnow and its venture firm, GTMfund. She oversees all aspects of media, marketing, and community engagement. Sophie leads the GTMnow editorial team, producing content exploring the behind the scenes on the go-to-market strategies responsible for companies’ growth. GTMnow highlights the strategies, along with the stories from the top 1% of GTM executives, VCs, and founders behind the strategies and companies.

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