Brought to you by: AngelList
How did we build the GTMfund back office? Easy!
We leveraged AngelList’s Rolling Fund product for Fund I, which was the perfect vehicle to scale up GTMfund in its first iteration. This structure allowed us to build our network, and add revenue leaders while we raised and deployed capital simultaneously, which was crucial for getting early points on the board and building relationships with founders.
For Fund II, we transitioned to a traditional closed-end fund structure through AngelList. This time with institutional investor support. This model allowed us to be more intentional about our portfolio construction. We worked closely with the AngelList 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 are looking to migrate your fund, we highly recommend you check them out. You can do so at www.angellist.com/gtmfund.
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
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Why GAAP revenue and cash burn are the two metrics that quietly govern everything.
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How AI is changing growth rates, margins, and what “good” looks like in SaaS.
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The rise of secondaries, and why they now rival or exceed IPO volume.
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How to read an S-1 like a pro (and what Alex looks for first).
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Founder ownership, fund lifecycles, and how long companies really stay private.
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Why power laws in venture are getting even steeper in the AI era.
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How AI is reshaping pricing models from seats to usage and outcomes.
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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.
Share your takeaways!
Follow Alex Clayton
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LinkedIn: https://www.linkedin.com/in/aclayton
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X (Twitter): https://x.com/afc
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Meritech profile: https://www.meritechcapital.com/team/alex-clayton
Recommended books
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The Price of Time: The Real Story of Interest by Edward Chancellor
Alex recommends this as a way to understand the history of interest rates, bubbles, and how “cheap money” distorts markets (crucial context for today’s AI and venture environment).
Referenced
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Meritech Capital: https://www.meritechcapital.com
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Meritech Insights (Alex’s S-1 breakdowns and posts): https://www.meritechcapital.com/blog
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GTMfund: https://gtmfund.com
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GTMnow: https://gtmnow.com
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OpenAI: https://openai.com
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Stripe: https://stripe.com
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Databricks: https://www.databricks.com
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SpaceX: https://www.spacex.com
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Canva: https://www.canva.com
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Oracle: https://www.oracle.com
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Salesforce: https://www.salesforce.com
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Intercom: https://www.intercom.com
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Netskope: https://www.netskope.com
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Figma: https://www.figma.com
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Klarna: https://www.klarna.com
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Hinge Health: https://www.hingehealth.com
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Wiz: https://www.wiz.io
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Meritech Capital: https://www.meritechcapital.com
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ServiceTitan: https://www.servicetitan.com
Follow Max Altschuler (Host)
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X (Twitter): https://x.com/HackItMax
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Newsletter:
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Each week, we uncover the pivotal moments, bold decisions, and go-to-market strategies that turn ideas into breakout companies.
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