20VC · 2025-11-10 · 86 min

Benchmark's GP, Everett Randle on Why Mega Funds Will Not Produce Good Returns

Harry StebbingsEverett Randle

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TL;DR

AI application economics break SaaS’s familiar 80%-margin scorecard. Randle argues investors should underwrite terminal 5–7-year margins, gross-profit multiples, and absolute gross profit per customer: an AI product at 50% margin can be superior to SaaS at 75% if it produces $500,000 versus $200,000 of gross profit. His blunt call: “We should not be placing that much emphasis on margins today,” especially because high inference COGS can reflect genuine AI usage. AWS is his analogy—lower margins can coexist with much larger customer spend.
Coding is already a “golden category,” even if Cursor’s market share keeps falling. Randle estimates code generation grew from essentially zero to $6–7 billion of ARR in roughly 2.5 years and could add another $4–5 billion this year; Cursor may have fallen from roughly 80% share to 25–30%, yet still be addressing a vastly larger market. Products with the most usage—Cursor, Claude Code and Codex among them—also improve fastest through deployment and can “leave everybody in the dust.” But growth is real only when an app clears the labs’ baseline: Jasper grew rapidly and then shrank when GPT-4 made its output look too similar to ChatGPT’s $20 offering, recovering only through more differentiated workflow software.
At the latest stated prices, Randle would take OpenAI at $500 billion over Anthropic at $350 billion. Anthropic remains slightly ahead in coding and probably B2B commercialization, while OpenAI has recovered ground with Codex; the decisive asset is ChatGPT, whose growth trajectory Randle finds almost impossible to stop. Having passed on OpenAI at $32 billion over nonprofit structure and dilution concerns, he now predicts it could be a trillion-dollar company next year: “I missed the forest for the trees.”
Benchmark’s small fund is designed to maximize multiples, not win every mega-round. Randle says the five best investments in its last fund, marked at last-round prices, stand at roughly one 60x, two 30xs and two 20xs—returns no post-ChatGPT OpenAI round matches. Benchmark therefore need not buy every lab financing; its two north stars are being the founder’s closest, highest-ROI partner and generating the highest money-on-money return in an LP’s venture portfolio. A customary 20% ownership target is an input rather than the goal: lower ownership in Mercor can still produce exceptional returns if Benchmark remains its most consequential venture partner.
Mega-funds may make immense absolute profits while still failing venture’s return test. Randle’s argument is structural: “You ship your fund size,” so $7–10 billion vehicles must write enormous checks, and those checks inevitably become the main product and organizational priority. He doubts their managers can credibly promise 5x net across the relevant basket of funds; Harry’s pushback is that unprecedented outcomes may still rescue the model, which Randle accepts in dollars but not necessarily in multiples. Tiger may finish far better than its reputation suggests, given positions in Databricks and OpenAI and preferred-stock protections on some losers, but Randle still expects many AI companies to go to zero or fall 90% while rare winners compound for decades.
AI’s moat remains technology, not merely distribution. Distribution earns a company the opportunity to build, but Randle says exceptional AI products require scarce talent, nuanced model pipelines and workflow design—not “bringing in the OpenAI API” beside a text box. The labs establish a $20 or $200-per-month experience baseline, so application companies charging more must create deeply differentiated workflow value that survives the next model release.
Commodity AI infrastructure can overwhelm quality concerns. Randle changed his mind on AI clouds, initially dismissing CoreWeave as a commodity middleman before astronomical inference demand overwhelmed that objection. He cited CoreWeave at roughly $60 billion and Nebius at roughly $30 billion in public-market value, with more than $100 billion across the public sector. He still expects CoreWeave and similar companies could eventually fall 70%, but says demand can justify investing with momentum.
Price matters only against the company’s own upside. Randle ranks people, product, market: people are the upstream engine, product is the strongest evidence of their quality, and market is most fungible because companies can pivot. SpaceX at $150 billion, Rippling at a $250 million Series A and Figma at $400 million on $4 million of ARR taught him to remove intimidating zeros and underwrite TAM, competitive position and upside rather than market convention. Models provide a base-rate yardstick—perhaps the path others underwrite for a 3–5x—but detailed forecasts become false precision; the real test is whether the qualitative view says the company will “absolutely smoke these projections.”
Benchmark’s greatest risk is stasis, not one missed cycle. Randle calls stasis the biggest threat over the next two decades: Benchmark must evolve with the asset class while preserving its two north stars and continuing to reach the very best founders. His long-run optimism rests on AI lifting GDP per capita as population growth slows—“continuing growing the pie” as the foundation for a functional, less zero-sum society.

Digest · the substance, structured for research

1. Great investors turn process into conviction

Mary Meeker’s quantitative reputation obscures what Randle considers her real gift: she is “the most qualitative investor” he has worked with. Reading a company’s historical and projected numbers “like she’s reading the Matrix,” she sees an 8–10-year narrative—for DoorDash, not an abstract growth rate but perhaps 20% of households ordering monthly.
The lesson was to use numbers to drive an investment story rather than become trapped in the model. Meeker’s sequential data gives her a way to visualize what a company becomes, joining quantitative discipline to a qualitative judgment about adoption, behavior and market position.
Peter Thiel’s genius, in Randle’s telling, appears as much in institutional design as stock-picking. Founders Fund employees could invest personally beside the fund, creating a concealed conviction test: if an investor would rather keep their money in the S&P, “why would we give our LPs this allocation?” Younger staff sometimes used unsecured debt lines to participate.
Founders Fund’s famously intense investment committees worked because relationships were secure enough to permit “no holds barred, complete truth-seeking.” Randle could tee off on Keith Rabois without hierarchy intervening; disagreement felt like fighting with a sibling, not navigating a political bureaucracy.

2. Mamoon Hamid taught taste by putting excellence within reach

Mamoon Hamid’s core lesson was that young investors must see excellence up close. Without early exposure to exceptional founders, management teams and boardrooms, they cannot reliably recognize that standard “in the wild” or hold weaker portfolio teams to it.
Randle sees a common line through Figma, Glean and Rippling: B2B software with consumer-like products, unusually strong user love and engagement, and teams capable of meeting a correspondingly high product bar.
Hamid’s advantage is “impeccable taste” across people, product and market, sharpened inside a deliberately narrow zone of strength. His mentorship encouraged Randle to develop an equally specific taste rather than imitate a generic venture playbook.
Harry supplied his own exaggerated endorsement: when Hamid offered to bring him into one of his deals, he told his team the diligence was already finished—“It’s B2B. It’s kind of PLG. It’s Mamoon”—capturing how much informational value an investor’s accumulated taste can carry.

3. OpenAI at $32 billion became the miss that changed Randle’s instincts

Randle loved ChatGPT immediately, but passed on OpenAI’s $32 billion round because the nonprofit structure, employee units and likely dilution looked “really gnarly.” Those risks were valid—the structure nearly destabilized the company, and talent hiring caused heavy dilution—but they did not matter beside its unprecedented growth and utility.
His diagnosis is unforgiving: “I got spooked and I missed the forest for the trees.” The private-equity training that gave him analytical discipline also encouraged him to over-weight structural complexity when the product itself was supplying extraordinary evidence.
Josh Kushner’s instinctive reactions to Spotify and Instagram now provide Randle’s counter-model: when a product feels inevitable, trust that intuition enough to avoid letting secondary defects dominate the decision. OpenAI remains his biggest miss and “hurts to this day.”
Randle predicts OpenAI could become a trillion-dollar company next year and raise at that level “no problem.” Harry’s related rule, learned from Kushner: if an investor is willing to accept less allocation merely to accommodate someone else, the weakened appetite itself says, “Don’t do that deal.”

4. ChatGPT gives OpenAI the edge while coding remains contested

Asked to choose between OpenAI at $500 billion and Anthropic at $350 billion, Randle chose OpenAI, though he called both potentially good investments. His downside analysis begins with ChatGPT: he cannot see what knocks it off its growth trajectory or prevents it becoming the most important consumer destination and app of the next five years.
Anthropic probably retains a bit of an edge in B2B commercialization after committing more time and resources to enterprise selling. It also remains slightly ahead in coding through Claude Code, Sonnet and its broader model suite.
OpenAI has nevertheless “made up a bunch of progress” with Codex, turning coding into hand-to-hand combat rather than a settled Anthropic advantage. ChatGPT’s consumer position, rather than a claim that OpenAI wins every workload, determines Randle’s valuation preference.
Cursor’s fate produced Randle’s honest non-answer: “I don’t know.” What he rejects is the inference that declining share means declining opportunity; Cursor can lose relative ground to Claude Code, Codex and Cognition while growing into a far larger absolute market.

5. Code generation is expanding faster than share is fragmenting

Cursor may have moved from roughly 80% of its initial market to 25–30% as competitors arrived. Randle’s estimate, however, is that code generation expanded from essentially zero to $6–7 billion of ARR in approximately 2.5 years.
His old “golden category” test identified markets adding $1 billion of net-new ARR in one year—large enough that a multistage fund effectively needed a position. Coding could add $4–5 billion across products and services this year alone.
Harry asked whether AI makes every category golden and whether the threshold should rise from $1 billion to $10 billion. Randle conceded AI enlarges many markets, particularly where software absorbs labor, but not all: a niche such as AI for veterinarians might still lack enough customers and budget.
Usage is also strategic. Randle expects products such as Claude Code, Codex and Cursor to improve fastest because AI products get better through usage; richly funded companies that have not put products into developers’ hands may face “a rude awakening.”

6. Labor budgets require a new taxonomy for AI companies

Randle’s concrete example was a Kleiner Perkins-backed home-services voice-AI business offering a 24/7 receptionist. A customer spending roughly $250,000 on seven ServiceTitan products spent the same on this single, newly launched AI product.
The economics worked because the customer could reduce three receptionists to two while answering calls and booking appointments around the clock rather than only from nine to four. The AI product both reduced labor expense and captured otherwise lost revenue.
That relationship cannot be understood by forcing the company into a SaaS template. Robert F. Smith, CEO of the first firm Randle worked at, Vista Equity Partners, used to say SaaS “tastes like chicken”: the businesses were similar enough for a repeatable operating playbook.
Investors are accustomed to roughly 80% gross margins, high-80s gross retention, 120%+ net retention and little capex. AI applications put inference directly into COGS. Lower margins may therefore indicate genuine usage; unusually high AI-app margins can mean customers barely touch the AI functionality. Randle wants investors reasoning from terminal economics, not rewarding an attractive but potentially empty percentage.

7. Absolute gross profit can matter more than margin percentage

Randle’s preferred comparison: if ServiceTitan produces $200,000 of gross profit per customer at 75% margin while an AI company produces $500,000 at 50%, “I don’t care” that the second percentage is lower. It has captured a broader relationship and more economic value.
The analytical units should become gross-profit multiples and absolute gross-profit dollars per customer, alongside a first-principles view of margins five to seven years out. Training costs and companies developing their own models add further differences from conventional SaaS.
AWS is his analogy. He estimated its gross margin at perhaps 50–60% and operating margin around 30%, yet it is commonly a software company’s largest line item—far above Salesforce, Workday or Adobe—because infrastructure spend is so expansive.
In the early 2010s, a $150 million-revenue software company could show a startling $30 million AWS COGS line. AWS’s percentage margin was less important than the multiples more customers spent on it; Randle suggested it might be a trillion-dollar standalone business if separated from Amazon.

8. Growth is real only when an app clears the labs’ baseline

AI companies can go from 0 to 100 in less than a year, but Randle keeps “easy come, easy go” in view. Jasper grew rapidly and then shrank because its early revenue lacked enough scaffolding and durable customer value.
GPT-4 exposed the weakness: customers judged Jasper’s output similar to what ChatGPT offered for $20 per month. Randle believes Jasper subsequently recovered by embedding LLMs throughout differentiated marketing workflows rather than selling lightly packaged model access.
The labs now set the minimum customer experience. An application charging materially more than ChatGPT’s $20 or $200 per month must outperform the lab product enough to support enterprise distribution, retention and a sustainable business equation.
Randle rejects the claim that moats moved wholesale from technology to distribution. Distribution provides “the right to build differentiated technology,” but exceptional AI products require scarce talent, careful model pipelines and tasteful workflow integration—not an API placed inside a text box.

9. AI talent and product craft remain the scarce technology

The classic “seven powers” have not disappeared; the stakes have risen because applications scale faster while the labs improve and distribute their own products faster. Sustainable growth still depends on differentiation that persists through successive model upgrades.
Randle reframes the technology moat as partly a talent moat. Few people can decide where LLMs belong in a workflow, how outputs should be improved, and how the full product should behave sufficiently well to outshine the labs’ applications.
That scarcity explains researchers receiving billion-dollar contracts and “LeBron money.” Distribution without such builders may produce access, but not the exceptional product required to defend the customer relationship.
Harry’s distribution-and-data thesis therefore received a direct rebuttal: Randle said the moat remains fundamentally technological. Product quality is also evidence about the people capable of building it.

10. Commodity AI infrastructure can overwhelm quality concerns

Randle changed his mind most sharply on AI clouds. He initially dismissed CoreWeave as a middleman reselling commodity compute—a broker with structurally weak margins—but astronomical inference demand overwhelmed that business-quality objection.
He recalled CoreWeave raising privately around $3 billion; at the episode’s stated point it was roughly a $60 billion public company, while Nebius was around $30 billion and the sector exceeded $100 billion of public market capitalization, before counting rapidly growing private players.
Randle still thinks CoreWeave and similar companies “probably go down like 70%” at some point. Yet early investors already gained liquidity after a 20x move from the level where he rejected the company, making his original commodity critique economically beside the point.
The lesson is deliberately uncomfortable: when demand resembles the first hyperscaler wave—and AI inference may show an even steeper cohort curve—“sometimes you just got to shut your mind up and invest with the momentum.”

11. Benchmark invests its fund size instead of chasing every laboratory

Randle applies Conway’s law to venture: firms “ship” their fund size, team and structure. A $7 billion fund with 50 investors must participate in mega-rounds because billion-dollar checks are among the few ways to deploy its capital productively.
Benchmark’s smaller fund can play another game. Its five leading investments from the last fund, marked at last-round prices, were approximately one 60x, two 30xs and two 20xs; Randle said no OpenAI round since ChatGPT’s launch reaches those multiples.
Harry calculated OpenAI at $32 billion as perhaps 12–15x headline appreciation, but closer to 6–8x after dilution. He contrasted that with Benchmark’s Lovable, LangChain, Sierra, Mercor and Fireworks positions: for a small fund, cash-on-cash return—not prestige—is the product.
Randle acknowledged that skipping labs could threaten relevance and access. His present counterevidence is Benchmark’s relationships with people such as Bret Taylor, whom he called the godfather of AI applications, and Brendan at Mercor, whom he cited on the AI-infrastructure side.

12. Ownership is an input; partnership and return are the outputs

Benchmark’s two north stars are to become each founder’s closest, highest-ROI partner and to generate the highest money-on-money return among an LP’s venture holdings. A customary 20% ownership target is not itself one of those goals.
Harry cited an article putting Benchmark’s Mercor ownership at roughly 10%, below its historical norm. Randle’s response was that larger potential outcomes create more ways to deliver exceptional returns while remaining the company’s most consequential venture partner: critics “confuse the inputs for the outputs.”
Harry challenged the “best partner” claim with Delian Asparouhov’s criticism that Benchmark fires founders. Randle noted that replacing founders was once routine—Google’s investors immediately sought a professional CEO—but said governance and board-founder relationships have changed substantially for the better.
Founder loyalty cannot erase legal, ethical or fiduciary duties. Harry described boards sacrificing the cap table to protect founder NPS; Randle agreed, adding that great founders do not want sycophants or “GPT-4o in the boardroom,” but adults willing to spar and improve the company.

13. Price matters only against the company’s own upside

Benchmark’s four general partners each represent 25% of the partnership and retain distinct styles: Eric Vishria gravitates toward inception, while Randle expects initially to invest more around Series A, B and beyond. The shared constraint is not stage but exceptional founder partnership and return potential.
Randle admitted insecurity about arriving as a growth investor. Vishria answered that Bill Gurley had been a public-markets analyst before Benchmark; Randle also cites Pat Grady as evidence that the best investors increasingly transcend stage rather than live inside an organizational category.
His ranking is people, product, market. People are the upstream engine; product is the strongest evidence of their quality; market comes third because it is most fungible. Teams can pivot, as Slack did, while a non-exceptional founder or product organization is much harder to transform.
SpaceX at $150 billion taught Randle to remove the intimidating zeros and compare TAM, competitive position and upside. Rippling’s $250 million Series A and Figma’s $400 million valuation on $4 million ARR looked absurd relative to market convention, yet relative pricing would have screened out their excellence.

14. Models test conviction, but mega-fund structures reshape behavior

Randle uses models to lay out the base-rate future—perhaps the path other growth investors underwrite for a 3–5x—and then asks whether his qualitative view says the company will “absolutely smoke these projections.” Beyond that yardstick, detailed forecasts become false precision.
Figma illustrates the trap: any accurate-looking forecast of its eventual duration, growth and profitability would have seemed engineered to win investment committee approval. Simple market sizing also failed because counting designers missed adoption by product and other roles.
In his 2021 essay “Playing Different Games,” Randle predicted bifurcation between Tiger’s high-velocity, founder-friendly, low-touch model and Benchmark’s concentrated, high-touch craft. The undifferentiated middle became his “J.C. Penney funds”; after Tiger faltered, “we got six or seven more Tigers.”
Harry disputed applying Tiger’s north star to Thrive, Lightspeed or General Catalyst. Randle softened the Thrive characterization but proposed an organizational test: ask the principals, junior partners and associates whether deployment affects promotion. When billion-dollar checks generate perhaps 95% of profits, he argues, they inevitably become the main product.

15. Mega-funds can win in dollars while losing the venture-return test

Randle accepts Harry’s central pushback: OpenAI, Anthropic and Cursor may become far larger than anyone once imagined, allowing their investors to make immense absolute sums. The disagreement is whether that translates into the multiples LPs expect from venture.
He doubts leaders of the largest firms can tell LPs “with a straight face” that a pari passu basket of their funds will deliver 5x net. Returning even 4x net on an $8–10 billion vehicle, he argued, approaches a scale that “defies the laws of physics.”
LP demand for private technology may postpone any reckoning because institutions currently accept lower returns for access. But Randle notes that LPs already have private equity for lower-return exposure, often with better liquidity; venture’s distinctive role is unusually high money-on-money performance.
Inside a 50-investor platform, the 23rd partner may inherit 30 merely good company relationships, need a couple of deals for promotion, and hope one creates tenure. Randle says that resembles investment banking or a large buyout shop more than “meeting really interesting founders” and making only the best investments.

16. Tiger may be vindicated, but the next crash still demands survival

Randle agreed that Tiger’s 2021 portfolio may finish far better than its reputation suggests. Large positions in Databricks and OpenAI, plus preferred-stock liquidation protection on many of the things that do not work, could make “#JusticeForJohnCurtius” more than a joke.
His conditional scenario was explicit: if Databricks becomes a $400–500 billion company and OpenAI becomes multitrillion-dollar, Tiger’s fund may be “pretty okay”—not the best portfolio an LP ever owned, but nowhere near a money incinerator.
The excesses remain vivid. At a December 2021 or January 2022 Miami party, possibly featuring Vanilla Ice, Randle watched public technology fall 30–40% and thought of The Dark Knight Rises: “Gotham is burning,” while the industry attended one last decadent celebration.
Today may rhyme with the dot-com cycle: many AI companies will go to zero or fall 90%, while the rare enduring winner compounds for 20–30 years. Benchmark’s answer is constrained fund size and careful capital use, preserving the ability to weather a crash rather than forcing LPs to flee.

17. Benchmark’s greatest risk is stasis, not one missed cycle

A partner advised Randle that a failed first Benchmark investment might be liberating: once it fails and “LPs still love us” and nobody is fired, the second decision carries less psychological weight. Early apparent success might instead compound the pressure.
Asked where he would put money among his former firms for the highest cash-on-cash return, Randle chose Founders Fund because incubation produces equity when buying it becomes too competitive. Anduril demonstrates the possible fund-level result; every few funds, or every five to ten years, the firm has incubated an unbelievable company.
Benchmark itself must remain dynamic while preserving its two north stars. Randle calls “stasis” the largest threat over the next two decades: involvement with the very best founders is the asset class’s currency, and tradition cannot be allowed to make “the tail wag the dog.”
His ten-year optimism is macroeconomic. Social media showed capitalism optimizing human attention toward glued screens, but AI can instead raise GDP per capita as birth rates slow. Drawing on Peter Thiel’s framing, Randle sees economic growth—“continuing growing the pie”—as the essential condition for prosperity and a harmonious, non-zero-sum society.

Ev Randle

I think we should not be placing that much emphasis on margins today. We need a new taxonomy for AI companies.

Harry Stebbings

I'm thrilled to welcome Benchmark's newest partner, Ev Randle. Benchmark is one of the best firms in venture.

Ev Randle

Tiger died, and we got 6 or 7 more Tigers. I don't think Roelof or Hemant or even Ben and Marc, at this point, can go to LPs and say, "Hey, we're going to get you 5x net on that." When you're writing billion-dollar checks, that is your main product. Go talk to the principals, the junior partners, and the associates at those firms, and you tell me that capital velocity is not the north star of those firms.

I think Tiger's going to end up much better than anyone thought they were going to end up.

Harry Stebbings

What do you think the biggest threat is to Benchmark being successful in the next 5 years?

Ev, I am so excited for this. I cannot believe we have not done this before. I think I personally timed it pretty well, if I'm honest. I'm rather chuffed with myself. Thank you so much for joining me today.

Ev Randle

Thank you, Harry. I have actually been listening to 20VC since 2017, which, ironically, I think is the year that you had Peter on for the first time. It's just been so fun to watch the show and the platform that you've built grow this way. It's almost like watching a startup become an IPO-worthy company or something. So, congrats to you, Harry.

Harry Stebbings

Do you know what? I've had a man crush on Peter Fenton since that first show. I remember he told me that price is a litmus test for your conviction, and I think about that at least on a weekly basis. I've repeated it to my team many, many times.

Before we dive into Benchmark, you've worked with some of the best: Peter Thiel, obviously, at Founders Fund; Mary Meeker at BOND; and Mamoon Hamid, one of my big bros at Kleiner Perkins. If I were to ask you for your biggest takeaway from each, what would you say your biggest investing takeaway is from each of them?

Ev Randle

One of the things I really love about the asset class that we practice our craft in is that there are so many different ways that you can be successful at it, and there are so many different strategies and frameworks that you can employ and still generate amazing returns. Each of the people that you just mentioned has a very different style and a very different way of practicing their craft.

If I was to lay out what I learned specifically from Mary, Peter, and Mamoon, I think with Mary, she does such an incredible job. Everyone thinks of her as this quantitative investor. She had her time as an equity researcher at Morgan Stanley during the dot-com bubble, and then she came to Kleiner Perkins. Everyone talks about the DCF models she creates and all the numbers that she does, but she's really the most qualitative investor that I've ever worked with. It's probably a surprise to hear that, but what she does is almost like she's reading the Matrix.

She lays out all the sequential numbers historically for a company and then all the numbers going forward. It's almost like she's reading the Matrix code as it comes down, and she's seeing what the company will become on an 8- to 10-year time horizon when she sees what the numbers are.

She'll look at a DoorDash model, and that was an investment that we had led at KP out of the growth fund at the time. She won't see 7 years out, 80% growth or something like that. She'll see that 20% of households are going to be ordering from DoorDash on a monthly basis, and she can visualize that.

From her, I just learned that when you use numbers in venture and growth, and when you want to be quantitatively driven, don't get stuck in a quantitative lens with it. Actually use that to drive the narrative and drive the story of an investment. That's been an incredible mental framing that I've used with someone like Peter Thiel.

Peter, I think so much of his cleverness and so much of his genius is actually in the way that he builds his firms, rather than even his investments. The way that he's designed Founders Fund is that he creates all these incentive structures and mechanisms to constantly be testing your conviction.

There's a program, for example, at Founders Fund where anyone that works on an investment—or if you're leading an investment—you can personally invest alongside the firm in that investment, almost as if you're angel investing. At first glance, it just looks like this amazing perk that you can have by being an investor at Founders Fund, but deeper down, it's a conviction test.

If you're sponsoring some pro rata of a company that's doing okay but not great, and the founder really wants you to do the pro rata so as not to blow up the round, but you're not doing some of your portion on the individual side of that investment—your angel investment—Peter can go to you and say, "Do you not think this is better than having your money in the S&P? Why would we give our LPs this allocation in this round if you don't even want to put your own money in this round?"

There are 100 different things like that that exist in Founders Fund that aren't explicit, like, "Do you have high conviction?" They test your conviction in deeper ways.

Harry Stebbings

I absolutely love that as a conviction test. Do you ever, just reflecting on that, have the fear that if you had that with a younger person—say, when you were at Founders Fund—if you don't have that much liquid cash, it is a lot when you have rent and bills?

I'm thinking through this as an active partner with you now because I'd love to implement that in 20VC, but I would hate for people to be scared and then say no to something because they didn't have the cash. That could be great. What do you think?

Ev Randle

It's super valid. I think, again, if you're at Founders Fund, you are all in. Most of us that were young at Founders Fund at the time all had debt lines—unsecured debt lines—that we were using to make these side, personal investments.

By the way, it's turned out to be an unbelievable portfolio for myself personally, and it's all worked out. So I'm very glad that I had it. But I think that's part of how, throughout his entire career, he has really designed his organization so people are all in.

He had a bonus system for PayPal employees. If they lived within a couple miles of the office, he'd give them more money. He just designs organizations this way. There's less pressure for the young folks that don't have much net worth yet, for sure, but he still expects you to be scrappy and find a way to do it.

Harry Stebbings

What do you think no one knows about the inner workings of Founders Fund that they should know from the outside in?

Ev Randle

From the outside in, obviously, Founders Fund is a bit of a black box. Everyone's like, "Wow, the returns are amazing. There's a bunch of weird personalities within that place. How does it all happen?"

When I was actually doing backchannel references on Founders Fund before joining, something that everyone said to me that they thought was a negative but ended up being a huge positive was, "Oh, you really got to watch out for the culture because I've heard that they yell at each other during ICs, or investment committee meetings, and they get super intense."

A few months into the actual job at Founders Fund, I realized that, yes, sometimes people did yell at each other at ICs, but it was because you were yelling at your brother, yelling at your sister, or yelling at your best friend. Everyone was so secure in themselves and the relationships that they had with each other—and they all have extremely deep relationships with each other—that you could actually just be extremely truth-seeking.

You weren't afraid to step on toes. You weren't afraid to do anything that might be seen as, "Oh, you shouldn't say that to a GP." It was just no holds barred, complete truth-seeking, everyone trying to get to the best answer.

I remember a few months into the job, I was on an email thread and just teed off on Keith Rabois, our good friend. At any other firm, that might be a fireable offense, or you might get a tongue-lashing for doing that. But at Founders Fund, it was a pat on the back. It was like, "Yes, that is how we do things here." It's flat. We're just trying to get to the truth. We're not trying to uphold some political bureaucracy or something like that.

Harry Stebbings

And then Keith fired you. (Laughter.)

Dude, that, to be fair, is a bold take for a younger person in your first years. Well done. That's conviction, going up against Keith in that way.

If we go to Mamoon, what are the takeaways from Mamoon? I think Mamoon is just one of the greats. He's done so well with KP. What are the takeaways from Mamoon?

Ev Randle

Yeah, Mamoon Hamid—I have learned so much from Mamoon. He's a wonderful mentor. We were talking before the show, Harry, about the kindness that he showed you when you were young, and he did the same thing for me.

I think the biggest thing that Mamoon has taught me—and this is a reflection of what he did and has done in his career—is that you need to, early in your career, see excellence up close. In terms of a company, a management team, or a founder, you need to see how the absolute best operate and do the job of company-building.

If you don't see that relatively early in your career, it's much, much harder to spot it in the wild, and you also don't know the bar to hold your other founders and your other management teams to. He does a very good job of getting younger folks that work at Kleiner Perkins, or even back at Social Capital, involved in the very best companies and in those boardrooms, seeing how they operate.

He thinks that once you've seen it, and once you know the "it" of what makes an A++ team tick, you can, one, much more easily see that in the wild, and two, you can really hold the rest of your management teams and founders that you work with to that really high standard.

I think Mamoon, more than anyone, has developed this impeccable taste around a mix of product, market, and people.

If you think about his huge, huge winners, whether it's Figma, Glean, or Rippling, they all have a common throughline. It's B2B software, but it's almost like consumer-like software that demands really high user love and engagement. He's just developed this really, really tight understanding of where he shines and where he has a really deep understanding of companies.

He's really sharpened his taste in doing that. So I think he's definitely encouraged me and encourages people that he works with to really develop a specific form of taste around the people, the products, and the companies that you think are going to be the big ones.

Harry Stebbings

He very kindly messaged me the other day and said, “Hey, I'd love to bring you into one of my deals, Ev. The founder is amazing, and you'd be great for it.” I messaged my team, just being like, “Hey, we're doing a deal. It's amazing. Mamoon's bringing us in. We're done. Diligence over.”

They're like, “Harry, no, you can't be serious.” I'm like, “It's B2B. It's kind of PLG. It's Mamoon. Would you like your job tomorrow?” So I totally agree and get you there.

Can I just ask, before we move to Benchmark—you mentioned Mary Meeker and the mental plasticity that she had around numbers and what the future could be. Where were you not mentally plastic where you should have been, and what did you learn from that?

An example for me would be: I met Alex at Deel when it was 2 on 10, and I looked at Paychex and ADP and I was like, “Nah, shit market, incumbents, distribution advantage, crap investment.” What a mistake. I wasn't mentally plastic and I should have been. What would yours be?

Ev Randle

An instance where I haven't, and where I haven't exuded neuroplasticity enough, I actually have a very recent example of this. It was the OpenAI round at $32 billion.

I started my career in private equity, which gave me a lot of strengths, but it also definitely gave me some blind spots in venture that I've needed to unlearn a little bit. When I was at Founders Fund, I was actually extremely positive on OpenAI. I had left Founders Fund right after ChatGPT came out, and ChatGPT, when it came out, was one of those moments where you're like, “This product is it. This is so unbelievably cool.” You could just tell that it was going to be a massive, massive product.

Then the $32 billion round of OpenAI came around when I was at Kleiner Perkins, and all of a sudden I was like, “Oh, man, this structure seems really gnarly. They're going to have to convert this somehow. It's a nonprofit. They're selling these employee units, and I think they're going to dilute the hell out of the investor base.”

I got spooked and missed the forest for the trees, both in terms of the structure of the company at the time and the potential future dilution. By the way, both of those things were very valid risks. The structure at certain points has almost taken the company down, and they've diluted a ton, given that they've had to attract all these AI researchers and all this incredible talent.

But it didn't end up mattering. None of that ended up mattering. What ended up mattering is that it's had the strongest and highest growth trajectory of any technology company in history. It's probably the best and most useful product that anyone who uses it has in their pocket.

I think Josh Kushner actually does probably the best job of this. He talks about his intuitions, and he saw Spotify and just kind of knew that, no matter what, he needed to invest in the company. The same with Instagram. I still need to learn to trust my intuitions more, because sometimes I let silly things like that cloud my thinking.

Harry Stebbings

Josh taught me one of the most valuable lessons, actually. He taught me that if you're ever willing to do less in a deal, don't do the deal. “I'm happy to take 10% if it means giving my buddy 3%.” Don't do that deal. That's a bad signal.

I remember Vinod came on the show when he did that deal, and he said, “Harry, listen, if it's a trillion-dollar company, we'll all make money.” We laughed at the time, and now it's like, “Oh, it might be a trillion-dollar company.”

Ev Randle

Three trillion. Who knows?

Harry Stebbings

Yeah. Do you think it'll be a trillion-dollar company next year?

Ev Randle

I think it'll be a trillion-dollar company next year, yes. I think they could probably raise at the end of the year—Q2, I think OpenAI could raise at a trillion dollars, no problem.

Harry Stebbings

Would you rather be in OpenAI at $500 billion or Anthropic at $350 billion? Obviously, at Kleiner Perkins we invested in Anthropic, and we had this debate a lot internally. Everyone kind of thinks this is a fun debate: OpenAI or Anthropic at the last-round price.

Ev Randle

I think they represent relatively different things. In terms of downside risk, it's hard to imagine anything that could knock ChatGPT off of its growth trajectory. I don't know what could stop ChatGPT from growing at the rate that it's growing. That asset alone is unbelievably valuable and completely locked in.

There's no way that it's not going to be the most important kind of consumer destination and consumer app over the next 5 years. I think where everything else is still hand-to-hand combat is obviously in coding.

I think OpenAI has actually done an incredible job with Codex and made up a bunch of progress against Anthropic that they didn't have before. On everything on the B2B side, Anthropic probably has a bit of an edge right now. They've spent a lot more time and resources toward really mastering the commercialization effort there.

In coding, Anthropic, with Claude Code, Sonnet, and all the models that they have, is probably still a little bit ahead of OpenAI. But given ChatGPT, I think I would probably rather do OpenAI at $500 billion than Anthropic at $350 billion. I think both are relatively good investments even today.

Harry Stebbings

I would be thrilled with both, just in case Dario or Sam are listening. Very happy to take some shares.

Ev Randle

Very happy.

Harry Stebbings

If you want to help me out here. Sam, I'll buy Brad Gerstner's if you want that one, because he doesn't want to. I won't ask any questions. I'll just wear a Sam T-shirt.

What happens to Cursor? You see Codex crushing it, as you said there, and Claude Code has done so well. What happens to Cursor? I don't know. I'm purely lost on that one.

Ev Randle

I think the thing that everyone has underestimated thus far is just how immense a potential market code can be. When you think about Cursor, a lot of people are like, “Well, their relative market share has gone down a lot,” because at first it was really just them, then Claude Code came out, then Codex came out, and now Cognition is scaling.

Instead of, I don't know, 80% of the market or something, maybe they have 25% to 30% of the overall ARR in the market today. Again, what people are missing is that the market for code generation, over the last 2.5 years, has gone from essentially $0 to probably $6 billion or $7 billion of ARR.

Something we used to do at KP and Founders Fund was try to identify the golden categories. A golden category is a category where the entire market for a single product adds $1 billion of net new ARR in a single year. If you find a golden category, especially if you're a multistage fund, you have to have a bet in that category, because it means that it's going to produce really big outcomes.

Instead of adding $1 billion of net new this year, I think code generation is going to add $4 billion or $5 billion of net new across every single product and service that's available for people to buy, both on the B2B and B2C side.

Harry Stebbings

Can I ask: does AI not make every category a golden category? I don't mean that stupidly, but customer service is, of course, tens of billions of dollars. Even if you think about much more verticalized software plays, could you not apply “golden category” to everything then? Should we not move $1 billion to $10 billion?

Ev Randle

It does for a lot of categories. It remains to be seen, right? Let's say you're doing AI for vets—veterinarians. Maybe there just aren't enough vets that have enough money to actually create $1 billion of net new in a given year.

But I do think that, for so many categories that seemed like they were middling in size, a lot of what AI has been able to do—especially if it can touch something that a labor force within a category was doing before—is creating much, much bigger markets.

As one example of this impact, at KP we were invested in a home services AI business that was essentially a 24/7 receptionist. Its first product is a 24/7 receptionist for HVAC people, home services, and anyone that would be a ServiceTitan customer.

We were calling customers and asking, “Okay, how much do you spend on ServiceTitan?” They're like, “You know, $250,000.”

It's like, okay, well, how much are you spending on this company? And they're like, "$250K." It's like, okay, you have 7 products from ServiceTitan, from SaaS 2.0, and you have 1 product that's just out of beta from this new startup in voice AI, and you're spending as much on that as you are on ServiceTitan, the system of record for everything that you're doing.

And they're like, "Yeah, well, we no longer have to staff 3 receptionists; we can staff 2, and we're now able to actually accept calls and book appointments 24/7 rather than the 9-to-4 schedule that our receptionists were sitting there." And so it's driving more revenue and more impact than even ServiceTitan was doing, given that the capabilities are just so much broader and real than the impacts that SaaS can have on companies.

Harry Stebbings

Ev, are we gonna be frenemies?

Ev Randle

Was that ProBook?

Harry Stebbings

No, no, this one, Lerer Hippeau led a round in Aloha, is the company's name.

Ev Randle

Oh, thank God. I lost this deal and I didn't know who I lost it to. And it's exactly the same way. You're like, "How much do you spend on ServiceTitan?" And then it's the same, if not more. And you're like, "Oh my God, that is 1 incredibly valuable segment that we're covering."

Yeah, and I think it gets to something that I desperately want us to do in the venture industry, which is we need a new taxonomy for AI companies. What I mean by that is AI app companies are meaningfully different from SaaS companies in a dozen different ways, yet we keep trying to shove all the metrics from these AI app companies into the frameworks that we created for SaaS.

Harry Stebbings

What was your pause on that? What metrics do we try and shove in that we shouldn't?

Ev Randle

If you just think about the P&L of a SaaS company, Robert F. Smith, the CEO of the first firm that I ever worked at, Vista Equity Partners, always used to say—probably still says—"SaaS is great because it tastes like chicken." All the businesses are the same. And the whole thesis behind Vista was that SaaS companies are so similar that you can do the same exact things to each of them in the whole Vista playbook style and make them way more profitable and run a lot more efficiently.

And so we're used to, "Gross margins need to be 80%, gross retention should be in the high 80s%, net retention should be over 120%, there should be very little CapEx," and that's what makes a good company. And I think what you're seeing with AI app companies is a very different situation where, if they're good companies with a lot of usage, you have a lot of AI inference in your COGS that you don't for normal SaaS companies.

And so people are like, "Oh, these are worse companies because they have worse gross margins." But if your average gross profit per customer can be 4 or 5x that of a normal SaaS company, then you actually have much more absolute dollars of gross profit per customer and potentially a much, much larger market than you do for SaaS companies as well.

So instead of talking about gross margins and revenue multiples, I hope that someday we talk about gross profit multiples and absolute gross profit dollars per customer. If your relationship with a customer can be much, much broader because you're taking part of their labor budget or you're giving them more economic value than you would if you were a SaaS company, it's just not appropriate to be grading them on a metric like, "Do they have 80% gross margins?"

It's like, well, if ServiceTitan has $200,000 of gross profit per customer and this other company has $500,000 of gross profit per customer, I don't care that that second company has 50% gross margins and ServiceTitan has 75% gross margins. It doesn't matter.

So I think that's the biggest example: the contract sizes can be much larger even if the gross margins are lower. But I think there are several others. Some train their own models, and so there are training costs and other various changes as well.

Harry Stebbings

So, help me out: should we not place such emphasis on margins?

Ev Randle

I think we should not be placing that much emphasis on margins today. I think the work that we should be doing is trying to understand what the terminal gross-margin structure looks like for these businesses and also what the absolute gross profit dollars are in each of these categories that these companies can represent.

Again, I think the folks over at Andreessen Horowitz have done a lot of good work in terms of evangelizing this idea that if you have high gross margins as an AI app company right now, it probably means that you have very little AI inference expense in your COGS, which means no one's actually using your AI features.

It's not the easiest thing to understand what these AI app gross-margin profiles are going to look like in 5 to 7 years. But I think that at least trying to go from first principles and reason about what the gross profit dollar per customer and the gross margins of these companies in 5 to 7 years look like is so much more worth doing, and it's such a better intellectual exercise than trying to compare it to SaaS, which is just a very, very different business and has a very different pricing and business model that isn't going to be as relevant, I think, over the next 10 years.

Harry Stebbings

It's so interesting. Rory O'Driscoll from Scale, who's basically like my adopted father—he doesn't know that, so you've just gained a son—he's listening to this show like, "Wow, this is a productive show." But he always tells me that, fundamentally, whether we make money from AI or not will be predicated on whether we see the movement from human labor budgets to AI software spend.

I think exactly to your point there, for everyone who's trying to understand absolute dollars in terms of profit, your margin can be lower, but because the spend is 5x, your absolute profit is significantly higher on a per-customer basis. Correct?

Ev Randle

Exactly. So let's think about AWS, for example. AWS—I actually don't know their exact gross margins—but they're not as high. They're not 80%; let's say they're 50% or 60%. I know that their operating margins, I think, are at about 30%.

The thing about AWS is that it is the largest line item for essentially any large software business versus anything else that they pay for. You're paying more for AWS than you're paying for Salesforce, Workday, or any other SaaS company, by a wide, wide margin.

In the early 2010s, you had companies doing $150 million of revenue, and people started to be like, "What is this $30 million COGS line to Amazon Web Services? What in the hell is this?" And I think that's an amazing example of, yeah, does AWS have lower gross margins than Adobe? Of course it does. But everyone that uses AWS and is a core customer of AWS spends multiples more on AWS than they do on Adobe, which is why it's such an unbelievably large business, probably a trillion-dollar business if it was spun out of Amazon.

So that is the idea that I think we need to all get in our heads: it's not going to be every company, and it's not going to be every market. But for the right AI companies in the right markets, the size of their revenue per customer is going to be so much larger than SaaS that, even if they have lower gross margins, they're going to be much, much more valuable companies.

Harry Stebbings

Going to that as well, what is AWS? It's a commodity. And that's what I find so interesting. You were like, "Oh, your models won't make money because they're just commodity businesses." And then you look at Google Cloud, you look at Azure, and you look at AWS, and you're going, "Wow, maybe the best business in the world is a commodities business."

To your point, one of the things I've changed my mind on over the last 2 years is these AI inference cloud businesses. So who's going to be the AWS, GCP, or Azure of the AI era? When CoreWeave was first raising in private markets, I was like, "Oh my God, they're reselling a commodity. They're a middleman. They're a broker of compute. It's going to be a low-margin, yada yada yada."

How wrong was I? I mean, maybe the market's down a little bit, but last time I checked, it was a $60 billion public company. Nebius is a $30 billion public company. There is over $100 billion in public market cap, and there are several private players that are growing astronomically as well in this AI inference cloud.

So I think sometimes we can twist our minds in knots over, "Oh, is the business quality okay?" When you have demand like this, like you had for the initial hyperscaler clouds—and I think we're seeing an even greater cohorted demand curve for AI inference—sometimes you just got to shut your mind up and invest with the momentum.

Ev Randle

I totally agree in terms of "shut your mind up" and investing with the momentum, but it brings me to the other element, which is different than ever before. You mentioned there the change from margins to a focus on absolute gross dollars per customer. The thing that's different is growth rates.

And I think the thing that I'm struggling with is sustainable versus unsustainable, but also being a sucker for momentum and high, high numbers. How do you think about the importance of growth rate—optimizing for it versus sustainability? And do we need a new taxonomy around growth rate as well?

Ev Randle

I think we do. I think the things that we need to hold in our heads when we're thinking about this are that we have companies going from 0 to 100 in less than a year. We've never seen that. At the same time, is it easy come, easy go? We had early examples of this.

I'm comfortable saying this because now the company has rebounded and, to my knowledge, is doing really well. I remember when people were talking about Jasper. The 2 AI investments that started the wave were Stability AI and Jasper AI. Stability is a different story, but Jasper went from 0 to 100 very, very quickly and then actually started shrinking. It was sort of easy come, easy go with the revenue, and they hadn't built enough scaffolding or enough actual, true value to really sustain the customer relationships they had and sustain their growth rates.

The way I've been thinking about this, especially as it relates to app-layer companies, is that the other aspect is: what is the risk for a lot of these app-layer companies, and who are they in danger from? It's the labs. The labs are creating apps, creating more value via the models, and giving that value directly to users. Oftentimes, as an app company, you need to be doing better than what $20 a month can get you from ChatGPT.

For a lot of these categories, the labs set the baseline in terms of customer experience. They're your competition at the base layer. Whatever you can get from ChatGPT, or whatever you can get directly from the labs' apps themselves, you need to be sufficiently differentiated from that because they're happy to charge $20 or $200 per month per user. A lot of these AI companies want to charge a lot more than that in order to have a sustainable business equation and actually be able to do B2B distribution.

When you think about Jasper at first, the issue they ran into was that when GPT-4 came out, people started saying, "Wow, the outputs I'm getting from Jasper are kind of the same as what I'm getting for $20 a month from OpenAI. I'm not going to pay however much more for Jasper. I'm just going to use ChatGPT." What they've done now is build sufficiently differentiated workflow software and tie in LLMs through the lifecycle of how their users work and operate, in a way that is sufficiently differentiated and gives them more of a moat.

I don't think the sources of moats have changed from SaaS to AI, necessarily. 7 Powers are still 7 Powers. All of the same ways to build differentiation are still there. The stakes are just much higher because the growth rates are much higher, and the labs are getting so much better so quickly, especially at delivering applications.

Harry Stebbings

How do you feel about people who say the moats have changed? The moat that was technology is now fundamentally distribution—in terms of access to customers and data, and access to data—and it shifted from technology to those 2 things. Do you disagree with that, or do you agree with that?

Ev Randle

I definitely disagree with that. I think the moat is still fundamentally in technology, not in distribution. Distribution obviously gives you the right to build differentiated technology, but one of the huge learnings we've had as an industry is how damn hard it is to build good AI products.

A good AI product is so much different to build than a good SaaS product. You need different people, and there are so many different parts of a good pipeline. Where do you bring in LLMs? How do you improve them? How does it fit within a general workflow? It's not just bringing in the OpenAI API and using it within the text box or something. It's extremely nuanced and complex to build an exceptional AI product, especially one that's going to outshine the labs' applications themselves.

I still think it's technology. It might just be different in that maybe it's not a tech moat in terms of having a unique database that no one's ever built before that's more efficient for X, Y, and Z use cases. It's really a talent-scarcity and talent-tech moat, where there just aren't that many people who know how to build these products and build off of these models in a super-intelligent, tasteful way. That's why you're also seeing people go for billion-dollar contracts and make LeBron money as an AI researcher.

Harry Stebbings

How do you at Benchmark think about that? I struggled with this one, too. My fund is $400 million. Benchmark, I believe, is $500 million to $600 million. You guys never really announce funds in the way that most people do because it's probably mostly just your money at this stage.

My question to you is: when you see a Mira Murati or Periodic Labs—great and very talented people—but these are $300 million rounds and $2 billion rounds, do you just accept that that is not a world that you play in?

Ev Randle

This gets to a question that I think some people have. I don't think you've had it, Harry. You've been very kind to us. But I think some people have asked the question: did Benchmark miss AI? Did Benchmark not get in on the AI wave because they're not in one of the labs, or they weren't in Mira's, they weren't in Thinking Machines, or any of these investments?

I'm a big believer in Conway's law. Conway's law is a programming concept that, when it's super-dumbed down for people like us, Harry, says you ship your org chart, or the product you ship looks like your organizational structure. I'm a huge believer in that for venture capital firms as well. I think you ship your fund size, or you invest your fund size, and your team structure.

If you have a $7 billion fund and you have 50 people, you definitively need to get in on these mega-rounds. It is the only way that you can put $1 billion of capital to work productively in a single shot. If you don't and it ends up being successful, you are left in the dust, while all of your megafund brethren got those returns. Now you're benchmarked poorly against them because you missed one of those things.

For a firm like Benchmark, it might not make any sense at all to invest in a $5 billion financing in a lab, even though those are good investments, because of our fund structure and our lean size. But our lean size and our smaller fund size also allow us to do other things that we think could generate even better returns.

Out of our last fund, our 5 best investments today, held at LRP—last-round price—are about a 60x. We have 2 30xs, and we have 2 20xs. Since ChatGPT was released, there isn't an OpenAI round that touches that return multiple and that money-on-money multiple. We have 5 of them, and each of them, I think, has a fair amount of upside even from here today, or maybe a lot of upside even from here today.

So I think you have to choose the game that you're going to play, and it's based on how big your fund is and how many people you have on your investment team. There are so many different ways that we can play the game and generate maybe even better money-on-money returns than folks who are investing in the labs. I do think the labs have obviously been amazing investments.

Harry Stebbings

Your fund size dictates the problem that you're solving for. When you said something about missing OpenAI at $30 billion, transparently, all I thought was, that's like a 15x on a blunt multiple to where it is today. But with dilution—

Ev Randle

Okay, let's say 14x. Let's say 12x.

Harry Stebbings

But with actual dilution, you're looking at more like a 6x to 8x, which, don't get me wrong, is fantastic. But when you do a comparison to your Lovable, your LangChain, your Sierra, your Mercor, and your Fireworks, I mean, we're focused on cash-on-cash.

Ev Randle

100%. Again, I think the lab investments are amazing as well, but our job is to—if we're going to stay small—the only way we're going to impress LPs is by having incredible cash-on-cash returns.

Harry Stebbings

Do you worry you need them to stay relevant? I agree with you on LPs, and I agree on cash-on-cash, but just in terms of relevance with founders and the community, do you worry that you need them to stay relevant?

Ev Randle

I think it's a question that we need to constantly be asking ourselves. If we ever find that our network access, the close relationships we have, and the people we have access to are slipping, or we're not getting access to the right people or the right network nodes, it's something that we always need to be sharp on and revisit.

But if you think about the cultural-touchstone founders of today's AI era, is there anyone more than Bret Taylor who represents this wave of AI applications? He's the godfather of AI apps right now. When you think about these really cracked young teams in AI, who do people look up to more than Brendan at Mercor and what they've done on the AI infrastructure side?

At least thus far, even with our strategy and the trade-offs that mean we can't invest in every single good round, we've still been able to attract and partner with—and I think build really great relationships with—a lot of the founders that people look up to in this AI wave.

I think our network thus far has been exceptional. But I do think it's an ongoing question, because if all there is left is these billion-dollar raises in order to build relationships with these people, then that's an ongoing question.

Harry Stebbings

Well, if that happens, then all of us will either work for the North Korean army or for Andreessen Horowitz. One or the other. [laughter]

Ev Randle

They're one and the same to me, Harry. They're one and the same to me. Marc and Ben. He said it. He said it. [laughter]

Harry Stebbings

You said the word “slip,” and then you said about Mercor. I'm in Mercor a little bit after you guys, sadly, but I did see the article that said the ownership Benchmark had in Mercor was obviously much less than traditional. I think it was about 10%, give or take.

I'm not asking specifics about the company. I'm just intrigued: How do you think about discipline around ownership in a new AI world where everyone's ownership is trending down?

Ev Randle

When I think about Benchmark's north stars—what we really care about in our investment strategy—and this relates to the ownership that we get in our investments versus everyone else gets in their investments, we have 2 north stars that we think about.

We want to be the highest-ROI and closest partner to the founders that we partner with. We want to be their most meaningful VC and partner from the moment that we partner with them until the company no longer exists. It can go public; we'll still be on the board, but until the company is no longer a going concern. And we want to generate the highest money-on-money returns that any of our LPs have in their venture portfolio.

But that's basically it. As the asset class evolves, there are ways to really serve those 2 north stars without necessarily having to get 20% ownership, or around there, every single time.

I think we're all believers—I think you're a believer, and we're certainly believers—that the outcomes are much, much, much larger in today's technology landscape than they were 10 or 15 years ago. There are more bites at potential $100 billion and trillion-dollar companies. There's just so many bites at the apple in terms of how you can both be a really meaningful partner to the founders and, 2, generate really exceptional returns.

So, in the Mercor case, yes, we didn't get high teens or 20% ownership, but I think if you talk to the Mercor folks about who their most impactful VC partner has been, I think they would say Benchmark. And I think that's going to generate unbelievable returns for our LPs. It's one of those cases where you can do the math on what the money-on-money return has been thus far from our ownership stake.

I think sometimes people confuse the inputs for the outputs at Benchmark. It's like, “Oh, they have to have 20% ownership, and they only want to invest at 100 post,” and all these things. I think that couldn't be further from the truth. We really have those 2 north stars, and whatever the asset class allows for in terms of the relationships that we build and how we can deliver the best for LPs and our founders, that is what we're serving toward and that's what we're optimizing for—not some vanilla percentage-ownership number.

Ironically, I think the last thing I'd say on that is, if you pulled any of our founders and said, “Do you regret the percentage ownership that you gave to Benchmark?” I don't think you'd get a single one of them to say, “No, we gave Benchmark too much.”

I think that's one of the really special things about the history of the partnership. It's my third week, so obviously I've contributed nothing to that. I'm just speaking to the amazing work that all of our current and historical GPs have done for the platform. But I also do think that even when we get—and we still often do get—really high ownership stakes, I don't think a single founder regrets that partnership.

Harry Stebbings

Ever. It seems that despite many years in venture, you still need a lesson from me, which is: regardless of what you did, it was all credit to you for the brilliance that happened before. [laughter]

Okay, it was me. Yeah, yeah, yeah. Cool. I remember doing eBay back in the day. Pierre and I were hanging out. We basically co-founded the business together.

Ev Randle

So good. Yeah, I do need to work on that.

Harry Stebbings

You said about—well, we can take this out if you want to—I pry, and you can take out one of your old partners. Delian is quite vocal about Benchmark. I mean, it's kind of the popcorn GIF, you know.

Ev Randle

It is.

Harry Stebbings

And you say about being the best partner. I think if you can answer it, it's helpful, because Delian's commentary doesn't help when he says, “Well, you just fire founders continuously.” Is that not slightly incongruous, being the firm that fires founders and also your best partner?

Ev Randle

I'll start with Delian's media strategy. Delian—and, you know, I love Delian. He's a close buddy of mine, so I hope he doesn't—I don't think he'll mind me saying this, because he certainly busts my balls more than enough.

Delian has always found an amazing media and Twitter strategy, which is: go find someone with a stalwart brand, or go find the biggest person on the playground and punch them in the face. People love it, it gets a lot of likes and clicks, it helps raise your profile, and it almost elevates you to their positioning. He's done it to Sequoia an immense amount. He's done it to Andre over the years, and we have not been spared the clickbait Delian tweets either.

No, I think every story has an immense amount of nuance in what happens between a board, a founder, and a management team, and there's an immense amount that goes into every single one of those decisions.

Again, I think times also completely change. In the '90s and early 2000s, if you think about or read about the Google investment, it's like Kleiner and Sequoia do the Google investment and immediately start searching for a professional CEO. It used to be the absolute norm. It wasn't even like, “Oh, we're going to push the founders out.” It was like, “No, you invest, and then you all together go look to recruit a CEO.”

2025 is immensely different than 2000. It's immensely different than 2010. It's even immensely different than 2015. The relationships between boards and founders have changed, and the relationships between venture firms and management teams and companies have changed a lot. I think it's for the better.

Obviously, I spent a fair amount of time in my career at Founders Fund. I love the idea of never firing founders and having them lead their companies from the moment you partner until the IPO and beyond. But at the end of the day, I'm also a believer in basic governance. If you do end up investing in someone who breaks the law or someone who's crossed ethical lines, it is your responsibility as a board member to potentially take remediation and action on behalf of all of the shareholders, all of the employees, and the company.

If you take a board seat like we do and you do have governance, you ultimately do have at least basic ethical and moral responsibilities. I think it's actually a convenience for Delian and some of the Founders Fund folks to absolve themselves of that weight and responsibility just by being like, “Oh, it's not part of our thing.” But I think it's almost out of laziness sometimes, more than it is some duty that they feel to founders.

Harry Stebbings

100%. I completely agree. I also think we're actually too kind on the flip side, where we now do not adhere to our fiduciary responsibility because we do not want to lose NPS so much. I'm on a company now that I'm invested in where the board is deliberately obfuscating their fiduciary responsibility just to preserve founder NPS in case they say something bad.

They are not looking after the cap table just because they do not want to piss the CEO off. That is a deliberate obfuscation of your responsibilities to protect shareholders and do what's best for them.

Ev Randle

100%. I completely agree. I also think the best founders don't want sycophants in the boardroom. They don't want GPT-4o in the boardroom telling them that everything they do is perfect, that they walk on water, and that they do nothing wrong. They actually want other adults in the room who are going to push them, spar with them, and make the company better.

Harry Stebbings

Can I ask you—you said about multiple bites at the apple. I wrote down “apple bites.” When we look at Benchmark over the years, Fenton did Airtable's Series C. I think Gecko was Series C. LangChain was a seed.

To what extent will you push the partnership now to expand the boundaries of what we call an A and what Benchmark does, to take more broad bites at the cherry or apple?

Ev Randle

Yeah, I think historically, again going back to those north stars that we talked about, when you think about the Benchmark investment strategy, it's helpful to marry the north stars that we talked about: every investment needs to be potentially absolutely astronomical money-on-money returns for LPs, and we want to be the most meaningful partner to our founders.

There are a lot of different ways to do that. So I think you marry those north stars with the personal investing style of each of the GPs. Each of us is 25% of Benchmark, and we work really well together; we’re a super tight-knit team. But each of us has our own styles. So even if Eric Vishria tends to love getting in right at inception and being the first check in, being really in the primordial-soup phase of a startup, it doesn’t mean that Chetan, Peter, or I are always going to operate exactly at that stage. We all have our particular preferences.

I think Peter does an amazing job of just following his founder conviction. He doesn’t think about stages. When he finds a Howie, when he finds a Brett, when he finds any of these founders, that is what guides him. He’s like, “I’m going to find a way to become the most meaningful partner to this founder, and I’m going to find a way for the investment to make them a lot of money for our LPs.” And so I think that is the mindset that we all have.

Historically, I’ve done more growth. I’ve focused more on Series B and beyond than on early stage. So will I do more Series A, B, or whatever we call it these days, than inception- or seed-stage investing, especially at first? Probably. But again, we’re guided by those north stars and finding founders that we really resonate with. Typically, we’re able to find ways to make it work on the back end and for our investments to generate exceptional returns.

So I think, unlike a huge mega-fund that’s like, “We have our Series A partners, we have our Series B partners, we have our Series C partners. They do fintech, they do healthcare, they do blah blah blah,” we don’t think about those things at all. We really just think about our north stars. I think we’re realizing more and more that there are so many different ways that you can have 10x, 20x, or 30x returns.

Harry Stebbings

I spoke to one of your former colleagues, and they said, “Ev is a phenomenal growth investor, but he’s a growth investor.” When I think about what matters at different stages, for me, in the early stages it’s people, and in the later stages it’s the market—actually, market sizing, depth, and just how big something can be.

We recently did Airwallex late at $4 billion. Incredible. But why? Because, dude, B2B payments—it’s a big market. We’ve got a lot more room to run. How do you think about that shift earlier? Are you nervous about making it? And what changes in what matters in your mind?

Ev Randle

I’ll be vulnerable with you, Harry, and say that this was a dinner I was having with Eric Vishria on our team. I was having a moment of insecurity when I was talking to him about the role of being a GP at Benchmark and saying, “Hey, I’ve mostly done growth.”

He was like, “Dude, Bill Gurley was a public-markets analyst before he came to Benchmark. You certainly are not going to be the most off-the-wall hire that Benchmark has made. That’s actually more par for the course for Benchmark.”

I think also, when you look at who you think are the amazing investors today, they transcend stage. If you look at Pat Grady, does Pat Grady think of himself as a growth investor, or does Pat Grady think of himself as just an amazing investor? Maybe he’s too humble. He’s a pretty humble guy, so maybe he doesn’t think about himself as an amazing investor at all. But I look at what Pat does, and I’m like, he finds incredible founders in investments that he thinks have an immense amount of upside, and he goes and partners with those founders.

I wouldn’t say that I’m an amazing investor yet. I don’t have the track record yet to say that I am, but that is my north star and that is my goal, and I’m going to work my ass off to do that. I think I’ve been able to tune my intuition, and even though I’ve used it to execute on growth-stage investing, if you look at a lot of the people that we think are growth-stage investors, they’re doing earlier-stage companies now and doing a lot of different stages at the same time.

Harry Stebbings

I thought Pat just did the deals his wife did. [laughter]

Ev Randle

I’m just kidding.

Harry Stebbings

He said it. He said it, not me, Pat. He said it. [laughter]

Ev Randle

Dude, I’ve known him for 10 years. I’ve said this shit. You can get away with that.

Harry Stebbings

I’ve said it for years. And this is why I think he’s just like, “I’ve never met Harry. Don’t know who this guy is. No idea.” A thing that does change, obviously, is price, and it does matter at different stages. How do you think about your own relationship to price?

Ev Randle

I think starting my career as a growth investor actually really helps me. One of the first investments that I did at Kleiner Perkins when I came back in 2022 was SpaceX at $150 billion. At the time, it was like, “Oh my God, $150 billion entry price.” The absolute numbers were, “Can we really make a good return on this investment?”

Having to go through the process of saying, “Hey, let’s not focus on just some large absolute figure. Let’s look at the TAM. Let’s look at their competitive position in their market. Let’s look at what happens if this goes right, and let’s look at the probability of it going right and who could potentially knock them off their perch to make it not go right.”

When you actually zoomed back and said, “Let’s take a few zeros off every single number—the TAM, the valuation, the revenue, everything,” if you were to look at it as a vanilla WidgetCo and reduce every number by 2 orders of magnitude, you’d be like, “This is an absolute no-brainer investment with a 10x upside case.”

I think doing later-stage investing can really help you think about price even at the earlier stage, because it makes you think, “I’m going to ignore what feels like a large entry price relative to the market.” If you’re in a market where everyone’s like, “Oh, the Series A market’s $100 million post-money, and if you do something at $200 million post-money, you’re an idiot because that’s 2x more expensive,” then you miss Rippling at $250 million.

The famous Series A that Mamoon did, where everyone’s like, “This guy’s out of his mind. He just paid $250 million for a Series A company that barely has any revenue.” Obviously, you miss Parker’s excellence, you miss the TAM that he’s going after, you miss the product sequencing and the differentiation that he’s going to build, and you miss the exceptional team that he had built.

I think if you can always try to isolate, “Hey, I’m not going to care about what’s going on in the market. I’m going to care about what matters for an investment and how much upside I think there is in a vacuum,” that matters a lot more. It’s something that you can actually get if you start your career in growth.

Harry Stebbings

Do you remember when Andrew Reed did Figma, and they were at $4 million in ARR and he did it at $400 million, and everyone was like, “This guy is 100x—what? Nuts.”

Ev Randle

One of the first 100x deals, I think, in SaaS. People were like, “100x ARR? What the hell?” And obviously it ended up being, I don’t know, 30x, 40x—an unbelievable investment.

Harry Stebbings

Do you outcome-scenario-plan, though? Because you said there about market analysis and trying to do top-down versus bottom-up. How do you think about that, and do you not worry that it can mislead you in the wrong direction?

Ev Randle

This is a lesson I think I learned from Mary mostly, and it’s one of my most important frameworks. You should understand what the base case, or the base-rate future, of the company looks like.

If you were an equity analyst and this was your 100th company that you were doing a little forward model for, and you weren’t paying that much attention, you’d be like, “Okay, just triple, triple, so it’s going to double, double, double,” or whatever. If you just did, “Hey, this is what the market thinks is sort of the baseline of what this company should do,” it’s actually extremely helpful to lay that all out and visualize that.

I don’t say, “This is the bull case, this is the base case, and this is the bear case.” I lay out what people are underwriting to. Let’s say at the growth stage people are underwriting to a 3x–5x. What does that look like on paper? And then how does that jibe with my mental framing of how important this company is going to be for its customers, for its market, and for the US economy, in some cases?

When you have a really strong intuition about a company in the middle of an inflection that’s about to absolutely explode, you look at the numbers that people are underwriting to in order to get to their 3x–5x, and you say, “This company’s going to absolutely smoke these projections.” It happens very rarely, but it’s really nice because it gives you the amount of conviction when you look and say, “Oh, everyone’s going to underestimate this thing.”

I think the other reason why models are not useful beyond that simple framing is that with every successful investment, you just feel stupid if you were to model Figma’s growth. Everyone would make fun of you. They’d be like, “Dude, come on. You’re just trying to get this deal done. Why would you model it growing this fast, for this long, this profitably? It’s never happened in SaaS. You’re crazy, or you’re just doing the IC a disservice.”

And so I think beyond being a yardstick to test your conviction, models aren’t that useful.

But for that, they're really, really good. I always remember Ernie from Carvana coming on and saying, “The amount of investors that would be like, ‘Hmm, the biggest car showroom is like a $300 million market cap, so this is a bad business.’” I always think market comps are such a dangerous thing to rotate your mind around when investing.

Harry Stebbings

100%. Or Figma with designers. I think David George—maybe it was on this show or another—talked about how he underestimated and understated the TAM of Figma because he went back to the team and said, “Well, look at how many designers there are in the world. If you just do the P times Q—the price times the quantity of designers—you don't get that big of a business.” Obviously, Figma then ended up penetrating a lot more roles within a company beyond designers.

People, product, and market: rank 1 through 3 in order of priority for you?

Ev Randle

The way you said it, honestly: people, product, and market. I think the people define everything else. They are the upstream engine that makes everything go. They're the most important piece.

Second, I think the product that the people build tells you so much about the people. It's the greatest evidence of the quality of the people: the product that they build.

Then market, third. Obviously, I am a believer that the market you're in ends up defining the size, and then the founder determines what percent of that size you can get in your exit. But I just think it's the most fungible. I don't think you can turn a non-exceptional person into an exceptional person. I don't think you can take a team that can't build a good product and make them a team that can build a good product. But you can change markets, especially early on in a company's life.

Most of the amazing companies and exit stories had some pivot along the road, whether you're talking about Slack or any of these others. I truly think that because it's the most fungible, market is the least important of those 3 things.

Harry Stebbings

You said that you can change markets. It was on this show where Doug Leone said, “Venture capital has transitioned from a high-margin boutique community to a low-margin, commoditized industry.” Tears ran down my face with my $400 million fund, which seems quite paltry. Do you agree with him in that statement?

Ev Randle

I think Doug might have gotten that idea from me. I'm half kidding. I wrote this piece back in 2021, and I think it's the reason why we first DM'd. It was called “Playing Different Games.”

Ostensibly, the piece was about the rise of Tiger. But what the piece was really about was the rise of a firm-level strategy that centered itself around increasing investment velocity as the core strategy. The idea was that you could make more money as a firm and as a GP if you invested a lot more money per year, even if you thought the forward returns were going to be lower on average per investment.

The idea was that Tiger was really the first one to take this idea and really, really run with it. They raised $15 billion or whatever they did in 2021. John Curtius basically deployed it all over that 18-month period.

At the very bottom—this is the ironic part of that piece—I said venture capital was going to bifurcate. On one end, you're going to have the Tiger model, which is high capital velocity, a lot of money out the door every single year, low touch, good prices—giving founders really good prices. On the other end, who did I have? I had Benchmark, ironically. That was going to be the craft: high-touch, the best signal that you can get if you're a founder, and very, very involved.

In the middle, I said we have the J.C. Penney funds, which are the dead zone. I think the crazy thing to me is what's happened over the last 4 years. Harry, how many firms have moved towards the Tiger side of the spectrum? Tiger died, and we got 6 or 7 more Tigers out of it in the last 4 years.

Obviously, a lot of these firms are running different strategies. Thrive and Founders Fund are doing extremely concentrated investments in really high-quality companies. You have the mega-funds, like Lightspeed and GC, doing their thing. It's a lot of different flavors of capital velocity—investment velocity—as their north star. But there are 6 to 8 firms now doing capital velocity, investment velocity, as their north star.

That was one of the reasons why I was really confident in high conviction and joining Benchmark, because if you look at how many of those tier-one brands have moved more toward the Benchmark side of the scale, there's basically none.

Harry Stebbings

Can I just push you? Do you think they are doing capital velocity as their north star? I think Josh would ardently push back on that from Thrive, and I don't even think you could apply it to Lightspeed and GC. I think they're solving for large checks, which is why they have to be in these mega-companies, because they need to deploy $500 million in some cases. I don't feel like they're solving for velocity in the same way that Tiger was.

Ev Randle

I do. I would push back. There are 2 things. Obviously, there are different subsegments of this now. So let's take the actual mega-funds, the people that I think are most following this strategy. If you were to say, “Well, for GC or Lightspeed or some of these mega-funds, is investment velocity the north star of the strategy?” to answer that question, I would have you go talk to the principals, the junior partners, and the associates at those firms.

You interview 10 of those people, and you tell me that capital velocity is not the north star of those firms, and I will cede victory to you, Harry. When you actually look at what's going on at the ground floor, it doesn't matter what Ravi Mhatre is saying. When you actually look at what's going on with the people who are actually doing these investments, they feel it. They feel that they need to get money out the door, and that's the only way that they're getting promoted up those organizations.

On the Thrive side, I agree with you. I think Josh would resent that characterization, and it was probably too blunt of a characterization. But again, I think subconsciously, as a firm, it's very, very hard to care about something that's not your main product.

When you're writing billion-dollar checks, that is your main product. That's what's going to make you all the money. If you put $3 billion in OpenAI and it's going to turn into $12 billion, it is unbelievably hard, whether it's conscious or not, to then go and say, “We're also going to be the best Series A firm, and we care just as much about Series A,” because why would you?

Ninety-five percent of the profit that you're going to make and the money in your pocket is going to come from the billion dollars you put in Databricks, the $3 billion you put in OpenAI, or any of those things that have ended up being your main product.

So I think you just can't focus on everything and give it your all. Even though it's less conscious for firms like Founders Fund and Thrive, it has become their main product and their main focus subconsciously.

Harry Stebbings

If we accept that, people then often move to the idea that they're going to do worse. They accept a lower rate of return because the Norwegian sovereign wealth fund wants 4% a year, and so that's what they're going for.

Then you actually look at outcome scenarios and outcome sizes: OpenAI, which will be a $1 trillion company next year; Anthropic, which will definitely be a $600–700 billion company; and Cursor, which hits $1 billion in ARR insanely fast. Outcomes are so much larger than we ever anticipated. I think they will make a huge amount of money because the outcome sizes have continuously expanded. Do you agree?

Ev Randle

Oh, yeah. They're all going to make an immense amount of money. But again, let's change the framework from absolute dollars to what you're giving each stakeholder of the 3 legs of the venture stool. Venture has 3 stakeholders: you have your LPs, you have your founders, and you have each other as GPs within a firm.

I don't think, as Ravi, Hemant, or even Ben and Marc at this point, that they can go to LPs—one of those legs of the stool—and say, “Hey, this basket of funds that we're making you invest pari passu across, we're going to get you 5x net on that.” I don't think they can say that, or they at least can't say that with a straight face. If you look at the recent return data, I think it suggests that.

I think they'll be able to make an immense amount of money on an absolute basis, but I think a lot of these LPs are in venture to make high money-on-money returns. They have PE for the low-return stuff, and they probably get better liquidity from PE. They're here for the high money-on-money returns.

This is one of the reasons why I'm extremely excited about Benchmark's competitive position in today's market, because we can go to LPs and say, “Hey, we're shooting for higher than 5x. We have the historical track record to back it up, and we have the fund sizes to back it up as well.”

I mean, you had Miles from Carnegie Mellon come on here and do the awesome math, the very clear math, of, “Hey, do you know how hard it is to return 4x net on $8 billion, $10 billion?” It is immensely hard, and it defies the laws of physics.

So, I think there's a difference between whether they're going to make a ton of money and whether they're going to produce the returns that LPs really want this asset class to produce. Those are 2 very, very different things. But for now, the rubber won't meet the road because, as you mentioned, there's just so much global demand from LPs for exposure to private technology, and they're happy to take lower returns. So I don't think there's any end in sight, but I think on a relative basis, between all of these different constituents and all these different GPs, there's a huge delta and huge differentiation between who can actually produce venture-like returns.

Harry Stebbings

Tiger. Mhm. I think Tiger will do much better than anyone anticipated when you look at their positions in Scale AI, OpenAI, and the protection they're going to get from a lot of liquidation preferences that they actually have, meaning a lot of them will get 1x plus a little bit, maybe. Do you think I'm wrong and being too optimistic, or do you think the whole ecosystem shat on them a little bit too early?

Ev Randle

I completely agree. I think Tiger's going to end up much better than anyone thought they were going to end up. I jokingly texted some of my friends, and I was like, “Hashtag justice for John Curtius.” I actually think everyone put him as kind of this pariah, the personification of the excesses of 2021, but, again, it might have proven—his strategy might have proven prudent and the correct strategy all along because they got really big stakes in Databricks. They invested in OpenAI very, very early. I think they have a large position in OpenAI. They actually have large positions in a lot of these amazing companies that could continue to compound 5x more.

Again, they'll probably benefit from the liquidation preferences and the beauty of having preferred stock for a lot of the things that don't work. In the fullness of time, I'm sure it's not going to be the best portfolio that any LP has ever gotten, but I definitely don't think it's going to be a money-incinerating fund by any means. I actually think it might end up being pretty okay once Databricks is a $400–$500 billion company and OpenAI is a multitrillion-dollar company.

It is hilarious. I do think people gave them too hard a time, probably, and I do think they might end up being okay.

Harry Stebbings

I love that hashtag. I'm sure John will listen to this and be like, “Yes, thanks, guys.” [laughter] When we were chatting about multistage funds before and going back and forth over email, you said how it sucks to be in a mega-fund. Why does it suck to be in a mega-fund, Ev? From the outside, building a firm, having mega-fees, mega-offices, Fiji Water in unlimited supply, [laughter] and more EAs than you have investors seems pretty good. Can you help me out here, dude?

Ev Randle

Okay, so maybe I should caveat by saying all on a relative basis, these people definitely aren't going to the coal mines and laboring all day under the hot sun or something. But I know I have so many friends at these funds, and some of them are probably going to kill me for this part of the conversation. I've mentored a lot of people who are either coming out of private equity or thinking about moving firms in venture growth, and one of the first things I say to them is, think about the day-to-day that I know exists in a lot of these mega-funds.

If there are 50 investors, if you come in and you're the 23rd partner at ICONIQ or one of these places, what companies do you get to cover? That's the first problem: you end up getting a very small sliver of the overall market because so many people have already laid claim and are the point person on the very best companies with the very best founders. So you end up being focused on this local maximum where you're like, “Okay, I have 30 pretty good companies where I am the point person on the relationship.”

I also really need to do investments because that's how people get promoted here. I really need to get a couple of these in the portfolio. To me, sometimes it just feels like a different job than the craft of venture capital, where you're almost playing the lottery. You're like, “Okay, I have these 30 names that I own. I'm going to try to do 2 of them, and then if 1 of them hits and is a huge success, then I'm going to get tenure and I'll get to be a GP, and then I'll get more coverage, and then everything will be okay.”

But it feels a little bit more like investment banking or a large private equity firm than it does what people think of when they think of being at a venture capital firm, which is meeting really interesting founders, building genuine relationships with them, and only doing the very best investments and partnerships. I just think it's really gotten away from that, and I think it's inevitable. Again, it's to that Conway's Law point of venture capital firms. It's just based on the fund sizes and team structures of these places.

Harry Stebbings

I agree. And if they get fed up with the private chefs and the Aesop soap in the bathrooms, then they can always go and build their own funds and toil away and do the painful, hard yards, in which case I wish them well. [laughter] I do agree with you there. I have to ask you—you mentioned doing those 2 deals out of the 30. The first deal is really hard, dude. How do you think about your first deal at Benchmark? You can fall on 2 sides. Just get it done; it may not be your best, but it's kind of like the first check. [laughter]

Just get it done. You promised me spicy, Harry, and you delivered. You delivered. [laughter]

Harry Stebbings

Or it's like, “You know what? I'm going to wait until I find the perfect company, and only when I find the perfect company am I going to commit to it.” Which side do you sit on?

Ev Randle

Yeah, my first investment. I won't lie to you, Harry. The weight of being a Benchmark GP exists. I definitely feel it. You're like, “Wow.” The people who have walked these halls—Bill Gurley, Mitch Lasky, Matt Cohler—incredible people with incredible track records, and you feel a lot of pressure to live up to the history of this place and the history of the brand.

I think I got really good advice. I won't name the partner, just so no one can trace back to what company they're talking about. One of the partners coming in was like, “Look, there's going to be nothing better for you than if your first investment sucks, because once you do 1 and it fails and you realize it's not the end of the world, life goes on, LPs still love us, and you're not fired, then you feel really comfortable and you start getting into a really good rhythm.”

Whereas if your first one's pretty good or looks really good, you can then feel even more pressure on the second one. So they were like, “There is something beautiful in having your first be a failure. It doesn't mean that I'm going to be looking for a failure out of my first investment, but it was really relieving, and it was amazing advice to get: it's all okay, and if anything, failing can help you feel more relaxed as you go up to bat the next time.”

Harry Stebbings

Just do 1 of them. [laughter]

Ev Randle

Exactly. Yeah. I'll do a Swedish satellite antenna company or something that Delian did, and then I'll be guaranteed a zero. [laughter] Having said that, obviously, Delian—I'm joking. Delian's track record is pretty good. You look at Sword Health, where you're like, “Really? That's a non-obvious pick,” and, “Wow, what a business.”

The thing I always give Delian crap for is that he does have an incredible track record, but a lot of it is software. He loves to shit on software companies and people that invest in software and all these things. And I'm like, “Dude, you sourced the seed of Ramp. Khosla owns an ungodly amount of Sword Health, which is an amazing company. And, yes, you obviously incubated Varda, which is a great company as well, and all these things, but a lot of your track record is in software.”

But no, honestly, I think a lot of people at Founders Fund have very underrated track records. I think Mathias Vantiani—I think he's the most underrated venture capitalist that exists today. He's so quiet. He's never online boasting about himself or anything, but DolarApp, Trade Republic—

Harry Stebbings

Why? [snorts] I met him when he was in London, and we had dinner, and he was doing the Trade Republic deal then.

Ev Randle

Yeah.

Harry Stebbings

Why do you say he's the most underrated?

Ev Randle

I just don't think a lot of people know about him. He's not online. I think he might—

Harry Stebbings

What's he got to his name, though? Trade Republic. So, Trade Republic, DolarApp, which I'm sure you know, Inter down in Latin America, and then he's instrumental—the growth team over there is quite small.

Ev Randle

You know, you got Napoleon, you got Matis, and you got a few other people like Amin. He's just played a pretty big role in a lot of the really good growth investments as well. So I just think, for someone who is ostensibly a growth investor, he's done a ton of really good early-stage things.

Harry Stebbings

Yeah. And he's humble and nice. He's like one of those perfect kids at school. You're like, “Oh, God.”

Ev Randle

I don't know about nice. Some people don't think he's very nice, but he's a sweetie at heart.

Harry Stebbings

Ouch. [gasps] Do you know what? I spoke to Henry from Stord before, and he said, “You got to ask, what's the most ridiculous story you remember from the 2021 times?”

Ev Randle

Oh my gosh. There were so many absolutely absurd ones. Again, I was at Founders Fund, so we were spending a fair amount of time in Miami. I remember distinctly, I think it might have been the 3rd Miami Tech Week or something. I think it was December of '21 or maybe January of '22, when it was pretty clear that the bubble was bursting from COVID and equity valuations were starting to get slashed 30% to 40% in public markets.

We were at some very decadent party where I think Vanilla Ice was performing or something. We were in Miami, and there were all these crypto people. I was just like, “Oh my God.” I was sitting around, and I was like, “This reminds me exactly of the scene in The Dark Knight Rises where Anne Hathaway is dancing with Bruce Wayne, and they're at this fancy party.” She's like, “I don't know how you could think that you guys could do this glamorous, decadent stuff while Gotham is burning.”

I was like, “Wow, we are at that party today. Gotham is burning. It's about to come to us, but for this time, this is the last decadent thing that we're going to be doing.” I just feel like 2021 was all like that. There were so many ridiculous things where I look back and it's like, why did we ever think, 1, this investment was a good idea, or 2, why were we doing these very decadent things in Miami? It just seems ridiculous in hindsight.

Harry Stebbings

I am so here for a Dark Knight reference, by the way. I love that scene. Well done, dude. Love it.

The final one before we do a quick-fire: you can think that Gotham is burning today, actually, in a lot of ways when you look at the state of the world. You can also look at it and go, “Christ, we're so early in the adoption and inflection of AI that this is just the start.” I hold these 2 opposing thoughts in my mind, and I'm kind of stuck on which one to adopt. How do you feel?

Ev Randle

I feel the same. I think today, relative to the dot-com boom and bust, if you really think deep down about what happened in that era—let's say you did the Amazon Series A, for example—there was a point in time 4 years later where it had IPO'd and then was down 80% from its IPO. But if you had held to today—and I forget if the Amazon Series A was $40 post or whatever it was—you went from $40 post to multiple trillions of dollars in value.

I think today is very similar in that there's going to be a ton of companies that are pump fakes that end up going to 0 or go down 90%. But I think it's really important to position yourself so that you can survive the inevitable crash on the other side. If you end up in these really incredible companies that still endure and define the next 20 to 30 years of technology, you're going to be paid in so many multiples of what you would get in a normal cycle.

We think and stay up all night thinking about, well, what is going to be the Amazon, the Google, and the Microsoft of this era? I think it also goes to our strategy. We're like, let's constrain our fund sizes. Let's be careful about what we do so that we don't get too far over our skis, where we can easily weather a crash and LPs aren't going to go fleeing once there's a crash because we've been very careful with our capital and we haven't incinerated billions of dollars or something like that.

Harry Stebbings

I think Benchmark could invest in Elizabeth Holmes doing Theranos Take 2, and you'd still get LPs queuing out the door, thinking that Benchmark has seen something no one else has seen.

Ev Randle

Maybe we should. Maybe we should. I think she's still in jail, but whenever she comes out, maybe we should.

Harry Stebbings

It's about being contrarian and right. The terrifying thing is she has quote-tweeted me agreeing with me more times than I like, and I'm always like, “This is a bad sign.”

Ev Randle

You're like, “Wait a minute. Apparently that's not her.” At least, I saw something on Twitter where someone's impersonating her. Apparently, she doesn't actually have access. So maybe it's one of your superfans.

Harry Stebbings

That's reassuring if so, because I'm always like, “[Expletive], delete tweet, delete tweet.”

Dude, I could talk to you all day. I want to do a quick-fire round. I say a short statement, and you give me your immediate thoughts. What have you changed your mind on most in the last 12 months?

Ev Randle

I think, honestly, the quality of the AI cloud business model. Again, I was very negative on it when CoreWeave was first coming up. I was like, “Oh, this is reselling a commodity.” I actually think there's a lot of interesting things that people are doing, and the demand for AI inference is just so astronomical that, at least for now and for the next few years, I think it's going to overcome all business-quality and business-economics concerns.

I think at some point CoreWeave and all these things will probably go down 70%. But obviously, I thought that back when it was raising at $3 billion, and now it's a $60 billion public company where the investors have been able to get liquidity. So I was definitely wrong.

Harry Stebbings

Which pumped company today will have the steepest fall, do you think?

Ev Randle

We're investors in Cursor. I am not a believer in some of the companies that have raised a ton of money and have not released a product or haven't had products that a lot of developers are using. I'm a huge believer that you have to get developers' hands on the product.

I think there are a couple of companies that have raised billions of dollars and are like, “We're going to build the best thing ever,” but they don't actually have products that a lot of developers are using. I think that's going to be a rude awakening, because AI products get better via usage. Oftentimes, if you have the right environments and Claude Code, Codex, and Cursor, the companies and apps with the highest amounts of usage are going to improve the fastest and leave everybody in the dust.

Harry Stebbings

Tell me, you've got BOND, you've got Founders Fund, you've got KP—all fantastic firms—but if you had to put your money in 1 firm for the highest cash-on-cash, which one do you go with?

Ev Randle

Maybe Founders Fund, just because they have a very unique ability to incubate companies. When you think about Anduril, the fund that Anduril is in has got to be such an ungodly return on that capital.

I think it's become a really, really competitive market. The only way that you can fend off how hard it is to buy equity is to sell equity or produce equity. The way you produce equity is by incubating companies. Every few funds, or every 5 to 10 years, they've incubated an unbelievable company. Obviously, Scott Nolan over there is the most recent to do it. I think that's just a way to get differentiated returns that are hard to produce from anyone else.

Harry Stebbings

Totally agree with you. Phenomenal. When you look back, no one has so reliably had such good-performing funds at scale—them and Index. Yeah, unbelievable there.

Okay, totally get you. Can you take me to the moment where you said in your head, “Yeah, I'm going to do Benchmark”? Was it a dinner? Was it a coffee? When did you go, “Yeah, I'll do it”?

Ev Randle

I think I knew I wanted to join Benchmark when I was 22, entering the industry. Honestly, you enter the industry and you read eBoys. I'm reading all of Bill Gurley's blog posts. It's a mythical place.

You enter the industry as a young investor and think, if I really work my ass off and get pretty lucky, maybe one day I'll be able to compete for a seat there. So when it comes true and they give you the envelope with the offer in it, it's almost like a childhood fantasy of joining the Yankees or something. It's super surreal.

Obviously, the people matter most, and that was really important during the recruiting process. I felt unbelievable alignment and really a level of closeness with Peter, Eric, and Chetan. But beyond that, I think the firm itself is just one of these mythical seats that you dream about from the day that you enter the asset class.

Harry Stebbings

It's like Real Madrid and going to the Bernabéu. I'm a—

Ev Randle

You tell me. I played FIFA in high school, but I don't know. I think it's like playing for Real. You grow up watching Ronaldo and you're like, “Oh my God, I could go play for Real one day.”

Harry Stebbings

We all chat shit that I'm so happy at Chelsea. I love being at Man U.

And then Ronaldo gets the Real Madrid offer and you're like, “Yeah, Old Trafford's not so great.” [laughter] Not so great, is it?

Ev Randle

Not as sunny as...

Harry Stebbings

No, I totally love that. Tell me, what's the biggest miss for you, dude? And how did that change your mindset?

Ev Randle

Biggest miss, we've talked about it a little bit, but the biggest miss has to be OpenAI at $32B. I think, obviously, it was kind of a hard-to-fill round. Obviously, they did it, but it was very non-obvious at the time, and it was just one of those ones that is so unbelievably painful because you missed the forest for the trees.

You let the structure thing and the dilution thing trick you out of investing in what is maybe going to be the largest tech company of all time. And also, just being in that ecosystem, it's such an unbelievable group of people that even if it was just an okay return, you'd still want to be involved with Brad and Sam and all the people over there that have defined a lot of what the AI industry is today. That one hurts to this day.

Harry Stebbings

What do you think the biggest threat is to Benchmark being successful in the next 5 years?

Ev Randle

I think the thing that is most dangerous, and the biggest risk to Benchmark not being successful over the next 2 decades, is stasis. I think we need to be dynamic. We need to always be evolving with the asset class while staying true to our North Stars.

I am very much a believer that we don't have to leave our North Stars or bastardize our true north in order to continue to be involved with the very, very best companies. But at the end of the day, being involved with the very, very best companies is the currency by which we all live in this asset class. That has to be the most important thing.

If there's ever a situation where we're letting our North Stars, or we're letting something else—the tail—wag the dog, with the dog being getting involved with the very, very best founders building the best companies, that's when we need to reevaluate our strategy and what we're doing.

Harry Stebbings

Penultimate one. Are you ready to lose all of your friends in your new partnership? Who's the best picker in Benchmark?

Ev Randle

I'll go with a data-driven one. Honestly, I think Eric is the most underrated picker. When you look at some of the things he's done, he's just done some really low-key things that have ended up being unbelievable.

He'll have Cerebras, which will IPO at some point in the future. That's going to be an unbelievable company. He has a lot of these sneaky absolute bangers. But if you go back and look at the percentage of Series A investments that ended up being generational companies, I think it's got to be Peter.

Peter also has the advantage of being in the game for 20-plus years, but it's got to be Peter.

Harry Stebbings

I also think Peter is possibly the greatest salesman I've ever met. His ability to manipulate language to sell his position is really beautiful.

Ev Randle

I went into my first pitch with him in my first week, and my jaw was on the floor more than the founder. I was like, “I have so much to learn from this guy.” I've never seen someone who practices the craft of infinite EQ and hospitality and just wordcraft like he does. It's unbelievable to witness.

You weren't like, “Wait a minute, this is just like being in a room with Delian.” [laughter]

Harry Stebbings

Delian's more of a blunt instrument, I would say.

Oh, dude, he's going to [expletive] either hate me or love me for this show. I have no idea.

Ev Randle

Probably a mix of both.

Harry Stebbings

Dude. Final one for you. I like optimism. What are you most excited about for the next 10 years?

Ev Randle

I think over the next 10 years, the only thing that's ever made me less of a capitalist than I am is realizing that capitalism is really, really good at optimizing things and making them more efficient. When the laser beam of capitalism moved from cars, TVs, and electric goods, making them cheaper, to the minds of people, I think it actually had a lot of negative consequences.

When social media had its rise, the thing it was optimizing for was, “How do we get people to glue their faces to the screen for as long as possible?” I think that's actually been a significant negative and probably the only negative that technology's had on society thus far.

When we look at what's happening in AI, Peter Thiel always talks about how the most important thing for keeping our society harmonious and functional is growth. As soon as this pie stops growing, things get a lot worse and people treat each other a lot worse because it's zero-sum. I think, unfortunately, you're seeing a fair amount of that where you live, Harry.

When you think about the determinants of GDP growth being basically population and then GDP per capita, and how much the birth rate is slowing, I think AI is going to be unbelievably good at continuing GDP growth. I think continuing GDP growth—the growth of the economy, continuing to grow the pie, having the middle class grow, and having everyone feel more and more prosperous over time—is the single most important variable in continuing a harmonious, functional society. I think it's going to do that in spades over the next 10 years.

Harry Stebbings

You know, Ev, honestly, I love doing this show. But I've done it for 10, 11 years, and not every show is as brilliant as this, by any means. It's shows like this that make me go, “This is why I still love doing what I do.”

So thank you for being so brilliant. Seriously, this was so much fun, and I couldn't be more thrilled with this show.

Ev Randle

Thank you, Harry. It's been so awesome just to hang with you, and next time we'll do a pint in London when I'm out there.