20VC: Is SaaS Dead in a World of AI | Do Margins Matter Anymore | Is Triple, Triple, Double, Double Dead Today? | Who Wins the Dev Market: Cursor or Claude Code | Why We Are Not in an AI Bubble with Anish Acharya @ a16z

Summary

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The Twenty Minute VC (20VC): Is SaaS Dead in a World of AI? | February 9, 2026

Guest: Anish Acharya (GP at Andreessen Horowitz/a16z)
Hosts: Harry Stebbings and Chris O’Neill
Episode Focus:
The rapidly evolving role of SaaS, enterprise software, and venture capital expectations in an AI-first world; the future of market defensibility, margins, and product innovation; who wins in the new application stack; and why Anish believes we’re not in an AI bubble.

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Episode Overview

This energetic, insightful conversation with Anish Acharya from a16z dives into critical questions facing tech entrepreneurs and investors in 2026:

• Is the SaaS business model doomed or transforming in AI’s shadow?
• Do margins, defensibility, and network effects still matter?
• Who wins: incumbents with scale or agile startups?
• What does true product-market fit look like in AI-native categories?
• Are we in a bubble—or at the starting line of new markets?

Through real data, anecdotes, and debate, Anish delivers contrarian takes and practical wisdom for founders, investors, and anyone obsessed with the future of software.

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Key Discussion Points and Insights

1. Location, Scale, and the Network Effect of Cities

• SF’s Enduring Advantage:
  • Anish argues that “cities are the original network effect” for tech. Despite the spread of talent, “the benefit of being in SF is enormous...there's something different about saying, 'I'm going to give everything else up and be singular in my focus and move everything to SF to make it happen.”* (05:06)
• Tel Aviv’s Unique Scale:
  • The market's small size “forces ambition outside domestic borders,” a contrast with the UK or other larger countries. (06:00)

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2. Venture Scale: Is $3–5B Still Enough?

• While $3–5B exits are “extraordinary,” Anish stresses that to build “trillion-dollar companies”—the new bar—you need assumptions and ambition from day one that break outside national markets. (07:12)

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3. Is SaaS Dead? Are Recurring Revenues Durable in AI?

"SaaS Apocalypse?"

• “Software is completely oversold. I heard it called SaaS Apocalypse today...the story that we’re going to vibe code everything is flat wrong and the whole market is oversold software.” —Anish (08:06)
• Even if you “coded your ERP and payroll yourself, you only save 8–12% of enterprise spend. Better to point the ‘innovation bazooka’ of AI elsewhere.” (08:06)
• Switching Costs Are Plummeting: AI coding agents mean “the cost of transitioning from one SaaS provider to another going dramatically down...That is how coding agents show up in enterprise software—decreased switching costs, more customers, less hostages.” (10:39)

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4. Who Wins: Incumbents or Startups?

• Incumbents have real strengths and distribution. Anish (referencing Alex Rampell):
  • “Will the incumbent acquire innovation before the startup acquires distribution?” (11:19)
  • Startups win in truly new (native) markets created by AI; incumbents simply improve in their existing categories. (11:47)
• Example: “AI-assisted movie making” is a new category with no incumbent—odds favor a native startup over, say, Adobe. (11:47)

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5. Application Layer vs. Foundation Models: Where Does Value Accrue?

• The application layer (“apps companies”) is undervalued in the discussion:
  • With so many strong, competitive models (‘foundation models’) in lockstep, apps that orchestrate, aggregate, and customize multiple models—e.g., Cursor for devs—create significant value, especially when users want to leverage best-of-breed for unique workflows. (12:48–14:47)

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6. Fragmentation Over Consolidation: Durability of Revenue

• “We massively overestimate the durability of revenue of AI companies…there’s a developer and developer-adjacent archetype for whom Cursor is perfect, and Codex as a CLI or cloud code will each find their own market fit.” (15:03)
• The market won’t look like a winner-take-all Uber/Lyft. Instead, it's more like cloud: an oligopoly with reasonable margins and specialization. (16:04)

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7. Moats, Defensibility, and Hostages vs. Customers

• Moats aren’t gone, but change:
  • True network effects—like Airbnb—are still gold.
  • Proprietary live data is now more powerful than static “data network effect” moats. (24:47, 25:52)
• “If you actually have an SAP system, you are a hostage of SAP…Now with coding agents, the complexity of transitioning…is dramatically lower.” (10:39)

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8. Margins, CAC, and LTV in the AI World

• Margins still matter, but “blend” differently in AI:
  • AI product margins are lower—often driven by costly trials and inference costs.
  • “Blended margin for AI native companies tends to be worse, but the form of distortion is healthier than five years ago—cost is mostly subsidized by big tech.” (27:19)
• CAC via free trials costs should be treated as marketing; look at power user margin and behavior for “durable margin.” (29:44)
• Retention is critical: “M2 is the new M1; tourists come in at month one, but true retention beyond that is the key metric.” (30:49)

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9. Are We in an AI Bubble?

• “This is not a bubble and it’s good that it is…Every time OpenAI brings on new capacity, all of that supply is 100% spoken for. Supply is not ahead of demand. Prices are rising, not compressing, and any subsidization is intelligent.” (31:22)

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10. AI-Driven Productivity; Beyond Just SaaS Cost Cutting

• “We’ll see the transition of spend from 12% SaaS to human labor budgets. Models can be empathetic in customer support or charismatic in sales—the lines are blurring.” (32:41)
• AI is an enabler for both reducing low-value rote tasks and expanding human ambition. (56:45)

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11. Market Size: Always Underestimated

• Investors repeatedly underestimate how large markets can be (“inertia is the best mental model in the universe”).
• Example: Credit Karma seemed niche, but people love to check their credit status—it became enormous. (37:54–39:40)
• “When you have a formidable founder making tremendous nonlinear progress, you have to tiebreak in the direction of them doing it forever.” (39:44)

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12. Winning Deals, Ownership & Price in Venture

• Anish on never losing a deal at a16z:
  • “We have to see 100% of the deals in our domain and win 100% of the deals we go after." (74:28)
• Price at sub-$100M valuations is less a focus—ownership matters more; at high prices, it’s the follow-on round risk, not the dollars in. (43:09–44:26)

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13. Triple Triple Double Double: Is It Dead?

• Not dead: such growth is still remarkable, but some markets (with fast cycles and new primitives) see even more explosive growth. Others—like ERP—move on slower cycles. Context is everything. (45:18)
• “I hate it when investors are flip about this. Getting to a million in revenue from non-friends is so hard.” (46:27)

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14. Founder Qualities & Repeat Entrepreneurs

• Enterprise: Repeat founders in their domain = huge advantage.
• Consumer: Beginner’s mind, willingness to be embarrassed—sometimes better.
  • “Once you’ve sold a company, you’re less likely to work on something that sounds silly—sometimes that hesitation holds you back.” (53:40)

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15. Product Cycles, Agents & the AI Stack

• “Agent maximalist” hype is premature:
  • You still need humans in the loop for exception handling and because instructions are often vague. (55:59)
• Where agents work best: BPOs and highly-structured, well-specified tasks.
• For ambiguous or creative work, human intuition is still critical for global maxima, not just local ones. (57:58)

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16. Open vs. Closed Models: Pragmatism Reigns

• “Not at a point in the cycle where companies are focused primarily on cost…‘Open’ sometimes has unique benefits, but ‘closed’ is still more advantageous for most.” (59:45–60:50)
• Cost is an issue, but capability gains are more important right now—price takes a backseat to value unlocked. (61:37)

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17. Kingmaking & Value Extraction from Investors

• Kingmaking is real in some cases (YC for early enterprise, e.g.), but “you can’t anoint a loser as the winner.” (64:47)
• Best founders know how to “maximally leverage” their VCs, especially agencies like a16z that can provide distribution and brand. (65:34)

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18. Most Memorable Quotes

• On ambition and cities:
  “Cities are the original network effect. For this moment in technology… the benefit of being in SF is enormous.” — Anish (05:06)

• On switching costs:
  “Some companies have hostages, not customers. Coding agents cut switching costs—less hostages, more customers.” — Anish (10:39)

• On moats and defensibility:
  “Networks are the gold standard. A network effect product is incredibly powerful.” — Anish (24:47)

• On the AI bubble:
  “It’s not a bubble and it’s good that it is. Every time [OpenAI] brings on capacity, that inference supply is 100% spoken for.” — Anish (31:22)

• On being “right”:
  “Your process doesn’t matter as long as you’re consistently winning… be right a lot.” — Mark Andreessen (40:16 recounted by Anish)

• On the future of spending:
  “Software is going to eclipse many parts of our discretionary spend. We talked about companionship, entertainment, therapy, healthcare, professional and education… there’s tremendous area for software to expand into.” — Anish (63:44)

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Notable Moments & Quotes with Timestamps

• On what’s required to “win” an AI-native application:
  “If you want to win in an agentic world, you have to own the tools, the workflow and the data... But ambiguity and exception handling still require humans.” (57:50–57:58)

• On open-source AI models:
  “There are idiosyncratic reasons we choose open models... [but] maximizing ambition and fulfillment is still more important than taking cost out.” (59:36)

• On AI and ambition:
  “Our circumference of ambition is only going to go up… execution or expertise is not a constraint any longer.” (56:45)

• On product-market fit missteps:
  “If there’s a mistake I’ve made, it’s being too casual about product-market fit... investing with self-deception is a mistake.” (68:30)

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Key Segments (Timestamps)

• SF’s Network Effect and ambition — 05:06–06:50
• SaaS market oversold & innovation focus — 08:06–09:13
• Switching costs & hostages vs. customers — 10:39–11:14
• Incumbent vs. startup innovation cycles — 11:19–12:38
• Application layer value — 12:48–14:47
• Moats, defensibility & margins — 24:47–29:34
• AI bubble skepticism — 31:22–32:23
• Market size underestimation & inertia — 37:54–40:06
• Winning deals, price, and ownership — 43:09–44:26
• Repeat founders vs. beginners — 53:40
• Agent overhype and human-in-the-loop — 55:59–56:39
• Open vs. closed models — 59:45–60:50
• Founder-VC value extraction — 65:34–67:03

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The Host's and Anish’s Tone

• Energetic, candid, and often self-deprecating, with intense respect for founders’ craft and humility about venture’s unpredictability.
• Anish leverages clear data, personal anecdotes, and real founder stories; generous with actionable advice.
• Lots of rapid-fire exchanges, some dry humor, and willingness to challenge conventional wisdom.

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Final Takeaways

• Anish is bullish on AI—but against the “doomer” SaaS narrative or belief that defensibility is dead.
• AI is shifting what creates value: lower switching costs, new types of moats (live data, power user engagement), and power users who willingly pay much higher prices.
• Venture may look different in metrics and speed but some truths—a formidable founder’s inertia, authentic product-market fit, networks—remain eternal.
• Huge new markets are being formed at the application layer, while foundation models become more interchangeable.
• Founders should maximize VC resources, but must always “build something people want” and try every product themselves.
• No, this is not a bubble. In fact, we’re just getting started.

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For more detail or to re-listen, visit www.20vc.com or search for this episode in your podcast player.

Transcript

[Anish Akaya]

You have this innovation bazooka with these models. Why would you point it at rebuilding payroll or ERP or CRM? The general story that we're going to vibe code, everything is flat wrong and the whole market is oversold software. Now an interesting topic that's not discussed is the cost of transitioning from one SaaS provider to another going dramatically down. I don't think we're allowed to believe in luck at Andreessen. We have to see 100% of the deals in our domain and that we win 100% of the deals that we go after.

[Harry Stebbings]

This is 20 VC with me, Harry Stebbings. Now one of the most played shows that we've done recently was Alex Rampell at Andreessen. They are on a freaking tear. And I'm so excited to welcome another incredible GP from Andreessen today. Anish Akaya, GP at Andreessen, where he leads consumer and fintech investing at Series A. He serves on some incredible boards, Deal Mosaic, Clutch, Titan, and one that I really want to invest in, Happy Robot. And he's led early bets in some incredible companies like Runway and Carbonated. Before Andreessen, he found and sold two startups, Snowball, which was acquired by Credit Karma, and socialdeck, which was acquired by Google. And he also scaled Credit Karma's US car business to over 100 million members. But before we dive into the Show Today, over 80% of Fortune 100 companies are running their businesses with Airtable. Airtable combines AI with the scale of an award winning, infinitely flexible, no code system. A platform where you can see all of your data in one place and use it to make really big picture decisions. Think of it like mission control for your company. Airtable goes beyond organization and automating repetitive tasks. It lets you use your data to inform strategy, monitor progress and take action. Every cell is capable of performing hundreds of AI powered tasks like web research or localization and using those results to inform and update hundreds or thousands of other cells and workflows in real time. Unlock the true scale of your [e-mail] 20VC. Airtable, the infra structure of innovation. And just like Airtable organizes your workflow data, Metaview organizes your conversation insights. This episode is brought to you by Metaview, who says hiring has to be fair. Every founder, VC and exec I speak with knows this. Your ability to hire is the biggest constraint on your company's growth. But recruiting is slow, it's subjective and only getting more competitive. And that's why teams like ElevenLabs, Brex Replit Deal and 5000 other organizations use Metaview, the AI company giving high performance performance teams a real unfair advantage in hiring. Metaview's built a suite of AI agents that behave like recruiting co workers. They proactively find candidates, they take interview notes automatically, and they help you surface the best candidates in process for the first time. AI handles the recruiting toil and gives you a single source of truth. That means hours saved per hire and a team focused on what matters most. Winning the right candidates as fast as possible. Don't let your competitors out. Hire you. Metaview customers close roles 30% faster. Try Metaview today and get a free month of sourcing at Metaview AI20VC. After Metaview captures what was said, Turing helps you build with the people who can deliver after it. Frontier Labs keep facing the same limitation. Models perform well on benchmarks, but they fall short once they enter real coding tasks, real tools and real workflows that disconnect between synthetic evaluation and actual system behavior is now a core block off for agentic models. That's why Nvidia, Anthropic, Salesforce, Gemini and other leading lab partners partner with Turing. Turing is the research accelerator focused on post training reliability. They build realistic RL environments, next generation data quality systems built from real world operational traces and coding datasets that stress models under conditions where failures matter, state changes, workflow branching, brittle tool calls and the coding errors that break RL agents but never appear in benchmark reports. In reality, a model may demonstrate correct reasoning in your evaluation setup, yet still select the wrong parameter or mishandle a code update in a realistic interface. Turing makes that failure visible and gives teams the signal they need to fix it. For Labs advancing Ajantic systems, Turing provides the structure required to understand why these failures occur. To find out how, visit turing.com 20vc that's t u r-I n g.com 20vc.

[Chris O'Neill]

You have now arrived at your destination.

[Harry Stebbings]

Anish. Dude, I've wanted to do this for a while. We've been going back and forth.

[Anish Akaya]

Yes, we have.

[Harry Stebbings]

And so I'm so glad that we.

[Chris O'Neill]

Can do this in person. Thank you for joining me.

[Anish Akaya]

Of course. Thank you for having me.

[Harry Stebbings]

I'm diving right in.

[Chris O'Neill]

We were just chatting now and I was saying I think it's better to build in London than in SF or.

[Harry Stebbings]

In other places other than sf. Talent is cheaper, it retains for longer. You don't have the promiscuity of people jumping from role to role.

[Chris O'Neill]

You've built a company now, both in Canada and in sf. How do you reflect on what I just said?

[Anish Akaya]

I disagree with you. I wish it was true. I simply wish it was true. And I want it to be true. And maybe it will be true. That it will be. You know, the whole thing that we always love to say to ourselves around sort of talent and opportunity not being, you know, talent is equally distributed opportunities not. The truth is that cities are the original network effect. And for technology, there is a network effect for builders in SF and for this moment in technology. Right. Where so many of the secrets are these sort of things whispered down shadowy hallways. The benefit of being in SF is enormous. There's also, we just talked about this. There's a selection bias question. Do you care enough to make it happen in sf? You can make it happen anywhere in New York, London, Toronto, Tel Aviv, you name it. But there's something different about saying, I'm going to give everything else up and be singular in my focus and move everything to SF to make it happen.

[Chris O'Neill]

Are there any other locations where you think there is actually positivity associated with that being located there?

[Anish Akaya]

Tel Aviv. I think Tel Aviv, you can be incredibly ambitious and uncompromising on that ambition and have a really, really good reason to be there. I think the other nice thing about the Tel Aviv ecosystem is that the country's so small, it's 10 million people, that you can't possibly fool yourself into thinking that the domestic market is going to be big enough for whatever you're doing. So you immediately go outside. Whereas if you're In London, there's 60 million people here. Okay. And you might say, well, that's actually a lot of people. And you know what, there are parts of the market like fintech where the LTVs are so high that perhaps 60 million is sufficient. But. But for most mass market products, it's just not sufficient. And if you end up starting focused on the domestic market, it's often hard to actually move on to a bigger market. So there are all of these reasons that it's just, it's not that it can't be done and there are incredible counterexamples, like 11. But I do think that is just that much easier in sf. And that's why that's where I focus.

[Chris O'Neill]

You said the word sufficient there.

[Harry Stebbings]

Yes.

[Chris O'Neill]

You can build a sufficient sized business, say in the uk, three to five billion dollars business, say, as an example. Respectfully, when we look at companies being created today, $3 to $5 billion just doesn't seem like it's interesting enough. Has the world of venture changed so significantly on what is sufficient for a venture outcome?

[Anish Akaya]

I mean, 3 to 5 billion is an extraordinary outcome, don't get me wrong. So in no way am I minimizing that. And look, I do think that those types of venture outcomes stack to create really meaningful funds. So this is not about working backwards from venture economics. But the biggest companies in the world today are trillion dollar companies. If you want to build a trillion dollar company, if that's your intention, you've sort of got to start with a set of assumptions that can lead to that. If your intention is to build an extraordinary enterprise and you build a three to $5 billion enterprise, you are one of the few people in the world.

[Chris O'Neill]

When we say about those three to $5 billion companies, I had a brilliant statement, which is the Sassaca the massacre of SaaS companies that's going on in the public markets today. When we look at it, essentially investors are no longer confident that traditional enterprise revenue is sticky or durable. Are they right to question whether traditional enterprise revenue is sticky and durable?

[Anish Akaya]

I think software is completely oversold. I think it's a silly story. I heard it called SaaS Apocalypse Today. It's very funny. Bloomberg is trying to get that to stick. Look, if you look at SaaS spend today, if you look at IT spend overall, it's 8 to 12% of enterprise spend. So even if you vibe coded your ERP and your payroll with all of the kind of risks and dangers that that entails, you're going to save 8 to 12%. You have this innovation bazooka with these models. Why would you point it at rebuilding payroll or ERP or CRM? Right. You're going to take it and use it to extend your core advantage as a business or you're going to take it to optimize the other 90% that you're not spending on software today. So I just think that of course there will be secular losers. There are like specific business models that are now going to be disadvantage. But I think the general story that we're going to vibe code everything is flat wrong and the whole market is oversold software.

[Chris O'Neill]

Okay? We are actually overly negative and we are being too critical on these companies. How do we think about then the continuing negative growth that we've seen in a lot of these companies, the continuing seat contractions in a lot of your, say CRM providers or Mondays of the world?

[Anish Akaya]

Well, I don't know if that's what we're seeing across the board. I looked at the data this morning and if you look at public market SaaS companies 75% have raised prices since ChatGPT was released. Least 75% and they've raised prices meaningfully. The mean is 8 to 12%. But there's a large group that have raised it 25% or more.

[Chris O'Neill]

Is that not because they have to? Because they're not growing seat count and so they have to grow revenue count.

[Anish Akaya]

Price is a measure of product market fit. Right. And if you have enormous competitive pressure, you are not raising prices, you're typically cutting prices. So I think one, you've got this dissonant fact that prices are going up. Two, if you look at the incumbents today, like ServiceNow is not IBM, they're a highly capable incumbent, they just went public and they raised guidance. So I think it's very easy to look at these things and say incumbents, incumbents, incumbents. Again, they're not seers, they're very, very capable. And I think they actually have a right to win and deploy technology in the context of these workflows. Now, will there be disruption? Of course. We've talked a bunch about companies that were once priced on seats, which are now going to be priced on outcomes, and that is going to be a big drag. But I think for the majority of SaaS, it has so little upside in being rewritten and vibe coded and so much down. Why would you do it? Now, an interesting topic that's not discussed is the cost of transitioning from one SaaS provider to another, going dramatically down. So systems integration. If you and Alex said this funny thing, and I know you laughed and I laughed too, which is that like some companies have hostages, not customers.

[Chris O'Neill]

Yeah, I love this statement.

[Anish Akaya]

I love it too. And if you actually have, you know, an SAP system, you are a hostage of SAP and they need to do nothing after they win you as a customer, accept the bare minimum if you want to switch to Oracle. Oh my God, that's like a multi year high risk. It's probably going to fail and you're probably going to get fired. It doesn't happen. But now with coding agents, the complexity of transitioning from SAP to Oracle is dramatically lower. The speed, the risk. So that is how I think coding agents shows up in enterprise software, especially amongst public names. Decreased switching costs, more customers, less hostages, which is a positive incentive for the entire ecosystem.

[Chris O'Neill]

You mentioned Alex Rampel. I actually sounds super weird. I actually think about Alex every day.

[Anish Akaya]

I do too.

[Chris O'Neill]

Yeah, well, there we go. Because he says the most brilliant thing, which is. And I'm going to butcher it slightly, but, you know, will the incumbent acquire Innovation before the startup acquires distribution.

[Anish Akaya]

That's right, yeah.

[Chris O'Neill]

How do you think about who wins in this world? The public SaaS company who has distribution, be it a HubSpot or a Salesforce, who has millions of customers? Or is it actually the startup who has speed, agility and incredible engineers?

[Anish Akaya]

So if history is any guide, and to reference Alex, he would say that it often is. Those who have actually studied history tend to do better than those who have not. What I would say is that when you have this product cycle and you have a capable incumbent, what happens is they usually make their product better for their existing categories. So Microsoft will make a better word processor than they've ever made. Google will make a better search engine than they've ever made. And we're actually starting to see that some of that anyway. What you instead see is the native categories that did not exist before the product cycle being owned by startups. So I think that's a little bit of what we're going to see. If you said something like software movies or AI movie making or AI assisted movies, that's just not a category in which there is an incumbent. And I'm betting that a native company will actually win that. It probably won't be Adobe. Will Adobe make a better sort of Photoshop and Illustrator than ever before? Probably. Right.

[Chris O'Neill]

You said there about kind of native being an opportunity in terms of where opportunity sits in the stack. Why do you think the application layer will create more value than foundation models?

[Anish Akaya]

I don't know if it'll create more value, but I think that it is under discussed how much value it's going to create if you think of what the models are. So if we lived in a world and we were actually thinking about this a lot in 2022 and early 2023, which is if you had a single foundation model company, which at the time was OpenAI, which was a whole generation ahead, then they essentially were this unique supplier to everybody downstream in the innovation ecosystem. And they could do what you would do. If you, for example, controlled the Beatles and you're the only record label to have the Beatles, it's like, do you want the Beatles or not? You can charge 99% of your customers gross margin and you do, and you actually tend to charge 100 or 110%. So that actually was a big risk to the ecosystem. What has instead happened is we have all these foundation model providers. They're all innovating roughly in lockstep 80% of what they do. I think that they're actually substitutes for and then there's the open source models, which also do the same things. And then in the 20%, which arguably is where a lot of the value is, they are all specialists. So because you live in this world of multimodal where for some use cases, they're substitutes, for some use cases, they're actually specialists, there's a lot of value in having an aggregation layer, and that is the apps company. So let me tell you two categories specifically. One is coding. I think that if you actually look at coding, you might know that Gemini is great for front end, Codex is great for backend. If you're vibe coding your project, you probably want to use both and you don't want to switch between two clis all the time. It's just a pain. So being able to use Cursor as a single way to orchestrate all the models is valuable. Similarly, for creative tools, right, we're seeing this specialization fragmentation specialization mid journey in Kriya with their Crea1 model, these are the most aesthetically opinionated models, right? They create this incredible beautiful imagery. Conversely, if you look at Ideogram, Ideogram is often used by graphic designers. It is intentionally not opinionated from an aesthetic perspective. If you're somebody who's working as a creative at a big company, sometimes you're doing graphic design and sometimes you're just doing beautiful photography for print ads. You want to actually have access to both, and to do that, you use an apps company.

[Chris O'Neill]

So I think we massively overestimate the durability of revenue of AI companies more broadly as well. I think there's a chance that Cursor loses half of their revenue this year with accountabilization of them by claw code. I don't know anyone who's not moved to claw code. When I hear that someone's still on cursor, I'm like, wow.

[Anish Akaya]

Yeah. I think the thing that we are underappreciating is that we assume, you know, efficiency is increasing, but ambition and number of customers is staying fixed. And I think this is one of the incorrect assumptions that keeps getting made around AI. It's like, well, what are all the people going to do? Where will all the jobs be? You know, it's like our ability to be ambitious for wanting more things always grows so much faster than our means. And in the same way, if you look at software, the desire and demand for software, both to make it and to consume it, is dramatically more than the supply that we have today. And I think there is a developer and developer adjacent archetype for Whom Cursor is going to be perfect Codex as an app, codex as a cli cloud code like all of these products are going to find market fit and all grow. And if you look at any of the other markets, like creative tools, they're going to specialize in fragment in their own direction.

[Chris O'Neill]

So when you think about market composition for that market in the kind of developer tooling space, does that look more like cloud or does that look more like Uber and Lyft?

[Anish Akaya]

I don't think it looks like Uber and Lyft. Right. I think Uber and Lyft are, to my mind, the most extreme examples of pure substitutes. And a lot of the sort of price has been competed away. You look at cloud, you sort of have this oligopoly where they all actually have pretty reasonable margins. Right. And you know, you can squint and say, of course they have their specializations, but they're roughly substitutes and yet they've all done well. The foundation model companies look a little bit like that. And I think in the apps layer you're just going to have people that want to consume the code they generate through a rich IDE and those that want to be closer to the metal, and that's probably closer to aws, Google cloud than it is Uber, Lyft.

[Chris O'Neill]

So when we think about that, how do you think about competitive investing? It seems to me like it doesn't matter anymore. Back when I started, it was a big problem. You didn't invest in competitors. Now everyone is investing in competitors. Are we in a world where that no longer matters?

[Anish Akaya]

When you think about a firm that's organized the way we are, which is we actually do stuff for our companies, it becomes very difficult to invest in directly competing companies because then you've got the same resources, the same sort of Fortune 500 buyer, the same engineer that both companies want to hire. And I just like, I don't think we can run our business by investing in directly competing companies now. With that said, we're in a part of the market where companies are diverging very rapidly. So even companies that appear to be directly competing today tend to be not competing in 12 months, 18 months.

[Chris O'Neill]

And going back just before you said about the opportunity in the apps layer, when we think about that, one threat that's often posed to the apps layer is the models themselves providing products, whether it's OpenAI focusing on health now a lot, or whether it's claw code or. Actually, I saw Anthropic do some Claude attachment to legal yesterday. To what extent is models invading the Apps layer a credible threat to the verticalization of apps.

[Anish Akaya]

Yeah, so this is such an interesting topic. So granola, which we're not investors in, but I admire them a great deal. It's a great company. They've built a really interesting thing and they're first of course to live meeting recording and transcription, which is awesome. They have been copied to the moon. Right now everybody has a meeting transcription feature. OpenAI released one within ChatGPT. Very cool. The thing about granola, and I assume this is true, is that their vision is not to be a meeting transcription product. I assume it's to be a productivity suite. Right. They're going to build Word and Docs and spreadsheet and all of these other products around that core primitive. Does OpenAI have the sort of prioritization, the resources and the ambition in that direction to build all the feature surface around the primitive? So I think the models will often actually recreate the primitive and even do product marketing, which I think the Claude legal stuff was. But if you have a market that demands a lot of feature surface, I just think the model companies are less set up to prioritize it.

[Chris O'Neill]

Do you not think if bundled into an existing solution with 80% of the features, the majority of people just go, ah, fuck it?

[Anish Akaya]

Perhaps. I just think that the model companies have ambitions in so many directions that it's hard for them to prioritize building opinionated UIs for the legal community. I also think in many of these categories, again, being multimodal is important and OpenAI is only going to ever give you OpenAI models. Right? Anthropic is only going to give you their models. Same with Google. So if you are multimodel rich feature surface, I think being an apps company is better.

[Chris O'Neill]

Boring wins is a statement that you said to me before when we were talking about kind of apps layers and where value will accrue. What do you mean by boring wins and how does that translate to the next generation of iconic companies?

[Anish Akaya]

Oh, did I say boring wins?

[Chris O'Neill]

Yeah.

[Anish Akaya]

Well, let me make the sort of exact opposite case, I think. Weird wins, huh? Yeah. So, I mean, here is something that's actually very interesting, which is the nature of these models is very different than the nature of any technology we've had before. I'd say a lot of the technology we've had before, it's quantitative, it's sort of clinical, it can do incredible things, but it's sort of bounded in the range of, you know, feelings that it can sort of capture. Now we have this wild, non predictable, emotional, very Human technology. And sometimes it gets pointed in these directions that are very human but perhaps uncomfortable to a big corporation. Right. What is the human experience? It often involves disagreement, persuasion, sexuality, and we see that mirrored in some of these AI products. Yet if you're Google or Apple, you have a thousand committees that are explicitly designed to ensure there is never any persuasion, disagreement or sexuality expressed in your products. So I think that there is a pocket that startups can really thrive in which is building these weird products that really touch on many core aspects of humanity that the models can reflect. But the big corporations are uncomfortable to release. I mean, everything in companionship. Every product in companionship has been both well received by customers and a little uncomfortable for the labs to build. Perhaps modular gro.

[Chris O'Neill]

I'm sorry, when you say companionship, you're.

[Anish Akaya]

Saying like character but also janitor. Right. There's a ton of products that are there for replica, which is probably one of the most healthy and nourishing forms of companionship. But all of these products are there and they're there to facilitate friendships between people and technology and a lot of that stuff is just uncomfortable for big tech to do.

[Chris O'Neill]

Would you encourage your children to use them?

[Anish Akaya]

Absolutely. In fact, one of the products that I would love to exist, my request for startup is what I call a contextual companion for my son who plays Minecraft. My son plays Minecraft, he plays it online, he absolutely loves it. You know, the other kids playing Minecraft may or may not be the best influence. Often not the best influence. I'd love to actually have an AI companion play Minecraft with them. So there's this context in which they interact and I don't know, just sort of models pro social behaviors and is still cool and chill. I think there's a lot of room for teaching through these types of relationships and technology can help provide that.

[Chris O'Neill]

Do you not think that it engenders or removes the ability to interact with other humans and makes people even more withdrawn or used to building a relationship with technology than we already have?

[Anish Akaya]

I think it does the exact opposite. I think people are able to be more self reflective and explore aspects of themselves and human relationships, that they often just don't have another person to explore these things with. And I think, you know, if you're wealthy and perhaps educated, you know, maybe you're interested in therapy and that's like an outlet for it. Or if you are like you and I and you've got this embarrassment of social riches and you have all these people that want to hang out with you and you Go to these dinners where you stay up late and having all these philosophical conversations, or perhaps if you're one of the relative minority today that is spiritual or religious some way, and it's very emotionally nourishing to you. There are directions in which we can explore these things, but I think for the majority of our society today, they just don't have an outlet. And I do think technology can be that outlet.

[Chris O'Neill]

I like the idea. I also like it especially when you think about the amount of old people who are alone and you think about the companionship there.

[Anish Akaya]

Yes. And by the way, I think the whole thing is that there's got to be a level of indirection. This is why I think contextual companions are very powerful. Because I think for a senior citizen, like, you know, it's important they have a big sense of self respect. So if an AI calls them every night to like check in on them, well, they can be like, hold on, I don't need that, you know, I don't need to be babysat. But if instead the AI called to, you know, check to see if they'd taken their medicine, ask them how their day was, maybe lightly flirt with them, talk about World War II, I don't know, like suddenly they've got a context in which they're interacting. There's a level of indirection, but the thing that's actually delivering is sort of spiritual nourishment.

[Chris O'Neill]

The shittest question ever. But you know, after 10 years, I'm not embarrassed to ask shit questions, which is, how does the UI paradigm change in the world of AI, everyone's like, now we're just all going to be voice. Do you agree with like just it's all voice?

[Anish Akaya]

I think so. Voice is amazing for enterprise. I think that one dynamic UIs and two chat UIs are overstated in consumer. And the best thinker on this is actually Eugenia, who founded Replica and now Wabi. She's, she's great on this. And what she would tell you if she was here is that, look, most people don't want to save time, they want to spend time. Okay? And the products are designed by the most high agency people in the world. Like Sam and Elon are the most high agency people in the world. For them, the optimal UI is a chat box where you say exactly what you want. And like, voila, there it is. But for many people, they're again looking to waste time, spend time. They want a browse based interface. They're not quite sure what they want, they can't always articulate it's. So I think that in a world where we have intent based and browse based, browse based largely stays the same. And perhaps the future of intent based is chat. I'm still a little skeptical.

[Chris O'Neill]

I think people are consistently concerned by. We mentioned it earlier, but defensibility, switching costs, durability. When we think about moats and Alex's statement of hostages, not customers, in a new world of AI, do we just accept that there's no defensibility or a new mote's created?

[Anish Akaya]

I think defensibility still exists and still matters. Networks are the gold standard and they still are. A network effect product is incredibly powerful. Now look, you might argue that something like Multbook is a new type of synthetic network. That perhaps means there are certain types of networks that are less defensible than they once were. But something like an Airbnb, you can have all the vibe coding in the world. Their network effect is incredibly powerful. But so one, I think defensibility matters. Traditional moats still do matter. I do think that within moats like systems of record, there will be some who are more or less prone to disruption. So if you're an on prem database and there's no engagement layer and there's not a lot of human workflows built around the so called system of record, I think that you actually are at some risk. If you're the core system for a bank, you've got thousands of transactions per second, you've got hundreds of humans that interact with you. You have this incredible demand for accuracy. I still think that you're sort of as good as gold in terms of defensibility.

[Chris O'Neill]

Is there any forms of defensibility which were very prominent in the prior 10 years which are no longer as prominent?

[Anish Akaya]

Yeah, I'll give you the opposite. I was always skeptical of the sort of data network effect that was like this thing that got thrown out a lot when you couldn't think of what moat to say. But today if you look at companies that have proprietary data sets and not just proprietary, open evidence is a good example of this. But live proprietary. And live is a very, very powerful moat.

[Chris O'Neill]

When you say live, what do you mean?

[Anish Akaya]

Like your health data, for example. Right. That's our sort of live and ever changing source of data. Now there's a question of how proprietary can that be. But once you actually have data like that, or perhaps live data about a product that's running now, you can put a relatively commodity model in front of it and get much better results than the most cutting edge model that does not have access to the proprietary or live data.

[Chris O'Neill]

Okay. So we have relatively the same forms of defensibility that have existed before. That will continue to make many. I'm always trying to understand, I feel very kind of insecure right now as an investor because I'm trying to understand what holds true from the prior decade and what doesn't. And I need to change my mind on when the facts change. I change my mind when we think about a lot of the forms of defensibility remaining true. I was always taught that margins matter.

[Anish Akaya]

Yes.

[Chris O'Neill]

I walk with my mother around London Pullman and I'm always like, margins matter.

[Anish Akaya]

Yes. I can imagine holding your hand.

[Chris O'Neill]

Poor mom.

[Anish Akaya]

Handheld. Yes. Jesus.

[Chris O'Neill]

No wonder she wants to finish the walk. My question to you is, do margins matter as much in a world of AI and are we entering a new way that we should be thinking about margins?

[Anish Akaya]

Yeah. So here is actually where I think there's nuance in the margin conversation that's important. Okay. So if you look back at any time you've got and we should talk about the bubble that doesn't exist or perhaps there is some sort of subsidization and distortion that's happening in the market. For the record, I don't believe in were in that period, but I do think that anytime you have this sort of superheated markets, you have some distortion. Okay. If you look at the distortion from 2021, you essentially had this indirect subsidy of Google and Facebook. So you would invest in a fintech company, you would give them $10 million, they would go spend $8 million on Google Ads and Facebook ads. So there's a subsidy that was happening that were sort of these empty calories for the startup. If instead you look at the form of subsidy that happens today, what it typically means is zero margin or negative gross margin credits for the user to try the product. So these things tend to be a drag, but these are actually very healthy calories for the companies because out of that you get conversion into high paying users and many of whom are actual power users. So I do think that the blended margin story for AI native companies tends to be worse. But if you look at the overall sort of form of distortion that's happening, it's a much better one than we had five years ago. Does that make sense?

[Chris O'Neill]

It does. Jason Lemkin is a very good friend of mine from Sasta and he said to me, I say a brilliant statement. He said, for the best companies, inference is the new sales and marketing.

[Anish Akaya]

Yeah, I love that. 100% correct? Yes, yes. I also think that power users are so much more powerful than they ever have been. Like Andrew Chen used to say, pre AI and I love this, like power users are just users. And it was true because even if they got 100x more value, they typically didn't pay 100x more. Like you look at Spotify, great European company, the very best Spotify SKU with the highest bitrate music, totally lossless, all the pods, all the videos, family plan, everything was 20, $25 a month. So there's a belief that the price ceiling for consumer products mass market was 20 to 25amonth. You look at Grok heavy, it's 300amonth, chatgpt $200 a month, Gemini ultra 250amonth. So we're seeing 10x higher prices paid and you have consumption revenue on top of it. So for the power users are paying incredibly high subscription rates plus consumption revenue. So the S and M costs of acquiring those users are very wisely invested. And I think this is an important point that's changed.

[Chris O'Neill]

But you're telling me then for my team, when I'm looking at margins with the investing team, that we should have the same high bar that we carried or we should have greater elasticity to lower margins.

[Anish Akaya]

So first of all, it's typically a lot of organic traffic one, I would look at your M1, you know, your sort of month one as traffic, not truly acquired users because it's organic and it's free to acquire. And then second, I would take the look at the sort of margin cost of those users, free trials and sort of just say, hey, that's CAC and that's okay. And then look at the margin profile of people who convert and say that's the sort of durable margin profile of the product and the business. So you're sort of unbundling the CAC oriented margin spend versus the durable margin which is what's associated with your power and paying user.

[Chris O'Neill]

It totally does. The challenge becomes if you're trying to work out a CAC to LTV metric that you can kind of oscillate around.

[Anish Akaya]

Yeah.

[Chris O'Neill]

It's very difficult to get an accurate sense of LTV in such a changing landscape where you're not sure of the durability.

[Anish Akaya]

Yeah.

[Chris O'Neill]

Is the LTV 12 months or is it 48 months?

[Anish Akaya]

Yeah, well, I think that retention really matters. And if you take a look at the best AI products, you know, even if you look at M2 as the new M1. Right. Because again, you're getting a lot of sort of Tourists who come in at M1, you're not paying anything for them.

[Chris O'Neill]

And so M1 means month one. For those that don't know.

[Anish Akaya]

If you look at M2 sort of as your first month for some of these products that are requiring a ton of top of funnel traffic, then you apply the same high retention bar you ever applied to them.

[Chris O'Neill]

What's an M12? That would make you very excited.

[Anish Akaya]

I mean like the bigger the better. But certainly 50% is solid. Right. And if you're 60, 70%, I mean we're, we're very, very happy.

[Harry Stebbings]

So we have that.

[Chris O'Neill]

In terms of margins, I do want to touch on. You said bubble. No, I'm not in that camp. I like to attack things while I'm there. Why are you not in that camp?

[Anish Akaya]

Well, there's a little quip that I like to use which is like it's not a bubble and it's good that it is. And I'll tell you why. Look, this is not my area of focus or expertise, but one, you look at OpenAI's recent investment announcement, sorry, which is that there are 20 billion of top line and the way that they got there is they 3x capacity and they 3x top line. So every time they bring on capacity, all of that supply, that inference supply is 100% spoken for. And we're seeing that story happen over and over again. Whereas in previous sort of so called bubble periods, you saw this incredible build out of supply far ahead of demand. So so far we're not seeing that. Right. Two, if you actually look at the prices that customers are paying, they're going up. So you're not seeing the sort of price compression that you would get from a typical overbuild of supply. Right. And then three, as I said previously, even if there is subsidization, there's always going to be some distortion. Subsidization, it's a sort of intelligent subsidization that's mostly being paid for by big tech and the labs and it benefits consumers and startups like God Bless, I'm all for that.

[Chris O'Neill]

I do a show with Jason Lemkin and Rory o' Driscoll and Rory said something brilliant I think, which is like this will all work out. If we see the transition of spend from the 12% SaaS budgets that we operate in today, transition from that budget to the human labor budget. Do you think we will see that transition?

[Anish Akaya]

I mean, we're already seeing it. I think DG was on the show talking about C.H. robinson. Right. Like we're seeing A lot of companies start to see the productivity improvement from this new technology. I mean, how can they not, right? It's not just coding agents in which this is showing up. You talked about voice. Voice is the wedge into the enterprise. Voice agents are so powerful. And by the way, I think that the, the near term story of a lot of voice. I know we talked about support, you talked about sort of customer support. That's interesting. But the more interesting thing is why is support an isolated function? And let's go through it. You typically have had sales support, operations and collections. Who is the person that's really good at customer support? Empathetic. They're a listener, they really understand the product well. Who is really good at sales? They're more of a yapper, they're a talker, they're high energy, they're very charismatic, they're sort of good at the app upsell. They're always in a good mood. You've got these two different human archetypes for these two different roles. We've typically organized the enterprise around these two archetypes. Right. But now the models can be either of those people at any time. So the most sophisticated companies are starting to take support, sales, collections, operations, bundle them all together with one broad goal like CAC improvement. And I think that is going to be the 10x on productivity. More than saying, hey, we're just going to take cost out of customers support.

[Chris O'Neill]

How do you think about competition within markets? I'm jumping around so much when it's fascinating. You brought up customer support. I tweeted it the other day and I tweeted it before. I just can't get my head around this market. There are like 50 providers with over 50 million in funding, 10 with over 100 million. I'm very much of the Peter Thiel school of thought that competition is for losers and we want to have monopoly markets with your Decagons and your Sierras and your Intercoms and your Paloa's and I can go on and on, I don't know.

[Anish Akaya]

Well, the question is how do you define market? Okay, now this is an important point, right? So I would argue that in many cases what you're calling a market is actually an industry. Let's look at legal. Many great companies have been funded and there's still room for another dozen. And I think the reason for that is legal is a $500 million. It's sort of infrastructure for capitalism broadly. Is there going to be one company that wins the entire market of infrastructure for capitalism? Of course not. That Is an industry, not a market. And you're going to have dozens of winners that all specialize. Just as in legal today, you've got dozens of specializations. So I think in many of these markets we are talking about it as if it is one market when it is much, much bigger. And all the companies will specialize in their own directions.

[Chris O'Neill]

Well, it's a $500 billion market if you assume that we eat their market, not we're unattached to it. Correct?

[Anish Akaya]

Yeah.

[Chris O'Neill]

And we aren't attached to it.

[Anish Akaya]

I mean, that's an open question. I don't think that we're in the 8 to 12% anymore. Right. 50 billion legal software, traditionally, I think we're going to be somewhere between the 50 and the 500 and I think closer to the 500 than the 50.

[Chris O'Neill]

What does that look like? That means AI native law firms, possibly.

[Anish Akaya]

I think it means dramatic productivity increases for lawyers, dramatic productivity increases for programmers and engineers. I think that the difficulty of doing 100% of a job is really, really high. It's this thing of pretty easy to get to 60, 70, 80%. I do think that's why a 20% productivity increase so far, we're seeing it show up more as you know, a four day workweek than 20% less jobs. Because jobs as bundle of tasks don't set themselves up to be 100% automated so far. Right. You can do all the customer support you want, but sometimes you got to take the customer out for a steak dinner. And so far the models are not doing that.

[Chris O'Neill]

They're not. We mentioned like the $500 billion TAM. Do you do TAM analysis when investing?

[Anish Akaya]

Here's what I think. I think we tend to consistently underestimate how big the markets are and consistently overestimate how easy it is to go from zero to one. I think when you squint, you can take something that's not working and say, I can see how it will work. And that is why in my mind, seed investing is, you know, it's its own sort of art. I focus very much on the Series A because I believe that the having shipped something and having sold something is such a dramatic signal to me that is actually, you know, the optimal point in terms of information provided, entry, ownership and price. Whereas at the seed it could be anything. Very, very difficult to get something working. Once you do get something working, I believe these companies tend to be even greater and greater versions of themselves for a long time to come. Then I think the mistake that many venture capitalists have made is just not Estimating the market to be as big as it is.

[Chris O'Neill]

I'm enjoying this so much. I have really three things I want to dig into there. You said about markets and underestimating size. Our dear friend Alex Deal. I met him at the seed round and he told me about Deal. And I was like, yeah, dude, you're brilliant.

[Anish Akaya]

But payroll deal. And 11. I'm sorry, off.

[Chris O'Neill]

I didn't tell you earlier.

[Anish Akaya]

What's your next pass, please? Okay, well, great.

[Chris O'Neill]

Okay, just keep them coming. Chris knows this. I sent a voice note to my partner saying, will someone please set up a just giving page for Chris because no one's going to invest.

[Harry Stebbings]

I will.

[Chris O'Neill]

I will send you my next pass. You know, most investors, when they send.

[Harry Stebbings]

You the past, you're like, well, I.

[Anish Akaya]

Look forward to your downturn.

[Chris O'Neill]

You should do.

[Anish Akaya]

Yeah, 100%.

[Harry Stebbings]

You said about market underestimation.

[Chris O'Neill]

I underestimated the payroll market. I thought Alex was great. I didn't underestimate him. But the market, I did. What market did you underestimate, which you later realized you were wrong on? And what did you learn?

[Anish Akaya]

It's such a good question about which market did we underestimate? I mean, I've made this mistake a couple of times. You know, like, for example, I remember when we were acquired by Google and I remember looking at the sort of the stock price then telling my co founder like, well, maybe this can go up 10 or 15 or 20 or 30%. How much bigger can it possibly get? So if you look at a company like that, which was so capable but seemed dominant in their core market, it was very hard to squint and see what they would become. And they're so much more valuable than they once were. I think another interesting example of this is credit karma. You know, free credit scores for Americans. And I know the credit score is a much bigger concept in America than it is where I grew up in Canada or even here, I think you'd sort of ask yourself if you did the back of the envelope, you would say, well, most people tend to use their credit score once or twice a year. Right? And most people don't even actually need it that often. It's only when you're applying for a new financial product. And then for most people, you either have exceptional credit and you don't really need to look at it because you already know that, or you have terrible credit and you just don't want to look at it and you kind of already know that. So now you've got this torso of people who infrequently need access to their credit score. Is that really a big company? And if you then look at Credit Karma, you know, it's like over 100 million Americans use it. You've got 50 million quarterly actives. You've got people logging in on average four times a month. And the reason that it works is that the credit score is actually this sort of mirror that people like to look in and see how they're doing objectively as an adult, whether you're doing great, whether you're doing poorly, whether you're doing just okay. People really find a lot of sort of satisfaction in the feedback loop of looking at their credit score. Not something that I ever would have predicted. And as a result, Credit Karma has many opportunities to sort of inform and sell their company, their customers, products. And it really, really works.

[Chris O'Neill]

So how do you reflect on that, like, missing that?

[Anish Akaya]

I think when you have a formidable founder and they're showing a lot of early momentum in a market, inertia is the best mental model. In my mind, inertia is the most powerful force in the universe. So everything that is happening today is going to default, happen forever. And when you have a formidable founder making tremendous nonlinear progress, you have to tiebreak in the direction of them doing it forever. That has to be your underwrite.

[Chris O'Neill]

So funny. Rory just mentioned earlier, he says when a founder continuously hits target, you should bet on them continuing to continuously hit target. Don't overthink this shit. It's hard to hit target.

[Anish Akaya]

Well, this is. I'll tell you a funny thing. So when I first started, I remember sitting. I spent a bunch of time with Mark and Dixon and everyone. So I remember sitting down with Mark and saying, all right, Mark, what's the process like? Tell me exactly what the process is. You know, And Mark said this maddening thing, which is just be right a lot. And I was like, mark, what is? Of course be right a lot, but what else? What is? And of course, you know, there's a bunch of things that we talked about. But ultimately, having reflected on that, I think his view is like, your process doesn't matter as long as you're consistently winning. When I started my career at Amazon as an engineer in 2003, they had a very similar thing. I think it's still a part of their kind of leadership principles, which is that you're consistently right. And I remember being 23 or 24 years old and just finding it to be maddening because, like, well, why are you right? How are you right? But this quality of being right sort of Supersedes the why or the how or all of our very intellectual mental models of how long it can sustain.

[Chris O'Neill]

And you said, like, just win and the importance of winning. We said downstairs, I lost to a wonderful colleague of yours, Sema, in the company Ask Leo in Germany at the Series A. And I reflect on this a lot. A lot.

[Anish Akaya]

I can tell.

[Chris O'Neill]

It's on my mind when you reflect what was your most painful loss and how do you reflect on that?

[Anish Akaya]

I haven't lost a deal.

[Chris O'Neill]

You've never lost a deal?

[Anish Akaya]

I've never lost a deal.

[Chris O'Neill]

How long have you been in Andreessen?

[Anish Akaya]

Six and a half years.

[Chris O'Neill]

Huh?

[Anish Akaya]

Yeah. Yeah.

[Harry Stebbings]

Do you worry about that?

[Chris O'Neill]

I mean this in the nicest way. Like, you know, I asked Ram Pal about this because he lost the A over it and then did the B, which was great and fantastic. Well done him.

[Anish Akaya]

Yeah. Perhaps risk aperture is not high enough if you're never losing deals. Maybe. I don't know. I think that there is a process by which you can be a part of most important companies that you want to be a part of. I think that there are some very difficult pre existing conditions to overcome. Like somebody has a very healthy, successful relationship with a past investor. You're just never going to overcome that. Right. And by the way, like, like having been that, I think healthy and supportive past investor for many people, I would never expect those founders to go work with someone else.

[Chris O'Neill]

What do you do in those situations when they're like this?

[Harry Stebbings]

I love you, but I've known these.

[Chris O'Neill]

Guys for 10 years. They backed me before.

[Harry Stebbings]

Do you joke?

[Chris O'Neill]

Hey, we're going to be the collaborative partner and try and nestle in now or we'll just peace out and not take part for this round.

[Anish Akaya]

I think that there are no games to be played and I think this is the magic of being in this business and being at Andreessen Horowitz. When I started, I had this nervousness around like, maybe it's a sales job, but I've realized if you just sort of show up with the right intentions and like, you know, you have to assume that they know everything you know. Of course they do. We live in this era of very, very sophisticated individuals and founders and you respect that and say, like, look, I want to like, respect the relationship that you have. With that said, like, our mission is to be a part of every important technology story that happens. If there's a way to be a part of it now, great. If not, like, let us get to know each other and earn the right to be your lead Investor at the next round. And sometimes that's the right thing. Thing.

[Chris O'Neill]

How elastic will you be on ownership in order to win deals?

[Anish Akaya]

Not very elastic. I try to explain what our model is, but I'm very elastic on price. I should probably be careful about saying that. I mean, my mental model is that below a certain threshold, the price doesn't matter. You just have to.

[Chris O'Neill]

I want to learn from you.

[Anish Akaya]

Yeah, well, this is my mental model.

[Chris O'Neill]

No, no, it was. I've learned in venture simply copy often works. So like very elastic on price and below a certain price, it doesn't really matter. What is that price?

[Anish Akaya]

I mean, look, I think price starts to really matter once you're into the hundreds of millions. And certainly at the stage that DG does, price does really matter. But I think at the early stage, let's say sub 100 million, like 50, 70, 100, even 120, the main way that price shows up is it may impair your ability to raise the next round because you price something so high. And we're very transparent about that. All of a sudden, tell a founder, like, look, you've got great metrics. We can do this Series A, as you know, 12 on 60, 15 on 75, like 12 to 15. It's a little bit of a wash for us in terms of the check size that we're writing. And it's more about what expectations you want to sign up for at the next round. And look, the one thing that we typically don't flex a lot on is ownership because that is our whole model. And like the model of, hey, we're going to put all the chips in behind you, doesn't work if we're not real partners.

[Chris O'Neill]

200 versus 300.

[Anish Akaya]

Yeah, I mean, it's, it's, it's in the margins. Again, I think a lot more at that sort of price threshold, I start to think a lot more about the next round than the absolute dollars in. Right. The absolute dollars, again, for a sufficiently large fund, probably aren't going to make or break the fund, but your ability to raise the next round, especially once you're in that growth territory. Right. The $500 million round is a hard round. The difference between having to raise at 300, 500 and 700 is pretty significant.

[Chris O'Neill]

Do you think we're skipping that round? And what I mean by that is if you think about the companies that are raising at 100 to 200 with 1 to 3 million in revenue, say early signs of PMF, and then they're growing so fast that they're hitting 30 to 50 within, I don't know, 12 to 24 months. Well then they raised a billion and that 500 million tween around is now gone.

[Anish Akaya]

Yeah, look, I think that happens and I think in a case where it's because core metrics are super healthy, like good for them. God bless.

[Chris O'Neill]

You know, I have a lot of enterprise SaaS, companies that do double double or triple triple double double. Is the world of triple triple double double dead. And do we all have to be lovable replied in 11 labs to get funded?

[Anish Akaya]

I don't think so. I mean I think that a lot of it is dependent, it's calibrated to your part of the market. So product velocity plus business velocity. I do think that you have to be top quartile compared to your peer set. I think there are some markets that are consumer ladder bottoms up where you can just see this explosive growth and that is awesome. It's extraordinary to see. But look, if you're selling an erp, you've got a much more cautious customer, It's a much more high stake sale if you're selling payroll. Now granted in the case of payroll, Alex and team have done a tremendous job of what should be like a slow boil sale and turning it into a fast boil sale. And they've got some very specific ways that they do that. But typically that is an industry that moves on slower cycles. So I think that there is just physics to some of these markets that mean triple triple double double is phenomenal. But there are other markets in which especially with these new primitives, you can go like 10 to 100 or 10 to 200.

[Chris O'Neill]

So you bring in triple triple double double to partnership and they won't shit on it.

[Anish Akaya]

Absolutely not. No, no. Again, I think that these are all heuristics that we use and we throw it around. First of all, I want to say I respect the difficulty of getting to a million of revenue. Dude, it is so hard, like getting anyone to pay you anything that's not a family member or friend is hard. And then going from 1 to 5 or 10 is super hard and 10 to 100 is tremendously hard. So one, I think that it's, I hate it when investors are very flip about this. And then two, no, look, I think it's all about the sort of assumptions that the founder is making, the data as a way to validate those assumptions and the kind of direction the. What if it works? What is the sort of direction of the curve? What's the area underneath it? Right.

[Chris O'Neill]

Totally get you.

[Anish Akaya]

And by the way, sorry to interrupt. There are companies that are Area under the Curve companies where it may be a much more complex sort of slower growth story, but the area under the curve is much more significant than companies that have very high slope but potentially have challenges with defensibility.

[Chris O'Neill]

Super interesting. So you're saying that the length to the start line, as Des trainer at Intercom says, it takes a very long time to build. Like in Figma. Figma for like three or four years was kind of in the build process.

[Anish Akaya]

Absolutely, yeah. Area under the Curve. And what do you have today with Figma? You have an N of 1 network effects product that by the way, is sort of ahead of where I think the market is going in terms of moving from products focused on execution, which today are being subsumed by coding agents, to markets focused on thinking. And I think a lot of the thinking work is going to be done in products like figma. I'm not sure that Dylan and team saw that 10 years ago, but I think they're well positioned today.

[Chris O'Neill]

Area under the Curve companies, how does the world change for them today and do they still hold inherent value of fundraising early? How does that change? Because it's difficult to sell.

[Anish Akaya]

Yeah, I mean, I think the challenge for Area under the Curve companies is that you've got to have enough momentum that you can continue to fundraise. You've got to have enough substantiality that your customer loves you, they're willing to pay you up front, they're willing to expand with you. So it has its own idiosyncrasies and difficulties. But I think often some of the most significant companies are these Area under the curve companies. And look, they're these 20 year overnight success stories. I think that those are underestimated in venture lore. The 1 to 100 companies are extraordinary and we all love to be a part of them, but we may talk about those and lionize those, perhaps sometimes at the expense of the Area under the Curve company.

[Chris O'Neill]

You said you very much focus on the Series A. We mentioned some of the pricing differences there. I, I get in trouble with my team constantly for tweeting things and like.

[Harry Stebbings]

Oh, how you made my life so much harder.

[Chris O'Neill]

And I'm like, it's too easy otherwise. And I say that series is the hardest place to be investing right now because essentially you have a million in revenue, very little signs of product market fit. Honestly, at a million in revenue, you're paying 100 to 200x ARR. It's incredibly competitive price to progress ratio is incredibly mismatched. Between a 25 million seat. Why am I wrong?

[Anish Akaya]

Yeah, well, okay, so first of all, I think as an investor, you have to decide what kind of risk you want to take. Okay. So that is what we're paid to do. So let's talk through what are the different types of risk. So the first risk is one that you mentioned that is competitive risk. Can I win this process or not? Okay. The second risk, and this is maybe a slightly less good risk to take, but I think still a fine one, is pricing risk. Did I overpay? And again, I think the way that shows up is the difficulty of the next round based on your entry price. Right. Maybe the third risk is team risk. Can this team actually go the distance? You know, can the company be. Can they be big enough to fulfill the company's ambitions? Because I think the founder themselves can attenuate or amplify a company's destiny. Right. The company can't be bigger than their ability for it to be big. Okay. The fourth one I think is a little bit of geographic risk and maybe this is less true today, but like, is a Silicon Valley team going to do this? And the fifth is fundraising risk.

[Chris O'Neill]

Risk.

[Anish Akaya]

This is a non consensus deal that actually has no other investor interest around it. That is not to say that you need investor interest, but if the team has a difficult time fundraising, no matter how good they are at product and technology, they're not going to get the opportunity to sort of see their vision through. So I think taking competitive risk, can I win? And pricing risk, when you say, sorry, can I win?

[Chris O'Neill]

You're saying, can I win as an investor?

[Anish Akaya]

Yes, against the other VCs, that is what we should do. That is like the number one most important thing that we do. Win the deals by building trust with the founders, being smart on the markets, being first to conviction, all of these things. And that's why I think the Series A being hard, it's supposed to be hard and you should be winning.

[Chris O'Neill]

Anyway, a couple of questions on the back of that. We're seeing teams fall apart quicker than ever. They're leaving their startups faster than ever, having just raised big rounds to do new things. Are we seeing this increased promiscuity from founders, do you think?

[Anish Akaya]

I mean, I think we've always had to assess how sort of authentic their connection is to the problem at hand. Right. Because as it is, doing these startups is a little bit irrational. And Alex said this on the pod and I think he's exactly right, which you have to be a little bit irrationally. Optimistic to do it. I think you also have to be irrationally interested in the domain in which you're working because these things get hot and cold all the time, you know, And I think that that authenticity, which is not like a comment on intent, sometimes really well intentioned people, I've been this person have a reason that they're building their company other than authentic connection to the problem. I just don't think that's a good setup. That's a setup for promiscuity.

[Chris O'Neill]

Do you mind when someone comes in and says, listen, I don't have any particular interest in, I don't know, sales for car dealerships, but I saw it as a ripe area for innovation and where models can be transformative. Do you mind that?

[Anish Akaya]

I think there has to be some sort of irrational direction in which they're pointed. Maybe it's pure capitalism and they're like, look, I've studied the living shit out of this market market and it is a means to an end for me. But like I'm, you know, I'm going to get there or die trying. You need to see a little bit of that outlier sort of emotion and commitment. And I think it's best expressed when it's in the direction of the problem. But it doesn't have to be. I think if somebody comes in and they're like, I did a case study on it and it looks great, like not a great setup.

[Chris O'Neill]

Do you find with the founders that you work with the best founders are the best fundraisers or actually can they be a bit quirky? Like all the best founders generally great fundraisers?

[Anish Akaya]

I mean, look, I don't think they all have to show up the same stylistically. You know, the sort of like polished, you know, go to market oriented, whatever. Like the type of founder we saw more often five years ago. I mean, the Korea guys to me are a great example. You know, they come into our first pitch, first meeting with everyone in the room, Thanksgiving holiday and you know, I think they're both wearing matching kimonos, they're both drinking Celsius. You know, Victor's got his like long skate hair. He's just this total badass who looks exactly the opposite of every MBA founder that we've been meeting five years ago. And he's got a quiet presence and a lot of it comes from his command of the technology and the domain. It's a totally different style. It works really well for fundraising. So I think you do need to be able to fundraise and you can be very authentic in the way that.

[Chris O'Neill]

You do it in terms of having a command of technology and you said earlier about the challenge of shipping product and getting from 0 to 1. Showing that you've had a success building in the past is a great way to prove that you can do it moving forwards. Do you have an unreasonable or an unwavering leaning towards serial founders who've proven that they can do it because of their drive?

[Anish Akaya]

Yeah, I'll give you a nuance take on this. So I think that repeat founders working in their domain of expertise are formidable. Like the Klutch guys sold a company to Carvana, you know, they weren't super happy with the way that the whole thing ended up in terms of their startup achieving their ambitions. They went and then started another company out of that also in the auto space called Clutch. It's going extraordinarily well and they know, you know, they're taking all the shortcuts because they know the market. So I do think particularly in enterprise, working in the same domain and you know, being a repeat entrepreneur is a huge source of alpha. I actually think conversely in consumer, having a beginner's mind and a high willingness to be embarrassed is a competitive advantage because so many consumer products feel embarrassing and you know, they're immediately dismissed as embarrassing or impossible or a silly, non serious thing to be working on. When you're 25 and like the stakes are low, you just want to make something happen in the world that is a perfect setup. Once you've sold a company, all of a sudden it's like your venture friends are like, what are you working on? You know, like your girlfriend or your boyfriend's like, what are you working on? You want to sound cool at dinner parties or at the bar. And that slight hesitation to be embarrassed can sometimes hold you back from the most ambitious, interesting consumer ideas.

[Chris O'Neill]

I said earlier, when the facts change, I change my mind. What about the way that you used to invest has changed most significantly?

[Anish Akaya]

Well, I think the number one thing, and here's my free advice to other investors, but also founders, is just like you have to use the products today more than ever. And I think the investing landscape of five or seven years ago when there was a ton of fintech and I'm a fintech guy, I love fintech tech. But it was harder to build intuition for a small business factoring solution. Like I'm not really, I don't know, maybe I should start a small business just to fat. Like there's too many steps to actually try the product. But today being native in this Product cycle just means waking up every day and being like, if there's three new models today, I'm going to try three new models, I'm actually going to make something. So holding yourself to an incredibly high standard of trying everything just gives you so much information, intuition. I think it's, it's non negotiable for founders and I think it's incredibly important for investors as well. Yet most don't do it.

[Chris O'Neill]

We say about trying product. 90% of the companies that I get pitched today, especially on the application side, are agent led or agent first. You said before there might be agent overhype. Can you talk to me about this? Why do you feel there's agent overhyped today and what does that mean?

[Anish Akaya]

Here's what I think. I think that the extremist view that we are going to have autonomous agents that simply do everything over incredibly long time horizons, like maybe we'll get there someday. But I do think that at a minimum, you need humans in the loop for exception handling. And then these models are only as good as the instructions that we give them. And our instructions, I mean, think about the way you manage your team. Your instructions are often frustratingly vague. So I do think that we need people in a tight loop with the models to actually achieve our objectives. And I think that the sort of agent maximalist view, which is you just chill out for the day and your AI does everything you need to do, is probably a little bit ahead of where we actually are.

[Chris O'Neill]

Do you take the view that agents won't remove tasks from what you do, but they'll enable you to do tasks that you didn't have time for?

[Anish Akaya]

I think it's both, I think that they will do tasks, they'll do the low NPS work that you don't want to do, right? Do the work that you want to do, not the work that you have to do? I think the second thing is yes, the surface area, the circumference of ambition is going to go dramatically up for us as individuals, but also for us as a species. Harry, how can this be the peak expression of our ambition as a species? You've read enough sci fi books to even have a glimmer of what that looks like. And I think that's a world that we're going to actually live in, which is if you are ambitious in a direction, you should be able to fully chase it down and express and fulfill it. And the only question is, who are the ones that are ambitious to go do things? Because I don't think, think Execution or expertise is any longer a constraint when.

[Chris O'Neill]

We think about those Best place to win an agent first game I had Eric from Podium on the show, which is a fascinating story of a traditional SaaS provider that's now gotten $100 million plus agent led business. And he said that fundamentally, if you want to win in an agentic world, you have to own the tools, the workflow and the data. And so you have to kind of own the full stack. Ala of course, him and Salesforce.

[Harry Stebbings]

Do you agree that you have to.

[Chris O'Neill]

Own the stack to really be a big player? Or can you be a meta layer on top of a core provider?

[Anish Akaya]

Yeah, I mean, I think that you can use a core provider, you know, via tool use. I mean, to me the big question is just sort of ambiguity as one of the big sort of questions for how much leverage you get out of agents. So if you look at BPOs, you know, business process outsourcing, they are the areas in which there's the least ambiguity, where the job is literally a series of tasks, where people in offshore call centers take a task off the queue. Those things are very well set up for sort of automation and agent replacement because you've got incredibly well defined tasks and you've got jobs that are bundles of these well defined tasks. I think there are many jobs in which there's just such a high degree of ambiguity. I mean, even in software development, like arguably the coding is the easy part. The tough thing is like, what are we coding today and how do we adjust and how do we sort of adapt to what the customers are saying, what the market is saying, what our own epiphanies were overnight. The models are incredible at getting us into these local maximas and sometimes the local maxima is the global maxima. But I think often it takes human intuition to break from the local to the global. And that is something I think the agent's just not going to do.

[Chris O'Neill]

You mentioned BPOs there. How do you think about the future of UiPath? They've had a tumultuous journey in the public markets. Is that one that's sadly suffering from this? Or actually, are they well positioned to take advantage of distribution that they have?

[Anish Akaya]

I wish I KNEW More about UiPath. I just don't know enough about the company to comment. I mean, I think RPA is, is super interesting, but vision models haven't nearly kept up with the sort of, you know, the way that we've talked about them.

[Chris O'Neill]

One thing that we haven't discussed, which I want to, is kind of open versus closed It's a big question. A lot more use open than actually they say publicly, I find. And there's a lot more willingness than ever to use open.

[Anish Akaya]

Open source.

[Chris O'Neill]

Yeah. How do you think about the distribution in terms of open versus closed and how that looks in the next kind of 24 months?

[Anish Akaya]

That's a good question. So I don't think we're at a point in the cycle where companies are focused primarily on cost optimization. And I think that is one of the reasons to choose open, you know, which is like get an open source model, host it, and then have a cost benefit as a result. I do think there has been some interesting properties of open models like Kimik 2. You know, I believe that they didn't post train it to sort of restrain what it could say. As a result, it was just a lot more interesting in terms of text generation in many directions. So it had this sort of interesting product characteristic that a bunch of companies built around a bunch of companion companies in particular. So I think there are these idiosyncratic reasons we choose the open models for product quality. But in most cases I think companies are thinking about maximizing the sort of direction of ambition and their ability to fulfill it versus taking cost out. And closed is still a bit advantageous. Now, the nice thing about closed is they too have been cutting their costs. Right? So granted closed is more expensive than open in many cases, but the cost of actually a Token on GPT 4.0 has gone down 100x since the model was released.

[Chris O'Neill]

You said that we're not in the period of cost optimization, which I agree and think is a very interesting point. Jason Lamkin said to me, he's a real builder with one of your tools. Actually with Ratliff, I think he's literally one of their top users. It's insane. What an incredible power user he is. But he uses 11 labs as part of the voice for one of his games. And he said this will be the year where we see the true substitution of AI products based on price. He's at 11 labs. I love it. It's amazing.

[Anish Akaya]

Yeah, it's too expensive.

[Chris O'Neill]

It's too expensive. This is the year where we've moved from trying things to shit. It works, but it's too expensive. No comment on 11 labs, but do you agree that we're going to see this transition in mindset from shit at worst? It's expensive?

[Anish Akaya]

I don't think so. Because I think what we keep seeing is as the models get better downstream players, ability to take those capabilities, productize them and raise prices has outstripped the raise in costs. Right? So the incremental cost increase, potentially, and in many cases not a cost increase, but it's not a cost decrease, is so far outweighed by what the new capability unlocks. Like coding agents, right? What you can do with coding agents, Claude code came out last February is dramatically better. Is anybody here saying, well, I should go back and use Sonnet 3.7 because it's cheaper, you know, or I should use something other than Opus 4.5 or Codex 5.2? Like nobody is saying that because the capability is so much more powerful, it really like sparks your imagination in the other direction. What more can we do rather than how do we make the existing thing cheaper?

[Chris O'Neill]

It is interesting. I remember when he said he's got like a startup game and he's like, dude, I'm terrified that people are going to use it because I'm going to go bankrupt.

[Anish Akaya]

Okay, so this is actually a fun topic, which is that the fact that these products have costs are a very good thing. But what it means is Jason's going to have to figure out his business model early. So this field of dreams investing, where a company builds a free product and they're like, someday we'll figure out a business model that's not viable, it's like, no, you have costs today the way that every small business in the history of small businesses has had pre software. So the fact that these companies have costs actually forces a business model hygiene that I don't think existed across the board 10 years ago. And that's a good thing.

[Chris O'Neill]

If you're 11 labs, would you not just say, fuck, subsidize, cut prices, own market. This is a land grab. Don't risk, churn by price for the next year or two. They raised 500 million, they could have raised 5 billion more.

[Anish Akaya]

I think the general. There's so much more to be done at the frontier and there's so many more categories and capabilities that those things unlock. It's just a better use of time. Today again, we talked about 8 to 12% of enterprise spend is on SaaS, right? How much of consumer disposable income is spent on software today? Few hundred dollars a month maybe. We're going to asymptote to 80 to 90%, I believe for consumer spend and enterprise spend. The way we do that is by pushing the frontier, not by 80 to.

[Chris O'Neill]

90% of consumer spend, the sort of discretionary spend.

[Anish Akaya]

Of course there's going to be rent and food, but yes, dude, I think that software is going to eclipse many parts of our discretionary spend. And we just talked about companionship and friendship. We talked about entertainment, we talked about potentially therapy, potentially healthcare, potentially professional. A lot of the spend that I do on things that help me be better at my profession, education. So there's a tremendous sort of area for software to expand into. Let's forget about taking costs out of things for now.

[Chris O'Neill]

I don't know if you're including food in that.

[Anish Akaya]

Yeah.

[Chris O'Neill]

If you're including a daughter.

[Anish Akaya]

Discretionary, non discretionary spenders is fair.

[Chris O'Neill]

And you're clearly not European because you miss one crucial one, which is fashion. Yeah, it would not be that.

[Anish Akaya]

Thought you were gonna say wine.

[Chris O'Neill]

Dude. No one buys wine. No one drinks anymore. Okay, okay. Tough to be in the winter.

[Anish Akaya]

Not even the Europeans.

[Chris O'Neill]

No, not at all. It's super interesting. Do you agree with kingmaking today in terms of the belief that as I think, you know, but like an anointed winner can be made? Do you think kingmaking is real?

[Anish Akaya]

Let me comment in two ways. One, I think an example of where there is a very positive sort of catalyst in their investor base for enterprise companies is yc. YC is an awesome place to start an enterprise startup that sells to other enterprise startups. And they've got these sort of like good vibes within the community that makes it easier to sell into even much bigger, more established YC companies. So I think that's a good example in which picking the right investor is actually a big benefit. You know, a lot of what we do is connect companies that are small but have really important product and technology to the Fortune 500 in 2000. But we can't force them to buy that technology. Right. And again, you have to assume that the buyers, especially these days, have perfect information. So I think that the right investor can be a catalyst, But I don't think that you can take a product that would not otherwise be the winner and anoint them the winner.

[Chris O'Neill]

Do you agree that the best founders you work with don't need their VCs?

[Anish Akaya]

I think the best founders that I work with know how to maximally leverage their VCs. And look, I think there is a set of founders who perhaps would never need their investors. But I do think that the best founders know how to sort of extend their success and increase their momentum by leveraging the right investors like Alex does. Right. Dude, I mean, I basically have a sales quota with Alex, you know, and DG would say the same thing. And Ben, he's even calling Ben, saying, hey, Ben, can you Help make this introduction. XYZ like he knows how to get the best out of Andreessen Horowitz and all of the. It's not just the investors. The entire team shows up for him that way. Could he do it without us? Of course he could.

[Chris O'Neill]

What advice would you give then? We have so many founders that. Listen, what advice would you give to founders on how to have maximum value extraction from an investor base?

[Anish Akaya]

Yeah, well, first pick an investor that does stuff. I think number one, I think number two is how do you know?

[Chris O'Neill]

Everyone says they do.

[Anish Akaya]

Well, the best way is to talk to other founders.

[Chris O'Neill]

Right.

[Anish Akaya]

You should talk to other founders. I think the second thing is again, the VC can't distort the market. Right. All they can do is make all the introductions. And I think the best thing Mark talked about this is when you're small, the VC sort of gives you power. Right. That's what you want. The VC basically takes your brand, which is not big, and they lend you their brand. So you're not XYZ company, you're an Adreessen Horowitz company. Now, over time your brand becomes much bigger than Adreessen Horowitz and that is great. But they can help bootstrap you and create credibility in conversations. But you still have to have the best product, technology, go to market to go win the customer.

[Chris O'Neill]

Totally agree with that. In terms of, I think the lending of brands, I think is how you've described it before. It is phenomenally valuable. Can I ask you, when we think about kind of the lending of brands, who's the single best founder you work with?

[Anish Akaya]

Alex is just such a beast in terms of his go to market instincts, his product creativity and just his responsiveness. The guy's nuts. You know, Alex is 100% working all the time. It's just incredible.

[Chris O'Neill]

I've got a fun story for. We have Project Europe, which is like the teal fellowship for Europe. Basically back 18 year olds with a big dream. Yeah. And a technical capability.

[Anish Akaya]

Oh yeah. Jaden was telling me about this.

[Chris O'Neill]

It's amazing. Anyway, I pinged Alex on a Sunday morning, 7am saying, hey, they want an intro to a sales rep on your team. Who's the best person? He's like, intro to me, please. I'm like, dude, it's like a thousand dollar deal. It's not worth your time. He's like, no, no to alexeal.com.

[Anish Akaya]

That'S what I mean. He's so impressive. But look, there are other founders who have specialists in their domain, like the clutch guys. I mentioned who are deep technologists and know how to apply to product like Korea or the Happy Robot team. So. So there's just so much to learn from all these individuals and I know it sounds trite, but I'm privileged to work with them.

[Chris O'Neill]

No, the Happy Robot guys, I wish I was invested in that.

[Anish Akaya]

They're amazing, man. Please don't tell me you passed on that at the seed too.

[Chris O'Neill]

No, no, I didn't. I never met them.

[Anish Akaya]

Thank God. Okay, good, good, good.

[Chris O'Neill]

That's one of those ones where it's one that I wish I was in it, but I never had the chance to do it.

[Anish Akaya]

They're wonderful, incredible technologists, really earnest people and they're seeing a ton of success.

[Chris O'Neill]

When you reflect on companies or investments that you've made that were not good, what did you not see?

[Anish Akaya]

If there's a mistake that I've made. It's been being a bit too casual about product market fit and this was more of a 2021 mistake, which is assuming something had product market fit and perhaps it didn't. And perhaps the founder had a super credible theory which by the way matched my theory for why it would get to product market fit. But as I said, it's easy to overestimate the path from 0 to 1. I'd say if there was a mistake I made, it was not being intellectually honest about is this actually working or do I think it will work in the near future? Now look, I've done a bunch of seed investing and I've made the bet and I think if you're intellectually honest and sort of clear sighted about a belief that it will work, then that's a fine way to invest. But investing with this sort of self deception of like, well, let's just assume it's working when it's not quite working is a mistake.

[Chris O'Neill]

I think, you know, a good investment or a bad investment in the first three months.

[Anish Akaya]

Do you agree there are moments when you win a deal and you are just, you're like, you know, the feeling is like sheer relief and I'm sure that there are moments I haven't experienced this thankfully. When you win a deal and you're like, wow, I won it. And you're sort of faced with uncertainty and I think the sort of psychology of that latter moment is very telling.

[Chris O'Neill]

Have you ever felt that the Andreessen brand holds you back in any way? Like maybe with a.

[Anish Akaya]

No, no, not one.

[Chris O'Neill]

It's a massive tailwind in law. There's never been one where there's like been A political question?

[Anish Akaya]

Not at all. No. And Mark and Ben are so special and authentic. And look, what Ben said, has said many times, is that they sort of, you know, feel like there. It's their responsibility to kind of extend the surface area of the entire industry. And, like, I see them do that every single day. So, no, there's never been even a moment at which it held me back. In fact, it's been just the opposite.

[Chris O'Neill]

Dude, I could talk to you all day. I do want to do a quick firearound with you.

[Anish Akaya]

Okay.

[Chris O'Neill]

Are you ready for this?

[Anish Akaya]

Okay.

[Chris O'Neill]

What's the most memorable first founder meeting you had? It doesn't have to be, like the best founder by the most memorable first founder meeting you had and why.

[Anish Akaya]

I mean, yeah, so it's probably the guys at Korea. Just because, you know, they'd been so mysterious, we'd been unable to get ahold of them for nine months. They'd been making all this noise on X with their sort of creative tools and their models, and we know there's so much anticipation meeting them. We all. It was Thanksgiving week. We all sort of flew in. Mark was there. And just to see these two guys walk in, total badasses with their matching kimonos, with their Celsius drinks, and just hold the room by being these deep, authentic technologists and product people, it's just not something that I'd seen before. And there was so much of a setup to the meeting that it's. It's what I'll never forget.

[Chris O'Neill]

Mark, Ben, dg, who's the best investor?

[Anish Akaya]

I mean, they're all extraordinary. Let me tell you the strengths. So, like, Mark is the guy that can just tell you, one, he'll paint a picture of the future. But two, he knows everything about everything else outside of technology. He's read every book. He's memorized them all. He's got these incredible stories. Of course, he invented the consumer Internet, so he is just. His storytelling ability is extraordinary. Then, like, to me, I mean, Hard Things was the first honest business book. Okay? And I always say about business books, like, the business model of business books is selling business books. It's not making you better. Most business books are full of shit. And Hard Things is the first one that was, like, authentic. And if you've read it as a founder, you're like, oh, my God, somebody finally sees me. So just his sort of stories of wartime and navigating these inflection points and his ability to contextualize that for whatever you're going through, totally unmatched. The thing About DG that's so special is a lot of us are sort of these founder investors. We are like learning how to be investors through the lens of being a founder. DG is a pure and highly, highly seasoned investor. He has this sort of pure play investor clarity that I tend to learn a ton from. He to me is so, so interesting at the growth stage in the same way that Dixon is interesting at the early stage. So much of our best thinking as Dixon and also dg, what's been the.

[Chris O'Neill]

Hardest decision that you've had to make in the last two to three years?

[Anish Akaya]

I mean to me a big decision was coming into investing and not being a sort of hands on builder anymore. I wasn't sure because I'd, you know, I've had some incredible investors, but I've had some investors that you know, just weren't the best. And sometimes through no fault of their own, sometimes they're sort of early career and sometimes, you know, they just were disengaged in a way that I never wanted to be. So I was uncertain about whether I wanted to move into investing. And I remember sitting down with Ben. Who was I to ask Ben questions? But I'm like, well I guess like I'm not sure anyway. So let me just be direct with Ben. I'm like, well Ben, how do you prevent bad behavior, you know, investor bad behavior, how do you prevent the sort of high anxiety? How do you prevent, you know, the person that's disengaged? And he's like, well, in the near term we don't measure you based on returns. We measure you by going and talking to every one of your founders every two years doing a 360 on you. And if your founders say you're telling them the truth, you're showing up, you're doing the work, you're being responsive, regardless of how those companies are performing, then you're doing a great job. If your founders say anything other than that, regardless of how the companies are performing, like you're looking for a job elsewhere. And by the way, we do those, we do these GP360s every two years. It's always a little terrifying. But the incentives are all structured in the right way. And that, that moment in the answer to that question is, was at which I knew, like, hey, this is, this is not a VC like every other VC I've seen out there. This is like a company.

[Chris O'Neill]

I remember someone from Andreessen tell me and I'll keep. I can't actually remember who it is, so I'm not Actually being deliberately quiet. It might have been Brian, it might have been dg, it might have been Alex. I really can't remember. But they said like, sorry. And they said like, in Andreessen, it's totally unacceptable to lose a deal, but it's very acceptable to not have seen it. And it'd be great that fair to.

[Anish Akaya]

Not have seen it.

[Chris O'Neill]

Like random company does very well. We never met them. We never had the chance to meet them.

[Anish Akaya]

I don't think so. I don't think we're allowed to believe in luck at Andreessen. We have to see 100% of the deals in our domain. I think it is acceptable to make a decision based on the information you have and have the decision be wrong. Like you invest in a company, it doesn't will work. And that's okay. That's the business. But the expectation is we see 100% of the deals in our sector and that we win 100% of the deals that we go after.

[Chris O'Neill]

That was very clear. There was no. No. I love it, dude.

[Harry Stebbings]

Okay, good, good. Right, that ends that conversation.

[Anish Akaya]

I mean, hey, look, some things are ambiguous, but that part is not.

[Chris O'Neill]

No, no, Nuance good. I hate nuance.

[Harry Stebbings]

It depends.

[Chris O'Neill]

It's the worst answer. You can invest in one seed firm. Which seed firm do you invest in?

[Anish Akaya]

All right. I think Brompton is pretty special at what he does actually at abstract.

[Harry Stebbings]

I agree.

[Chris O'Neill]

Why?

[Anish Akaya]

Yeah, I mean, one, he's a cold blooded capitalist, which is awesome. He just has great instincts. And I think the seed, to me, the seed stage is the hardest stage at which to invest because it's easy to make one great seed investment. But it's hard to have a system, I think, for doing great seed investing, because there is, even when the people are amazing, there just isn't anything there yet. There is no product. The true seed, there's no product and there's no go to market yet. A post product, pre traction, that gets easier. Post product, post some traction, that gets a lot easier. And I call that a series A. But at the true seed, it's just hard to be right a lot. And he has consistently been right a lot. So when I sort of look at a seed manager I respect, I don't know exactly what his witchcraft is, but it's working. He's right a lot.

[Chris O'Neill]

What have you changed your mind on most in the last 12 months?

[Anish Akaya]

I think the thing that surprised me about this product cycle, you know, I was building my first company in the mobile product cycle. And in the mobile product cycle, the sort of like the anointed winners in 2008, 2009 were not the eventual winners. So we had this cycle where you sort of had the Friendsters and then two or three years later you had the Facebooks right in this product cycle. What's actually interesting is a bunch of these. The early leaders from 23 and 24 have maintained their lead. We talked about Harvey, that's a really impressive company. You know, Gamma is a really impressive company. Cursor is a really impressive company. Like the companies that were early have so far continued to actually be dominant. And that's something that I've sort of changed my mind on. I think in 26 we're going to see a whole new set of categories because Mike, can I share my view on where we are in the market? I think that late 22nd, November 22nd is ChatGPT 23. A lot of the kind of obviously good ideas, and that's not to denigrate them, they were obviously good, were started in some of 24. In the end of 24, reasoning models started working. So even the ideas that were obviously good but not working, suddenly many of them suddenly started working. With the advent of 01 and deep seq25, those companies scaled. So now we are starting to see for existing markets, which is like customer support and the evolution of that chat creative tools code. We have these early leaders. Those markets are somewhat established. It's going to be very hard to be like another customer support or coding tool today. Conversely, we're going to see a set of AI native categories I think emerge in 2026. Knowing what we all know now, what company would you build? That is the operative question. And OpenClaw and Multbook are just the beginning of that. Like those are ideas that were inconceivable two years ago. So I think that the, the thing for that I learned over the last 18 months is like, hey, maybe the early leaders will just be the leaders. And over the next 12 months I'm going to pay a lot of attention to who the early leaders are in the sort of new native categories.

[Chris O'Neill]

How significant is Malt Book? Everyone's very excited by it. You're a lot more product centric than me. How significant is this?

[Anish Akaya]

I mean, it's just so damn cool. Just like just to talk about it, to observe it. It's shallow and you know, biology called it robot dogs barking at each other. And I think that there's an element of truth to that. Right? And any humanity they have is just the sort of sparks of the humanity that it's taken from the context of its owners. I think, though, what is very interesting is the idea that we can have these digital twins, you know, these echoes of ourselves going. Interacting with other people. I mean, you could. We were talking about dating downstairs, right. And sort of how the dating apps are a mess and probably not durable in their model. Like, you could imagine a world in which I train. I'm married, but, you know, if I was not, I train a little digital twin of myself. And other people would do the same, and they would go have, you know, pseudo dates, and then they would come back and matchmake us and say, like, hey, we had this, like, virtual date and it went kind of well and maybe you guys should hang in person. So now we're able to kind of replicate and scale ourselves in a way that was totally science fiction five years ago, one year ago.

[Chris O'Neill]

I don't know if you've seen match.com today, but the stock price is down like a huge amount because someone basically did this. Ugc. Oh, yeah. Yes.

[Anish Akaya]

Yeah, yeah, yeah. The hinge thing. Yeah. That's tough. Yeah. So I think that, like, you know, Karpathy said that people are looking at the point and they say that we're overhyping it, but they're not looking at the slope, which is being underhyped. And I think that's correct. Right. The point moat book, as an individual data point, is probably overhyped right now, but what it points at directionally is underhyped.

[Chris O'Neill]

Next 10 years. Final one. What excites you most? What do you like? I like optimism. What are you most optimistic for and excited about?

[Anish Akaya]

Oh, my God, dude. I mean, where do I start, right? Like robots, pet robots.

[Chris O'Neill]

So for me, it's like, specifically, like, actually medical. I think we'll have amazing breakthroughs in treatments like multiple cirrhosis, which my mom has, which is previously. She's been like, oh, bad luck. I think we'll have real breakthroughs there, which is super exciting for me.

[Anish Akaya]

Yeah. Okay. Well, let me tell you something personal to myself, which is. I'm a longtime transcendental meditation person. I've been meditating since I was a little kid, 25, 30 years. And it, like, brings me this, you know, this peace and joy that maybe you see a little bit of my personality. And I think that the idea that everybody could have a little slice of that peace and joy is something that is now becoming more and more possible because I think that with the technology we have, it's going to take away a lot of the rote parts of life. It's going to give people access to more of these types of relationships that they find so fulfilling. So I think just the kind of the NPS of the human experience, for lack of a better phrase, is on the way up. And like, I love that for my fellow person. That's what I'm excited about.

[Chris O'Neill]

Dude. It's such a pleasure to do this in person. Thank you so much for sitting down with me. I really enjoyed it.

[Anish Akaya]

Sorry I'm a little loopy. I can't tell if it's 3am or 3pm.

[Harry Stebbings]

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