Latest / The Learning Corner by Precursor / Episode #21: Anthropic's Latest Raise, Internal Turf Wars in Big Tech, IPO Alternatives In Venture

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Episode #21: Anthropic's Latest Raise, Internal Turf Wars in Big Tech, IPO Alternatives In Venture · The Learning Corner by Precursor

• 0:00
  Think the venture business historically has been built on the IPOs are what create your
• 0:04
  legendary funds.
• 0:05
  Being in an Uber or a Twitter or a Google or a Facebook, that's how you create legendary
• 0:09
  funds.
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  But what happens if those IPOs just don't happen or if they happen twenty years after
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  formation in a world where most venture funds have ten year lives?
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  What do you what do you do?
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  It's the week of February 24.
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  Welcome to the learning corner, a Precursor Ventures podcast.
• 0:29
  Welcome to the learning corner by precursor.
• 0:30
  I'm Mia Farnam and I'm joined by our GP and managing partner, Charles Henson, where we will
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  be talking through the articles and Goodreads that caught our team's attention over the past
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  week.
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  Topic number one, amidst the frenzy a month back with deep seek, according to Reuters,
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  Anthropic is finalizing a $3,500,000,000 funding round that will bring its valuation to
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  $61,500,000,000 showing there is still eagerness from investors to continue funding
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  the more expensive foundational models headquartered in The US.
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  I never thought anything going on with DeepSeq or probably any other competitors in this space
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  would dry up any interest.
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  Yeah.
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  In open AI, anthropic, etcetera.
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  But it's even more clear to me now that the carrot at the end of the stick of strategic
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  positioning that is won from being part of these rounds is such an important part of this
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  investment mindset.
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  So the funding round is actually even larger than what Reuters reported last month by
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  $1,500,000,000 So curious to know where your thoughts are since we have a continuing thread
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  about this on our team and in the podcast.
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  I've long felt like a lot of this big ticket, large model stuff is a big poker game, and you
• 1:41
  gotta have the chips to stay in the game.
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  And if you don't have the chips, you can't invest in the next generation of your model.
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  And if you can't invest in the next generation of your model, you're not competitive.
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  And I think at some point this year or next year, we will find out, is there any residual
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  value in a LLM provider who can't keep going?
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  To me, it's inevitable that at least one or two of the reasonably well funded people will fall
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  behind and won't be able to continue to raise this money.
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  I think it's interesting to see how this all plays out.
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  The other thing that's crazy to me to think about is even if you'd invested in this company
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  at a 5 or $10,000,000,000 valuation, which would have felt hard to imagine, you'd be up
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  somewhere between five and ten x your money on paper.
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  And I think right now, under the current thinking, the LLMs feel like the big winners in
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  this category for a lot of people.
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  And they're like, hey.
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  If these end up being the Google or the AWS of AI, this might be the best.
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  And I also just think we're in a world where bigness begets bigness.
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  You get to a certain size, and if you get to a billion dollars, the probability that you'll
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  get to $5,000,000,000 in this environment is actually reasonably high if you continue to
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  execute due to the supply of capital.
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  And look, if you're like, hey.
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  I wanna bet on an LLM provider that's likely to be one of the winners provided that these high
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  capital LLM models end up being long term valuable.
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  The two best bets to make that are available to you are Anthropic and OpenAI, and anything
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  after that is highly speculative.
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  It's crazy what you said before.
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  From the last round to the current round, you could have been at five x.
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  You also could have probably made some liquidity if you wanted to because everyone
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  would be clamoring to come and take up whatever allocation is available regardless of what
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  happens in the news or what we see with DeepSeek, etcetera.
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  I guess from my vantage point, I was starting to see in this current round and starting to
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  carve out maybe a more distinctive consumer approach with lower price points for computing
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  power, hybrid reasoning models, one of which they just released out this week, and even
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  relatable benchmarks like the Pokemon tests that they did.
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  But Yeah.
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  Is it truly for differentiation, or is it just for marketing?
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  Kind of just wondering, are we watching actual competition for market share or if both
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  Anthropic and OpenAI are essentially just running the same playbook, raising tons of
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  unprecedented capital to secure computing resources and talent while the business model
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  itself is secondary.
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  So are investors of both companies just funding genuine alternatives to one another, or are
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  they just inadvertently creating an AI duopoly where the primary competition is more so for
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  capital than customers?
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  Yeah.
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  I think you took the words out of my mouth.
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  But I also think if I were a large customer who needed an LOM solution, I would want DeepSeek
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  to be healthy.
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  I would want Anthropic to be healthy.
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  I'd want OpenAI to be healthy.
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  I'd want Gemini to be healthy, and I'd want Llama to work For a couple reasons, one, I'd
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  want the ability to price compare across those services just like we see in our portfolio
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  companies.
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  You know?
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  It'd be a different world if AWS was the only option, but you've got GCP, you've got Azure,
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  you've got, for the really large people, the ability to self host.
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  And I think, actually, that competition is good for consumers, but it's also good for those
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  companies.
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  I'm sure their bottom lines would be better with less competition, but the presence of
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  other people competing for that business forces them to push cost down or provide better
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  service or continue to invest in new products and services.
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  So I think it would be customers who would benefit the least if this was a monopoly
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  situation.
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  Because then not only would you be stuck with one model, you'd be forced with the prices
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  offered by those models or the model providers.
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  So I think customers will continue, I think, to support multiple model providers because it's
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  in their best interest to have choice.
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  I mean, we see it on our team internally when we're using different tools.
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  You and I both, I feel like, subscribe to a lot of the different models and pay the monthly
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  price to get the pro version of it all.
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  And I think a lot of that is to do with, we like to compare and see what the differences
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  are.
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  My question is at what price point would somebody not be as curious to leverage it?
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  And this is truly more so from like a d to c angle, not an enterprise level at all.
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  I'll say this.
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  I remember when Spotify came out and my friend was like, can you imagine that you could have
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  basically all of the world's music in your pocket for, like, $10 a month?
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  That seems like a criminally cheap price.
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  And then if I told you you could have the world's smartest supercomputer in your pocket
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  for $20, I think most people would say that's a criminally cheap price.
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  And the thing that's been eye opening to me is I know a lot of students who pay for ChatGPT.
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  You know, students are cheap, but I think if a student tells you that ChatGPT is worth $20 a
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  month, it's really worth at least $20 a month to them.
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  And I think the more interesting thing is as ChatGPT does more, as perplexity pushes the
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  envelope, like, how many of these things are people gonna pay for?
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  As I explained to our CFO, I actually really need to pay for all of these things for testing
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  and learning purposes.
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  I spend hundreds of dollars a month on AI tooling.
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  That is not normal.
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  I don't expect most people to do that either in a business or a professional context.
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  I think most people will end up paying for one of these things, somewhere between zero and one
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  of these products.
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  And I will say this, Mia.
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  I scoffed at paying for JetGPT Pro, and then I said, I should just pay for it and see if it's
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  different.
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  Hey.
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  It is pretty sweet.
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  I'm like, wow.
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  For $200, I get to experiment with an agent.
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  I get essentially unlimited use of deep research.
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  I get all of these other models.
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  Is it worth $200?
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  The way I've been using it, it's actually worth more than that to me.
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  The interesting part is now also we're seeing folks, not you and I, unfortunately.
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  We're not that young.
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  But folks who are growing up with these tools, they probably won't know an alternative without
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  them.
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  They've only grown up in a world where access to those types of models is priced at 200 a
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  month.
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  And so they can't imagine what it's like, so that's normal.
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  It'll be really interesting to see how it all flows generationally too, even from a macro
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  perspective.
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  Our second topic was by Erin Woo at the information titled Google's AI efforts marred
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  by turf disputes.
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  The article details how Google's AI development is being hindered, not by the capacity and
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  ability to build, but rather internal organizational tensions.
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  Erin walked through what non Google folks didn't see when notebook LM was launched and
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  hailed as a success.
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  According to the article, apparently, there were clashes between the Google Labs
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  experimental unit and folks on the workspace team, all wanting to draw specific parameters
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  around what turf they own and what innovation capabilities should be brought in by outsiders.
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  The tension expands to other areas.
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  DeepMind and Google Cloud sharing conflicting priorities, Sundar having to scale back Pixel's
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  AI assistant to not internally compete with the Gemini assistant.
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  Despite reorganization efforts to consolidate AI initiatives under DeepMind, these conflicts
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  persist.
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  So from the vantage point of this article, we are really seeing how the frenzy and
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  opportunity around AI innovation has created such tension internally.
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  However, it's clear that dynamics like these arise simply when a company becomes massive.
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  And there was a great quote by Carl Bass, who's the former Autodesk CEO and known former
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  special advisor to Larry Page, who was quoted saying big companies get in their own way.
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  Small companies have a much more defined path to getting stuff done.
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  So I was curious what you thought here.
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  I wish I could, like, cite the person who said this, but I don't think I have their
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  permission, so I won't.
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  I talked to someone who's looked at a couple of these coding co pilots like Cursor, and I was
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  like, how does Cursor beat GitHub CoPilot?
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  Like, GitHub Copilot has all the developers because of GitHub.
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  And this was before this article came out.
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  I don't think this person had any proprietary insight into this notebook.
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  Elon case is that we're betting that in some of these cases, the turf wars and political
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  battles between product owners in these companies will inhibit their ability to ship
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  product.
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  And that these companies will succeed in spite of all of the distribution advantages that
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  these big companies have.
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  They will succeed.
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  And I thought about one really specific example that I lived through.
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  I worked at Google at a time when Google Drive was known as platypus, and Google Drive was
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  under development, and there was a lot of time and effort put into it.
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  And Dropbox came out, and everyone's like, we're gonna, like, crush these like, there's no
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  way this little start up company and the thing you realize at a big company is not only do you
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  have to fight all these political battles, you also have to deal with the problems at scale,
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  which is if you're at Dropbox, you can say, hey.
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  This is the thing.
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  It kinda works.
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  It only works on these computers.
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  It only works on these you can launch a constrained product.
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  When you're a Google or a Microsoft or a FAANG company and you roll something out, it kinda
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  has to work for a lot of different edge cases and use cases.
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  And there's a level of polish and finish that people expect even on v one.
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  And it's gotta be multilingual, and it's gotta work it's gotta comply with these data
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  requirements.
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  You end up having to do so much work.
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  And then when you launch it, you can't quietly launch it and tinker because you launch it and
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  everybody notices.
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  And the question is, how do you know if you're Snapchat and you're like, we have stories, but
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  Facebook's gonna copy stories, but it's not gonna kill Snapchat versus the little
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  featurettes that sometimes get crushed when a big company announces a new product capability.
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  And my general rule of thumb is you never wanna as my friend used to say, you never wanna
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  compete with a shark in the ocean.
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  You don't wanna compete with a big company in their core domain.
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  I think until very recently, it was nearly impossible to compete with Google in Core
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  Internet search.
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  They effectively beat back everybody who attempted to do that, and Perplexity and
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  ChatGPT are probably the first real threats they faced.
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  And so I think we will end up seeing a really mixed bag here.
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  There'll be some great Harvard Business School case studies, and maybe it's Cursor, maybe it's
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  Replit, maybe it's I don't know.
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  Pick your favorite AI powered tool that's competing with an incumbent that has a
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  distribution advantage.
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  There'll be some story about how internal politics or some other miscalculation by a big
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  company created space for somebody to really get a foothold.
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  And there'll be other examples where the distribution advantage of the incumbent snuffed
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  out the entire opportunity almost immediately.
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  So I'm very curious to see how this plays out.
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  And I think if you really know the inside of these companies and the personalities of the
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  leaders, you might be slightly more attuned to picking out the ones where it's worth going toe
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  to toe.
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  But you have to wonder, Google must have reasons why they invested in Anthropic even
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  though they have tons of money going into their own in house AI tools.
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  It's almost saying some of the things that maybe they can't acknowledge themselves about
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  how quickly they need to scale a product in a way that works at the scale that people want
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  it.
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  So taking bets outside their business probably makes sense.
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  I think it was interesting.
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  I was just reading an article.
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  I don't remember where I saw it.
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  I might have saw it on blue sky.
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  It was about Amazon shutting down their Steam competitor after putting a quarter of a billion
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  dollars into it.
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  And they were like, it sort of never occurred to us that we wouldn't win.
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  And the person who wrote in the article, there was a big part who was like, well, we relied so
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  much in distribution that we didn't really do all the things we're supposed to do to make
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  sure this was a product that people wanted and that we understood why they wanted it.
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  And I do think sometimes big companies overestimate the value of distribution and can
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  skip really important steps about customer discovery and, like, building something that
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  people want.
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  Tempting to just put something out there when you know that it's gonna get distribution.
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  Taking an entirely different perspective on it.
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  I mean, their core issue just seems to be balancing innovation with protecting existing
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  revenue streams.
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  So they're essentially just neutering their own AI products to avoid cannibalizing on the
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  current businesses.
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  Is this strategy ultimately just self defeating in a really quickly evolving market, or is
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  there room or possibility that this cautious approach could actually be more prudent than
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  the move fast philosophy that I feel like is just sweeping across AI right now.
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  I think one of the hardest things to do when you're running a business that's working is you
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  can totally see the future.
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  And I think lots of businesses think, oh, well, let it continue to erode, and we'll try to cut
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  over just at the moment where the new thing is working, and it never works because you can't
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  predict the rate of erosion.
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  That old saying about, like, it's hard to get a man to believe one thing when his paycheck
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  believes in something else being true.
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  And I think it's really hard for big companies to be like, we have just this massive business
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  doing thing x.
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  And if you look at the history of most tech innovation, that's how it's gone.
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  You know?
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  When Google bought Rightly and started doing docs and spreadsheets, those products were not
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  as good as Excel and Word.
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  They had one real advantage.
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  They were much better at real time collaboration.
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  And there are a bunch of things that Google did in the cloud that were inferior to desktop
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  products until everything moved to the cloud.
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  And then there are a bunch of things in social that, like, Meta understood much better than
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  Google did.
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  And it seems to me that there are some things in this AI world that the upstarts seem to
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  understand or be able to grasp and implement faster than people who have, to your point, a
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  business to defend.
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  And it's really hard as a public company to say we're gonna put the entire franchise at risk to
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  chase something that's still kind of unproven.
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  Moving on to the last topic.
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  I don't have a specific article on this just because it thread that everyone has been
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  talking about, honestly, since probably q two twenty twenty four.
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  But it's focused on the lack of IPOs as we kind of barrel through q one of twenty twenty five.
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  I mean, 2025 was seen as the redeeming year for IPOs for most venture capitalists after such a
• 14:20
  drought over the last few years.
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  So we're almost through February somehow, and IPO activity and announcement has not turned
• 14:27
  out in a way that most individuals were hoping for.
• 14:30
  I know on behalf of the VC land, for sure.
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  So there are still a lot of big names expected to go public in 2025.
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  So you have like stripes, Databricks, Clorino, all folks that people would love to see them
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  announced.
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  However, I think there are broader questions around IPOs as the main route for venture
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  backed companies to return capital back to investors.
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  And I know that you have some thoughts specifically around the area, so I wanted to
• 14:53
  kind of dive deeper with that with you.
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  Yeah.
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  I would encourage people to read Aaron Griffith's article.
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  I thought it was really good in framing this.
• 15:00
  I think it's gonna be interesting.
• 15:00
  A lot of people said the second that we have the new administration, all of the animal
• 15:05
  spirits will be unleashed, and there will be pent up deal demand.
• 15:08
  And I'm like, I don't think that's true.
• 15:11
  I don't think antitrust and regulatory was the only reason deals weren't getting done.
• 15:15
  I certainly believe that that was a contributor in some cases.
• 15:19
  You look at Figma, Adobe, it was absolutely an issue there.
• 15:23
  There were other things that were done in that transaction that maybe were suboptimal.
• 15:26
  But, look, I think part of the challenge is there's never been more private capital
• 15:30
  available for scaled late stage companies.
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  And if I were the CEO of a late stage private company, and I'm not, if my choices were remain
• 15:38
  private, continue to raise money to fund your growth, have a board of your largely of your
• 15:42
  choosing because you chose the investors and you chose the board, not be subject to
• 15:47
  quarterly earnings calls, not be subject to the whims of Wall Street, not be subject to
• 15:51
  activist investors and short sellers.
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  I'd be like, you know what's better?
• 15:55
  Being the CEO of a private company.
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  And if I don't need the public markets to raise money and if my investors, employees, and
• 16:02
  management team can get liquidity through these regularly scheduled tender offers, what do I
• 16:06
  really get by being public?
• 16:07
  You get a public currency, but honestly, as an investor, if Stripe wanted to buy one of our
• 16:11
  companies, I would consider that a quasi public currency.
• 16:14
  I'd be just as happy getting Stripe shares as I would getting Visa shares or JPMorgan.
• 16:19
  It wouldn't really matter to me.
• 16:20
  So I think right now, these late stage companies have all of the benefits of being
• 16:24
  public and liquidity and none of the and put aside all the regulatory and compliance costs
• 16:29
  associated with going and being public.
• 16:30
  I actually think these companies could absorb those, but but those are real costs.
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  It's unclear to me, like, why you'd wanna do it.
• 16:36
  And to me, if you pull on that thread, you're like, most of the transactions in venture that
• 16:40
  generate liquidity are m and a.
• 16:41
  Historically, it's been, I think, eighty twenty m and a to IPO, but the massive, massive,
• 16:46
  massive halls come from IPOs.
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  And I think the venture business historically has been built on m and a's kinda like help you
• 16:53
  chip away.
• 16:54
  The IPOs are what create your legendary funds.
• 16:57
  Being in an Uber or a Twitter or a Google or a Facebook, that's how you create legendary
• 17:01
  funds.
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  But what happens if those IPOs just don't happen or if they happen twenty years after
• 17:06
  formation in a world where most venture funds have ten year lives?
• 17:09
  What do you what do you do?
• 17:10
  The business isn't set up for that.
• 17:11
  And, yeah, you could do a continuation.
• 17:13
  But there's a lot of mechanical things you can do.
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  But I think, to me, it just highlights my belief that secondary liquidity is gonna become
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  a much bigger source of venture fund distributions and the money that goes back to
• 17:25
  investors than it's been in the past.
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  And I think for small funds, it could become the predominant source of liquidity in the next
• 17:32
  decade.
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  Because as a pre seed fund like us, if we were in Stripe, we'd be fifteen years in with the
• 17:38
  IPO date, which I'm sure the the board is obviously talking about.
• 17:41
  It's not going to be this month.
• 17:43
  So there's a possibility it could be eighteen to twenty years before you could distribute
• 17:47
  those shares to your LPs.
• 17:48
  I love the patience of our LP base.
• 17:49
  I don't think they're that patient.
• 17:50
  If you're an early stage fund, can you become a legendary fund by spotting secondary
• 17:54
  opportunities early and then, I don't know, creating liquidity for your investors at the
• 17:58
  threshold that you needed to, but then secondaries.
• 18:00
  There are a couple things that happened last year that really got my attention.
• 18:03
  One of the big ones was, like, when Google almost bought Wiz because that's a company that
• 18:07
  you would have had to pay a hundred and 20 ish million post to get into, but you would have
• 18:12
  gotten out at 23,000,000,000 in an m and a transaction, not an IPO.
• 18:16
  And as far as I understand, there were opportunities to take secondaries along the
• 18:20
  way.
• 18:20
  Part of the reason that you needed IPOs was that was the only way you could get billion
• 18:24
  dollar liquidity events to the tunes of billions of dollars.
• 18:27
  But if now in the private markets, you can get out of these companies at $10.15,
• 18:31
  $20,000,000,000, it's effectively replaced the liquidity that you could only get from IPOs.
• 18:36
  So in that world, like, even VCs don't really need IPOs anymore if you get in early enough.
• 18:41
  I think the challenge is for the big funds, if you're on the board and you own 20%, it's
• 18:45
  harder but not impossible to sell a portion of your stake.
• 18:48
  I understand what the mechanism and the journey kinda looks like at early stage for our funds.
• 18:52
  But for folks who jump in later and take up much larger check sizes, they need guaranteed
• 18:57
  multibillion dollar outcomes.
• 18:59
  They have to.
• 18:59
  Yeah.
• 19:00
  I think also if you own let's say you own 5% of Stripe, which is probably at this point a
• 19:05
  $3,000,000,000 position, and your LPs were getting antsy, you could create a continuity
• 19:09
  vehicle.
• 19:10
  You don't wanna hang around for the IPO.
• 19:12
  We we're here.
• 19:13
  We're ready to buy it.
• 19:14
  If you're patient and wanna stay in, we're gonna park this over here in a new vehicle.
• 19:18
  And so I think the financial sophistication of the venture model is gonna continue to evolve,
• 19:23
  and it's gonna evolve towards complexity and not simplicity as these hold periods get
• 19:28
  longer.
• 19:28
  All of the things that PE firms mastered twenty and thirty years ago, we're learning from first
• 19:33
  principles today.
• 19:34
  And, like, attempting to master them in one year.
• 19:36
  In
• 19:36
  2024 and 2025.
• 19:39
  We are all out of time for today.
• 19:40
  Thank you, Charles, for stopping by.
• 19:42
  Thank you to our listeners for listening.
• 19:43
  Please like and subscribe, and we will all talk to you next week.
• 19:46
  Thank you.
• 19:47
  Bye.