Latest / The Learning Corner by Precursor / Episode #2: Anthony Kwesi Hagan, Euclid Insights, Sarah Tavel's Newsletter

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Episode #2: Anthony Kwesi Hagan, Euclid Insights, Sarah Tavel's Newsletter · The Learning Corner by Precursor

• 0:00
  One of my friends sent me this joke one time, which is like, there's no such thing as a shark
• 0:04
  attack.
• 0:04
  If you got in the ocean with the shark, you were at the shark's house, what do you think
• 0:07
  was gonna happen?
• 0:08
  I think about that a lot in the context of VC people dabbling into the world of PE.
• 0:12
  It's the week of September 30th.
• 0:15
  Welcome to the Learning Corner, a Precursor Ventures podcast.
• 0:22
  Welcome to the Learning Corner by Precursor where we talk about the articles and good reads
• 0:28
  that caught our team's attention over the last week.
• 0:32
  I'm Mia, and I'm here with Charles Hudson.
• 0:34
  Charles, how are you doing this week?
• 0:36
  I'm great.
• 0:37
  Calling in from the greater DC area today.
• 0:40
  How long are you gonna be there?
• 0:42
  I think I'm on the ground for a grand total of 24 and a half hours.
• 0:46
  I landed at 7:30 this morning and I take off at 7 tomorrow, so maybe less than 24 hours, I
• 0:52
  guess.
• 0:53
  Love it.
• 0:53
  Alright.
• 0:53
  We can just jump right into it this week.
• 0:55
  Let's do it.
• 0:55
  Let's kick it off with this week's topics.
• 0:58
  Topic number 1, buying time, unrealized returns, get used to waiting.
• 1:04
  It's a piece by Anthony Quasi Hagen found on LinkedIn.
• 1:09
  Anthony talks about the increasing trend of delayed returns on investment, particularly
• 1:14
  across private markets.
• 1:15
  He explains that longer holding periods for unrealized returns are becoming the norm due to
• 1:20
  changing economic conditions and market dynamics.
• 1:24
  Investors, both on the LP and GP level, are urged to shift their mindset to be more patient
• 1:31
  and understand that long term value creation may take more time than before.
• 1:36
  Additionally, he believes that the best way to continue amassing respect within a LP and GP
• 1:41
  relationship is a level of transparency regarding both the problems and positives of
• 1:47
  the dynamics of this type of a holding period.
• 1:50
  So, Charles, curious to know how different these types of questions or asks from LPs have
• 1:57
  become over the years, especially for a place like Precursor that comes in so early.
• 2:01
  How much of this is due to the market versus how much of this is inherently just part of
• 2:05
  Venture?
• 2:05
  Yeah.
• 2:05
  I got to know Anthony when he was at Crucial and have really enjoyed his writing.
• 2:09
  And for those who don't follow on LinkedIn, if you're a GP and you want some good LP
• 2:14
  perspective, I'd encourage you to follow Anthony.
• 2:16
  His writing is very good.
• 2:17
  Mia, it's been a real, I'd say, like, whiplash moment for me.
• 2:21
  When I started back in 2015, most LPs I talked to were pretty clear.
• 2:26
  They said, hey.
• 2:26
  Look.
• 2:27
  We know that it's gonna take time to get money back from these pre seed companies.
• 2:30
  They're so early.
• 2:31
  A lot of the LPs I talked to said, hey.
• 2:33
  We wouldn't be surprised if our seed or pre seed managers need 7 to 8 years to get to
• 2:38
  meaningful cash flow and DPI.
• 2:39
  Even that felt like a lot of pressure when you're doing 0 to 1 investing, but I'm like,
• 2:42
  okay.
• 2:42
  That gives me some sense.
• 2:43
  Now mind you, they didn't oftentimes share this to me until fund 3, and I was like, oh, I've
• 2:47
  had these expectations.
• 2:48
  I didn't know how you put back in fund 1.
• 2:51
  Right.
• 2:52
  But it felt to me like there was a recognition that pre seed was gonna take time.
• 2:56
  And then I think in 2020 and 2021, a lot of LPs I know got a lot of distributions out of
• 3:01
  Venture.
• 3:02
  Between IPOs, SPACs, big secondaries, a lot of money came back.
• 3:06
  So I found in that window of time, LPs weren't super concerned about time to liquidity.
• 3:11
  Also, the stock market was pretty good and interest rates were low.
• 3:14
  So if anything, they were looking for places to find yield.
• 3:18
  And then in 2022, everything changed.
• 3:21
  If you think about the last couple of years, we haven't had a lot of IPOs.
• 3:24
  We haven't had a lot of m and a.
• 3:26
  Stock markets are down.
• 3:27
  Thankfully, they've recovered.
• 3:28
  Interest rates went up.
• 3:30
  And a lot of LPs, particularly the ones who have two attributes, the ones who already were
• 3:34
  kind of maybe overweight venture, as in they had sort of more exposure to venture than they
• 3:40
  want from their model.
• 3:41
  A lot of those folks said, gosh.
• 3:43
  Maybe now is the time to dial back venture.
• 3:45
  There's also a lot of LPs who use the distributions from their existing venture
• 3:49
  program to fund the next set of commitments.
• 3:52
  So as they get money back from one fund, that's what funds the next set of commitments.
• 3:56
  And they just went from getting a lot of money back in 2020 and 2021 to essentially getting
• 4:00
  next to nothing back in 2022 and 2023.
• 4:03
  And I think it's a lot easier to be patient and have a feel good about a long hold period when
• 4:08
  you go through a period where you're rewarded for it and you get money back in large chunks.
• 4:12
  And I think a lot of LPs got to a place where they're like, I just need liquidity wherever I
• 4:16
  can find it.
• 4:17
  You know, there were words I never thought I'd hear about in the context of venture like
• 4:21
  continuation fund and strip sale.
• 4:23
  These are all tools that other private asset managers have used in the past, but they really
• 4:28
  haven't been part of the lexicon adventure.
• 4:30
  And I think there's also this tension, which is right now, LPs feel the need for liquidity.
• 4:35
  And I think if you're a GP and you're not engaging with your LPs that are on that
• 4:38
  conversation, at least making them understand that you understand what they need, I think
• 4:43
  you're making a mistake.
• 4:44
  But the flip side is these funds last 10, or as Anthony said, 10 plus 1 plus 1 plus 1 years,
• 4:49
  and my goal is to optimize the amount of money we return to our LPs over the life of the fund.
• 4:55
  And so there's this tension.
• 4:56
  You sometimes wanna do things in the short term that will provide liquidity and give them
• 4:59
  relief and meet their needs.
• 5:00
  But, also, in the back of my mind, Mia, I think some people, if we sold a bunch, will come back
• 5:05
  at the end and say, well, why did you sell so much?
• 5:07
  Why didn't you hold it to maturity?
• 5:09
  And I'll say, well, in the moment, it felt like the right thing.
• 5:11
  So I think LPs aren't required to be consistent, but I appreciate the ones who are
• 5:15
  clear, and I think the pendulum has really swung towards liquidity.
• 5:18
  And the thing I'll say that's hard in private markets, it's not like the stock market where
• 5:22
  you can just say, gosh.
• 5:22
  We're gonna go raise cash.
• 5:24
  Even though we love NVIDIA or even though we love our Apple stock, we're gonna sell it
• 5:27
  because we need cash.
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  To get liquidity in venture, you need a buyer on the other end if you're the seller.
• 5:33
  And I think in a lot of cases, the bid ask spread is so big that if you want to go create
• 5:37
  liquidity, you'd be selling really good assets at a pretty steep discount.
• 5:42
  And I'm not sure that that accomplishes the long term objective that most venture funds
• 5:46
  have.
• 5:46
  So I do think it went from a conversation where everybody was like, we're fine to wait because
• 5:50
  the prize feels like waiting.
• 5:52
  And then overnight, it felt like, we don't wanna wait at all.
• 5:55
  Give us everything you have.
• 5:56
  And I think that was a bit of whiplash for managers, and I just assume it's because the
• 6:00
  LPs were feeling whiplashed too.
• 6:01
  And it's a really difficult thing to navigate, and I just spent some time with one of our
• 6:05
  larger LPs on the East Coast.
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  And he's just like, look.
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  We understand.
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  Long time liquidity is a feature in precede.
• 6:12
  He's also a bug.
• 6:13
  He goes, it's both.
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  And I worry that some of the folks I've met have lost sight of that fact, but I get it.
• 6:19
  It's because they're feeling tremendous pressure at the institutional level to deliver
• 6:22
  liquidity back either to fund programs, could be to fund grants, could be to support some
• 6:27
  other initiative.
• 6:28
  The the need for liquidity is very real.
• 6:29
  It just reminds me of things that we've talked about internally, the tug and pull of deciding
• 6:34
  when to create a liquidity event specifically within maybe a secondary opportunity for some
• 6:38
  of, like, your best positions, but at a clear discount.
• 6:41
  He closes the piece with this reality.
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  There's an increased admonishment for lethargic exits from an LP perspective, but from a GP
• 6:48
  perspective as well.
• 6:49
  And he said, quote, I know many GPs view selling too early and leaving value on the
• 6:54
  table with the same disdain as incurring flat out losses.
• 6:58
  And then he argues that just focusing on the logical weighting of target returns on the
• 7:02
  deals could help uncomplicate this.
• 7:04
  How much of that is actually true that this truly does uncomplicate discussions with LPs?
• 7:08
  I'll say 2 things.
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  1 is, I think not all LPs are a monolith.
• 7:12
  You know, we have some LPs who are very focused on maximizing total cash on cash returns over
• 7:17
  the life of the fund, and they are time insensitive.
• 7:20
  They would rather have us hold it.
• 7:22
  We have others who are time sensitive due to needs they have in their own program, given
• 7:26
  their business model.
• 7:27
  Money today is worth more than money tomorrow in a meaningful way.
• 7:31
  And the question is like, how do you do what's right for your entire LP base when everybody
• 7:35
  has slightly different preferences and incentives?
• 7:37
  One answer that Anthony kinda mentioned LP secondaries kind of allow you as a GP to say,
• 7:42
  hey.
• 7:42
  If you wanna liquidate the whole position, you can make that decision without me having to
• 7:46
  then go decide a company that we're really excited about.
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  We're gonna sell it now to produce liquidity for a set of LPs who need it, whereas other
• 7:52
  people would want us to hold it.
• 7:54
  I think there's one really positive thing that's come out of this conversation, and I'd
• 7:58
  say, Will Quist, that Slow and I have talked about this, and I actually learned quite a bit
• 8:02
  from Rebecca Kaden at USV.
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  I think the conversation about selling and when to sell and discipline around selling and and
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  selling as a skill was not something most GPs talked about.
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  It was very much a buy and hold business.
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  And I think if anything, this has made a lot of us, including me, think more about, okay.
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  It's probably okay and preferred to sell some early along the way knowing that you're gonna
• 8:23
  give up some of the optimal return because 2 things can happen.
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  1, just shipping money back early feels nice.
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  And 2, not everything that goes up stays up.
• 8:30
  And if something gets stretched, and I would say, like, this has been a big evolution of my
• 8:33
  thinking is I'm now willing to do some selling in series b and c rounds for companies that we
• 8:38
  entered at the pre seed or the seed, particularly if the founders are selling some
• 8:41
  as well and there's an opportunity to get liquidity.
• 8:43
  It is nice to be able to give money back to our LPs.
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  I I told one of them, I can't change the destination, but I can make the ride smoother.
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  That's about the best I can do.
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  And I think getting money back along the way instead of having to wait to those terminal
• 8:54
  years to get everything back just feels better.
• 8:56
  What does that conversation look like with founders when you're typically electing to kind
• 9:00
  of raise your hand and offer that secondary opportunity?
• 9:02
  I find it's a relatively straightforward conversation if they have sold previously or
• 9:07
  are selling now, and if you're not talking about selling the entirety of your position.
• 9:11
  So I'm not at the point now where I'd wanna go running around on exchanges or trying to find
• 9:16
  things outside of the bounds of what founders would countenance and what they'd support, but
• 9:21
  I am open to having that conversation with people when they're raising rounds that are
• 9:25
  later.
• 9:25
  And we've been in a company 7, 8, 9 years, and we haven't redeemed anything.
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  But I don't I don't think I'm at the point where we would do anything, like, antagonistic
• 9:32
  or hostile.
• 9:33
  Thankfully for us, I find a lot of our founders understand our business model too.
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  And they're like, hey.
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  I've been working on this for 8 years, and you've been in it for 8 years.
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  So we're kinda We've been working on it for 8 years, so we're kinda We've been working on it.
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  Same time and see.
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  Mhmm.
• 9:43
  Yeah.
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  Yeah.
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  Awesome.
• 9:44
  Well, that was great.
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  Thank you so much, Anthony, for writing that up.
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  Topic number 2, the AI First Roll Up by Euclid Insights.
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  This piece discusses the all exciting world of venture back roll ups, specifically ones that
• 9:59
  are AI first and services driven despite lackluster returns on venture back roll ups
• 10:05
  from a true historical perspective.
• 10:06
  And the arguments in support of this strategy outlined in the article include recapture of
• 10:12
  margins, the advantage of buy versus build, the opportunity to more accurately underwrite
• 10:17
  potential efficiency improvements.
• 10:19
  And the arguments against this approach include questioning that margin lift from AI, the fact
• 10:24
  that roll up strategies are difficult to execute well at any scale, and the reality that
• 10:28
  for most VCs, quote, the juice simply may not be worth the squeeze.
• 10:33
  So Charles, curious to know actually how often within your circles do people at the GP level
• 10:39
  actually bring up roll up strategies, especially now, and and has the chatter
• 10:42
  increased with this emergence of AI?
• 10:44
  Yeah.
• 10:44
  I really like the Euclid team's writings on vertical software.
• 10:48
  They they're big thinkers in that category, so I I really enjoyed this article.
• 10:52
  I think a lot of people have been trying to figure out, well, what do you do with AI?
• 10:55
  And I think there was a moment where people said, instead of software as a service, SaaS,
• 11:00
  we'll do service as software, and we're gonna sell basically outcomes.
• 11:04
  We're gonna sell people a capability as opposed to selling them software that allows them to
• 11:08
  build the capability.
• 11:09
  And I think that's one of those things that just sounds really great on the surface as an
• 11:12
  idea.
• 11:13
  I think it's harder in practice.
• 11:14
  And so I've met a lot of people who said, well, maybe the right thing to do is to go start or
• 11:18
  buy a bunch of legacy assets, in this case, accounting or financial services or something
• 11:23
  that's kinda people driven, AI enable it, and run that same business at a much higher margin
• 11:29
  or at a lower cost, take the whole market, become sort of like a tech enabled service
• 11:33
  provider.
• 11:34
  I think that sounds great.
• 11:35
  But as the article highlights, I think it's really hard to run an efficient business that's
• 11:39
  trying to, like, compete on cost, but it's also making significant investments in r and d to
• 11:43
  keep the technology at the cutting edge.
• 11:45
  That's really hard.
• 11:46
  And I think this notion that, like, oh, we could roll all these things up and apply AI.
• 11:50
  I've always thought that, like, roll ups are mostly about cost cutting, efficiencies,
• 11:55
  financial engineering, you know, 1 +1equals3.
• 11:58
  That's not my world, but that's always been my impression.
• 12:00
  And I was like, that's not what most VCs are good at doing.
• 12:03
  Most of us are, as the article pointed out, looking for a capital light, high growth
• 12:07
  businesses with good margins.
• 12:09
  One of my friends sent me this joke one time, which is like, there's no such thing as a shark
• 12:13
  attack.
• 12:14
  If you got in the ocean with the shark, you were at the shark's house.
• 12:16
  What do you think was gonna happen?
• 12:17
  And I think about that a lot in the context of VC people dabbling into the world of PE.
• 12:22
  Those folks are very good at what they do when it comes to cost cutting.
• 12:25
  And the interesting thing is when I talk to my friends who do buyout, they're already doing
• 12:29
  this.
• 12:30
  They're maybe not rolling up companies, but they're immediately, as they buy these
• 12:33
  companies, looking at ways they can use they're just saying AI is yet another efficiency cost
• 12:38
  cutting tool that we can apply to this business.
• 12:40
  And if there's a case where the technology can help us cut costs and improve efficiency, we
• 12:44
  will use AI.
• 12:45
  If AI can't do it, maybe we'll move it offshore.
• 12:48
  But they're already doing some of this.
• 12:50
  They just don't write and blog and tweet and TikTok as much as VCs do.
• 12:54
  So I thought it was a really good articulation of the good, the bad, and, like, the perils.
• 12:58
  And my takeaway was, like, be careful if you go down this route.
• 13:01
  For those of you who might wanna read it, definitely zero in on the part about Metropolis
• 13:05
  parking.
• 13:06
  There are some cases where I think it does make sense where you have an asset that is a local
• 13:10
  monopoly asset where once you own it, people have to deal with you.
• 13:13
  They talk a lot about just how hard it is to get software into some of these categories.
• 13:16
  I think we've also seen some of this in digital health.
• 13:19
  There have been venture firms that have talked about buying hospitals because a hospital that
• 13:23
  you can control, you can essentially roll out whatever technology platforms and services you
• 13:28
  want as opposed to trying to sell through the bureaucracy as an outsider.
• 13:30
  So I think as technology gets more powerful, software investors are gonna look for new
• 13:34
  models and new structures and ways to push this stuff out.
• 13:37
  More is just another thought for that specific example for hospitals is you can apply AI
• 13:42
  layers onto it and drive efficiency, but at what cost?
• 13:44
  And this is kind of what you were saying of, like, where do we have a decrease in quality?
• 13:48
  Like, where do we lose patience?
• 13:50
  There are things there to consider.
• 13:52
  I agree with the article's rhetoric that obviously there's a clear enterprise value
• 13:55
  captured through AI first aggregation strategies.
• 13:58
  But the question is really around whether that's where venture dollars should be going,
• 14:03
  especially in this later adopter market where these acquisitions could typically take place.
• 14:09
  So a final question about this is specifically in areas where they're traditionally slower to
• 14:14
  adopting technology?
• 14:15
  What are the things that investors should look out to of being like, this is the right
• 14:18
  opportunity to do this versus another that's not?
• 14:21
  The thing I can see that makes sense, so they kinda touched us at the end of the article.
• 14:24
  The idea of doing a roll up and, like, let's say, buying a 100 accounting firms as the
• 14:28
  people who run them retire, that seems hard.
• 14:31
  Buying 1 and using that as a platform and tech enabling that one and then using that existing
• 14:36
  book of business, the existing licenses, whatever infrastructure you have, and using
• 14:40
  that as a platform, that I think I can see working as a way to just jump start.
• 14:45
  And I think you're seeing some of these early AI companies look to buy data providers,
• 14:50
  models, like, looking to buy legacy assets.
• 14:53
  Like, there's a little talk about Harvey trying to buy some things in the legal space.
• 14:56
  I I think you're gonna see people who have balance sheets say, if we buy this legacy
• 14:59
  asset, it's actually worth significantly more to us than it is on its own.
• 15:04
  And if we were to buy and absorb it, we could sort of turbocharge the thing that we're
• 15:07
  building.
• 15:07
  More to read there.
• 15:08
  Definitely feel free to jump into that article on your own time.
• 15:11
  Rolling into our final topic, topic number 3, thinking through the future for LLM companies
• 15:18
  and what this means for b to b AI startups is a piece from Sarah Tavel's newsletter found on
• 15:24
  Substack.
• 15:25
  Sarah elaborates on a previous piece of hers where she describes how LLM funding is like one
• 15:32
  big stack poker game.
• 15:33
  She says how these big stack poker players like Meta, Microsoft, Google, they really don't have
• 15:39
  any other choice but to continue raising their bets as the prize of coming out on top is far
• 15:44
  too good, and if you pause for one second, you could be left empty handed.
• 15:47
  So this week, she expanded on the future of this game calling into a reality where LLM
• 15:53
  players will look to validate these investments gone into training the models by moving, quote,
• 15:57
  up the stack and evolve from an API or chat interface to an async agent.
• 16:03
  More simply put, if you're an AI native application company, the foundational model
• 16:08
  company is likely can or maybe will have the tech to build out these capabilities and remove
• 16:13
  the need for any such API integration.
• 16:16
  And one of Sarah's suggestions for b to b AI startups to combat this reality is to, quote,
• 16:22
  execute like hell and land grab in an overlooked vertical.
• 16:25
  I know our team has spoken to 100 of companies in this space.
• 16:31
  But, Charles, what are some of the questions you need answered by these types of founders to
• 16:36
  get a little bit more comfortable?
• 16:37
  The thing that really struck me, having spent more time with some folks at OpenAI, is the
• 16:43
  compounding rate of innovation at that company is unlike anything I've seen in a really long
• 16:47
  time.
• 16:47
  I read Sarah's post.
• 16:48
  I was like, I think it's equally likely that these platform companies will accidentally end
• 16:52
  up competing with people.
• 16:53
  And not through any purposeful innovation, but they will release capabilities that make things
• 16:58
  that were hard trivially easy, which will mean that the thing that you did that was unique and
• 17:03
  interesting is no longer hard to do.
• 17:06
  I think, to me, that's what I keep coming back to.
• 17:08
  And, like, I think most of the model providers want the models to be more powerful, which
• 17:12
  means on their own, the models will be more capable, which means, like, the specialty
• 17:16
  things that you need specialized apps to do.
• 17:20
  But I don't get the sense that the model provider's goal is to sort of laser attack
• 17:25
  specific applications and say, like, we're gonna build it.
• 17:29
  I think what's more likely is it's gonna be, hey.
• 17:30
  Instead of a specialty contract analysis tool, you can feed it to the LLM.
• 17:34
  You don't need all the specialties.
• 17:36
  Because a lot of what the specialty stuff is doing, it's massaging the inputs or the outputs
• 17:41
  of an LLM.
• 17:42
  Because if you just gave it the thing un massaged, you wouldn't like the output.
• 17:46
  As the models get better, whether it's reasoning, whether it's, like, more like, as
• 17:50
  they get better, I think naturally, they're just gonna be more capable.
• 17:54
  And so this is the thing I keep coming back to is I could point to 8 or 10 companies that I
• 17:59
  met that were working on voice enabling chat gpt a year ago, and I was like, I'm pretty sure
• 18:05
  chat gpt, they're going to have a voice enabled service.
• 18:08
  So if your whole value prop is you can talk to us like you're talking to chat gpt, that
• 18:13
  doesn't strike me as a great moat.
• 18:15
  And it's turned out that, like, voice mode first of all, I think voice mode is awesome.
• 18:19
  I use it all the time.
• 18:20
  But it kinda does what those companies sought out to do, but better.
• 18:24
  Like, it doesn't require an additional app.
• 18:26
  It's just better.
• 18:27
  There are things that were hard for me to do in GPT 3.5 turbo that, like, 4 o makes easy.
• 18:33
  So I read Sarah's post, and I was like, this just reinforces my, like, you know me.
• 18:37
  Yeah.
• 18:37
  I have all kinds of about AI investing as a as a seed investor.
• 18:41
  And I'm just like, the real risk is that the things that you build to produce a result based
• 18:46
  on the current state of AI, 12 months from now will be trivialized.
• 18:50
  And so I I wouldn't be surprised if the steady drumbeat of progress means that a lot of people
• 18:55
  who are building vertical applications to solve a problem, the models eventually get good
• 19:00
  enough that the wrapper you need around AI to get the result you want becomes less and less
• 19:04
  meaningful because the models are just better and more powerful.
• 19:07
  Now, look, that presupposes that the model companies continue to raise the tens or 100 of
• 19:11
  1,000,000,000 of dollars required to continue to step change, improve the models.
• 19:16
  I just think the rate of change in this industry is so high.
• 19:19
  I'm not sure how you confidently make bets at the infrastructure or application layer without
• 19:24
  thinking about this stuff.
• 19:25
  To your earlier point, maybe the foundational models aren't coming after every single thing
• 19:31
  that these applications are building, but then you better hope that you are the best
• 19:35
  application at doing what you're doing.
• 19:36
  So then if somebody doesn't want to use what the foundational model is doing, you are right
• 19:40
  there as the next choice.
• 19:42
  And that's a very difficult task to achieve.
• 19:44
  So it goes to my final question, which is if I'm gonna put myself in the shoes of a founder
• 19:48
  in b two b AI startup land, I do feel a little bit discouraged hearing that basically
• 19:53
  everything I create is too late.
• 19:55
  Is that truly where my mind should go?
• 19:59
  This is the conundrum I can't solve.
• 20:01
  If you know that whatever version of AI you're using today is the worst version you'll ever
• 20:06
  use, the impetus is to wait.
• 20:08
  Usually, in technology, oh, if I don't start today, I'm gonna miss out.
• 20:10
  I'm like, actually, this technology is getting better and cheaper every day, so there are
• 20:13
  things that are impossible today that will be affordable and simple 9 months from I don't
• 20:18
  even know what those things are.
• 20:19
  I'm willing to go out on a limb and say there are things that we think are hard problems that
• 20:22
  will cease to be hard problems in 9 months.
• 20:24
  Just think about reasoning.
• 20:26
  If you were trying to figure out, well, how do I make Chegg PPT reason?
• 20:30
  I've written all this code and fancy no.
• 20:32
  You're like, no.
• 20:32
  It just reasons.
• 20:33
  All the work you did to figure out to simulate reasoning, it just it just does it.
• 20:37
  And you're like, oh, we have all these artifacts, all the stuff we built that's
• 20:41
  suddenly not that valuable.
• 20:42
  And maybe there's some lessons you learned and but, like, as a practical matter, it's not an
• 20:46
  edge anymore.
• 20:47
  And by the way, like, the new thing is, like, faster and cheaper.
• 20:50
  I don't know how you solve this problem except to go into this eyes wide open and say, I'm
• 20:55
  jumping into a really dynamic industry.
• 20:57
  And if anything, I would say, if there's a problem that seems like it's too hard to solve
• 21:01
  with the current state of AI, I know it sounds paradoxical as an early stage VC, The optimal
• 21:05
  strategy might be to wait or to get really close to the people at Anthropic or OpenAI or
• 21:10
  Google, wherever.
• 21:10
  Get really close to them because they might tell you, hey.
• 21:13
  In 3 months, we're gonna release something that's gonna be amazing.
• 21:16
  And so don't spend a bunch of cycles trying to solve this problem because we're gonna solve it
• 21:20
  for you.
• 21:21
  So I don't know.
• 21:22
  I think it takes a particular type of entrepreneur to ride this wave.
• 21:26
  Well, we are all out of time for this week.
• 21:30
  So thank you, Charles, and thank you to our listeners for popping by the learning quarter.
• 21:35
  If you love the podcast, please subscribe and share it with a friend.
• 21:39
  Can't wait to see you all next week.
• 21:42
  Bye.
• 21:42
  Bye, everybody.