Latest / The Learning Corner by Precursor / Episode #84: Convicted vs. Disciplined Healthcare VCs, The Capitalist Multiverse, The Untrainable

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Episode #84: Convicted vs. Disciplined Healthcare VCs, The Capitalist Multiverse, The Untrainable · The Learning Corner by Precursor

• 0:00
  This is the lesson I think VCs always relearn.
• 0:02
  We relearned it with Google.
• 0:04
  We relearned it with Facebook.
• 0:05
  I think we've relearned it with NVIDIA.
• 0:06
  The big companies end up being much bigger than you think because usually there's some
• 0:11
  combination of tailwind and timing that pushes them to a place that was hard to imagine
• 0:15
  before.
• 0:15
  And I think so long as that's the case, there will be companies that are worth paying for,
• 0:19
  but I don't think that means that on average, price and ownership don't matter.
• 0:22
  You know, we only have one SpaceX.
• 0:24
  We have one Anthropic and one OpenAI.
• 0:26
  I just don't know that you should just throw all of the playbook out of the window.
• 0:30
  It's the week of June 22.
• 0:33
  Welcome to The Learning Corner, a Precursor Ventures podcast.
• 0:38
  Welcome to The Learning Corner by Precursor.
• 0:40
  I'm Mia Farnam, and I'm joined by RGP and managing partner, Charles Hudson, where we will
• 0:44
  be talking through the articles and Goodreads that caught our team's attention over the past
• 0:48
  week.
• 0:49
  Our first piece this week is from Halitechko's Substack, Massively Better Healthcare, and it
• 0:54
  explores one of the more contested questions in venture right now, does ownership discipline
• 0:58
  still matter when AI is enabling companies to grow faster and raise at higher valuations than
• 1:03
  ever before.
• 1:04
  The piece maps out a really clear split between two camps of health care investors.
• 1:09
  The first are the convicted.
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  They've essentially retired ownership thresholds as a binding constraint,
• 1:15
  underwriting each deal on its own terms and stretching if the conviction is strong enough.
• 1:19
  The second bucket is the disciplined, and they argue that when markets get frothy, the
• 1:24
  ownership bar matters more, not less, and they're sourcing earlier and writing bigger
• 1:29
  checks to hold the line.
• 1:31
  Where both camps agree is that no one is bargain hunting.
• 1:35
  Everyone believes this AI moment is structurally different from prior bubbles, and
• 1:38
  the clearest signal of a durable business is the multiyear enterprise contract in health
• 1:43
  care.
• 1:44
  That's never changed.
• 1:45
  The open question here neither side can fully answer yet is whether health care's structural
• 1:49
  reality is the longer sales cycle, the complex regulations, finite market sizes will
• 1:54
  ultimately bound AI's upside in ways that make ownership discipline matter more here than
• 2:01
  anywhere else.
• 2:02
  Obviously, this piece focuses on the health care of it all, and it's just a different
• 2:07
  industry than I think what we see in the media when we see companies race to a 100,000,000 in
• 2:12
  ARR so quickly.
• 2:13
  They're typically selling to more traditional b to b customers with much larger budgets and
• 2:17
  room for experimentation than customers in health care who you and I both know from lived
• 2:22
  experience investing in those places where you're typically floating maybe a single digit
• 2:26
  to negative margin if you're on the health system side.
• 2:29
  You're a payer.
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  There's just longer cycles.
• 2:32
  So maybe zooming out a bit more broadly, we can talk about the health care of it all, what this
• 2:36
  dynamic looks like for that specific industry, but then how does this dynamic of the convicted
• 2:40
  versus the disciplined, does that take a different form in different industries as it
• 2:45
  pertains to AI and the pricing that we've been seeing?
• 2:47
  I think software has always had people in the, like, price doesn't matter crowd and that you
• 2:53
  should just be in the hot com I feel like health care as someone doesn't invest in as
• 2:57
  much health care as others, I always felt like it was more of a monolithic community.
• 3:01
  It was like, hey.
• 3:01
  This stuff just moves slowly because it's regulated and because the big players can move
• 3:06
  slowly, that there were more guardrails on what you could pay, how much you need to own, and
• 3:11
  the scale of outcomes.
• 3:12
  And I think AI has changed the math for those folks too.
• 3:15
  Maybe not as much on the realized exit side like we've seen on SaaS, but but I think on
• 3:19
  people's perception.
• 3:20
  I think this is the question in venture, and I read through it, and I was like, the place
• 3:24
  where I've landed on all this is if the outcomes are really gonna be bigger, and it
• 3:28
  appears that they will be at the extremes, if you find a truly great company, it's probably
• 3:34
  worth more than you think.
• 3:35
  This is the lesson I think VCs always relearn.
• 3:38
  We relearned it with Google.
• 3:39
  We relearned it with Facebook.
• 3:40
  We I think we've relearned it with NVIDIA.
• 3:42
  The big companies end up being much bigger than you think because usually there's some
• 3:46
  combination of tailwind and timing that pushes them to a place that was, like, hard to imagine
• 3:50
  before.
• 3:51
  And I think so long as that's the case, there will be companies that are worth paying for,
• 3:55
  but I don't think that means that on average, price and ownership don't matter.
• 3:58
  You know, we only have one SpaceX.
• 4:00
  We have one Anthropic and one OpenAI.
• 4:02
  I just don't know that you should just throw all of the playbook out of the window.
• 4:07
  And I think what the Scrub Capital folks said in the article makes sense to me, which is like
• 4:11
  for every deal, and what Hunter said too, for every deal you have to look at the combination
• 4:14
  of entry price, market size, team, ambition, all of these things and figure out, do I think
• 4:19
  this one's gonna pencil for me?
• 4:21
  Yes or no?
• 4:21
  Yeah.
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  And I think the idea of never stretching seems crazy, but the idea of saying price and
• 4:26
  ownership don't matter at all because everything will be bigger also doesn't make any
• 4:30
  sense to me.
• 4:30
  People believe that they're either disciplined or convicted, but how can you actually prove
• 4:35
  out if that's the camp that you're actually in versus what you're telling yourself day to day?
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  I think it's the, like, this time it's different versus it's always the same crowd.
• 4:44
  I think that this time it's different crowd is being disciplined is silly, not because
• 4:48
  discipline is a poor trait, but discipline is leading you to make the wrong decisions about
• 4:53
  what to invest in.
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  Because you have, you know, I've been saying this a lot internally, you haven't updated your
• 4:58
  firmware and that entry prices are different, exit prices are different.
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  So the the prices you can pay and the structure you can pursue needs to be updated with the
• 5:07
  scale of outcome.
• 5:08
  And if you're still focused we'll just make this.
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  If you're still focused on 10 posts to some magic number, that ship has sailed.
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  And you're running an old model that doesn't apply.
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  The flip side is everybody says the same thing at the top or in a bull market.
• 5:20
  Period of time, it's different.
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  This is why multiples can be this high.
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  This is why you can pay this revenue.
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  This is what everything said in 2021.
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  SaaS.
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  It's the golden era of SaaS.
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  Like, sure, you can pay a 100 x forward revenue.
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  What's the problem with that?
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  These companies are growing so fast.
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  The market's so large.
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  And it turned out at some point, like, gravity set back in.
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  I think the unspoken thing here is I think the outcomes I've learned in venture are very
• 5:42
  different for these two strategies.
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  I'm not convinced that the rewards for discipline from in terms of what LPs reward are
• 5:48
  as great as they are in the public markets.
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  The public markets, if you're disciplined and you hold and things come your way or you can go
• 5:54
  short, you can make money.
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  Think I in venture, if you're too disciplined, you follow your model and nobody cares.
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  And I think the other thing I've learned is if you are convicted, it is this weird asymmetry.
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  If you're convicted and right, you make a lot of money and then it kinda doesn't matter at,
• 6:08
  like, an individual level whether you're ever right again.
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  If you're convicted and you're wrong, but everybody else is wrong, you kinda get to hide
• 6:14
  in the herd.
• 6:15
  Yeah.
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  So there is the part of me that says, like, increasingly, feels to me venture is really a
• 6:19
  momentum business in a way that maybe it wasn't before.
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  It's a momentum business.
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  And being in the hot companies and being on trend has all of these other ripple effects
• 6:27
  around fundraising, brand, notoriety, visibility, and then maybe outweigh the
• 6:32
  benefits of being it's kind of like if you're trying to be a value investor in a bull market,
• 6:35
  it's pretty tough.
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  Kind of on your own island for a long time until the tide comes in.
• 6:39
  And I think in publics, being on that island can be more attractive than it is in privates.
• 6:43
  But how does this feel different from cycles before, Charles, of being on your own island
• 6:48
  and being able to have conviction that it'll see it through?
• 6:51
  I think everyone always says this time it's different.
• 6:54
  And sometimes it is.
• 6:56
  The Internet was different.
• 6:57
  It just wasn't different right away.
• 6:59
  Mobile was different.
• 7:00
  It wasn't different right away.
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  And look, there are also in these bubbles, there are companies that get acquired or who
• 7:06
  are perceived as being valuable.
• 7:08
  If you were in those companies and can get in and out of them, it's great.
• 7:11
  If you were a website if you were in broadcast.com in the first bubble, that's not a
• 7:15
  company of consequence today.
• 7:17
  But you did quite well in that one.
• 7:18
  I can name a bunch of other companies from the mobile era that if you were in them, they were
• 7:22
  consequential.
• 7:23
  And I'm sure we'll look back and say, wow.
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  There were some companies in the AI era that we thought were gonna be very consequential early
• 7:28
  that turned out to just not matter.
• 7:30
  And that's that's part of, I think, the convicted person's personality too tends to be
• 7:35
  slightly more gambling oriented.
• 7:37
  There's a willingness to say, like, I'm gonna bet on this trend before we figure out the
• 7:40
  outcomes and bet that if I'm in the companies that matter, that some of these things are
• 7:44
  gonna work out.
• 7:45
  And then just to bring it back to the health care of it all too for this specific article.
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  I think that's where feel personally for my friends who said I'm more of the growth side of
• 7:53
  healthcare investing.
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  The risks of not being part of the biggest plays within healthcare right now, the biggest
• 7:59
  companies, are so massive because, and Hallie it throughout the article and in the piece that
• 8:04
  you wrote, the sales cycles are so slow.
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  There are so few decision makers at each of the big customers that if you miss out on the one
• 8:12
  that's big, I don't know when there will be another one.
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  And especially in this AI era, it just feels so consequential.
• 8:17
  I think the other thing, just in hearing you say that, I think this is different math for
• 8:21
  being a generalist than a specialist.
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  I think if you're a specialist fund, you have to be in the companies in your category that
• 8:26
  matter.
• 8:27
  And your options are, like, pay a little bit early or pay a lot later.
• 8:30
  And so I've always told you if you're a specialist fund, the math is different because
• 8:34
  I don't think you can afford to be completely disciplined as a specialist fund because part
• 8:39
  of what your LPs are paying you for is category access.
• 8:41
  It'd be like if you were an AI fund and you're like, I'm not in any of the model providers.
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  I'm not in any of the big inference companies, and I'm not in any of the big high flying
• 8:49
  application companies.
• 8:50
  None of those things might work, but not being in them would look really weird if ILOs.
• 8:54
  Like, hey.
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  I put money into an AI fund that's in none of those companies.
• 8:57
  Yes.
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  Well, our second piece this week is a recent newsletter that Sam Lesson from Slow Ventures
• 9:01
  sends out, which made the provocative argument that the SpaceX IPO is proof that the DCF model
• 9:07
  is no longer the only globally scalable story of value.
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  His thesis is that the Internet has made it possible for alternative belief systems around
• 9:14
  volume.
• 9:15
  So think crypto.
• 9:16
  You can think memes docs to scale to truly trillion dollar size in ways that simply
• 9:21
  weren't possible for.
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  SpaceX is obviously the clearest version yet because it's backed by a genuinely futuristic
• 9:28
  narrative complete with the $23,000,000,000,000 TAM in their s one that Sam describes as,
• 9:33
  quote, so ridiculous.
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  It was brilliant marketing, and we obviously saw that come true almost two weeks ago.
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  The deeper point isn't really about SpaceX at all though in his piece.
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  It's that we may be entering a capitalist multiverse where investors are no longer all
• 9:48
  playing the same game, holding assets not just for cash flow, but for identity, for story,
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  optionality, and the chance to participate in what Sam calls the swerve to infinity.
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  He's careful to hedge that history suggests this probably ends badly, but argues that post
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  Internet world is structurally different enough that monoline capitalism with one universally
• 10:10
  accepted story of value may actually be over.
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  Though Sam's argument is genuinely that we can no longer assume all investors are optimizing
• 10:18
  for the same thing.
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  So from where you sit, Charles, is that actually a new argument, or have this different
• 10:22
  investor bases all been playing different games, and now we're just creating a name for
• 10:26
  it?
• 10:27
  I think it's a description.
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  I think Sam left out one really important thing, which is entertainment.
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  I think some of this is entertainment.
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  And I was very perplexed by the stonks, GameStop, Memestock stuff Yeah.
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  Until I started meeting people who were part of that community.
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  And it's a lot of the things Sam mentioned.
• 10:46
  It's identity.
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  It's striking back at the man.
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  Yeah.
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  It's entertainment.
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  It's fun.
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  They were like, this is fun.
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  Like, this is fun.
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  There's some money to be made.
• 10:55
  There's a little bit of nihilism.
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  They're like, I don't know how else I'm gonna make money.
• 10:58
  Probably not.
• 10:59
  Like, I'm not gonna be able buy a house with my nine to five.
• 11:01
  And I do think I read a lot of pieces which are like, SpaceX isn't worth this because I ran
• 11:06
  this model and look at price to earnings and even and I'm like, but no one's valuing the
• 11:10
  company based on that.
• 11:11
  They're valuing it because it's Elon and it's space and it's cool.
• 11:15
  And there's a lot of money propping it up.
• 11:17
  I think there's all these other things too.
• 11:19
  Financial markets have changed so much with high frequency trading, with index funds, with
• 11:23
  all of these things.
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  The idea that stocks move because individual stock pickers are doing DCF analysis.
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  I think that world has been over
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  Yeah.
• 11:30
  For a while.
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  And I think I was expecting a unified paradigm to replace it.
• 11:34
  And I think instead what you end up with are these fractured this multiverse like you
• 11:38
  described.
• 11:38
  Some people are still looking for stocks where the math pencils out.
• 11:42
  Some people are just, oh, there's momentum.
• 11:44
  There's momentum around Nvidia, but what's the next choke point in the AI story?
• 11:48
  Oh, it's it's memory.
• 11:50
  Quick.
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  Let's go buy Micron.
• 11:51
  Other people are like, wouldn't it be funny if we took a shoe company and made it an AI
• 11:54
  company?
• 11:55
  Cool.
• 11:55
  Let's rebrand Allbirds as an it.
• 11:57
  Yeah.
• 11:58
  None of this stuff is real and serious except that it's money.
• 12:01
  And I think if you're gonna participate in markets, you have to understand the motivations
• 12:05
  and behaviors of other market participants.
• 12:07
  It's too easy to just say these people are being irrational.
• 12:10
  Like, but they're participating.
• 12:11
  And I think the same is true in venture.
• 12:13
  I've been guilty of this sometimes.
• 12:14
  Like, this price for this company doesn't make any sense.
• 12:16
  Well, someone else paid it.
• 12:17
  I've read something that said, like, you know, conditional on getting to $10,000,000,000, the
• 12:21
  probability of getting to a $100,000,000,000 is quite high.
• 12:23
  I'm like, that feels true.
• 12:25
  If you get to $10,000,000,000, however you get there, there's a lot of late stage money that
• 12:29
  says, well, let me find the stuff that feels derisked.
• 12:31
  But the stuff that feels de risked might not actually be as de risked as we think it is.
• 12:36
  Right.
• 12:36
  Those companies might still have a lot of money, a lot of work to do, but we live in a
• 12:39
  world where so much money is trying to find the thing that's gonna go from if you said, what
• 12:44
  game would you rather be in?
• 12:45
  We'd rather be in the 0 to $100,000,000 game, the $100,000,000 to a billion dollar game, or
• 12:51
  the billion to a 100 I think a lot of people are like, you know, I'd rather find the assets
• 12:54
  that already have gotten some momentum and hope that instead of going from one to 10, have
• 12:59
  somebody who's gonna go from one to You get the notoriety, the name brand value, the
• 13:03
  visibility, and you can still make the same kind of multiple.
• 13:07
  It was hard not to think about.
• 13:08
  They're obviously quite different in the space that they are, but when WeWork filed the s one
• 13:12
  describing this whole universe that will exist because of the company, and that's what you're
• 13:16
  investing in.
• 13:17
  You're not investing in this company.
• 13:18
  It's a tech company.
• 13:19
  Yeah.
• 13:19
  It's gonna be a school.
• 13:20
  It's gonna be a village.
• 13:21
  It's gonna be everything.
• 13:22
  The public rejected that notion, obviously, entirely before it even hit the scenes.
• 13:27
  This one, because of the space, I think Elon has far more ground than Adam did.
• 13:31
  This one was very embraced.
• 13:33
  And people even the folks who participated in the public markets, when it went out, I think
• 13:37
  they all agreed that I'm not participating because of what the company is today.
• 13:40
  But if Starlink takes off, this is what I'll be part of.
• 13:43
  If we actually get commercial travel into space, this is what I get to be part of.
• 13:47
  That distinction is is interesting that people have widely accepted and wanna be a part of
• 13:51
  that versus WeWork when they read that being like, oh, I actually do not wanna be part of
• 13:56
  that.
• 13:57
  I think some people are buying SpaceX because they believe in the business.
• 13:59
  I think some people are treating it like a vote for a version of the future that they wanna
• 14:03
  see.
• 14:04
  I think there's some people who are just like, this is a good trade.
• 14:06
  Other people are gonna be in it.
• 14:08
  And, you know, I look at it.
• 14:09
  I'm like, Starlink is an interesting business.
• 14:11
  SpaceX is an interesting business, and then you have the whole x AI.
• 14:14
  But I think Elon is very good at attracting attention to his companies.
• 14:17
  I read all these, like, Tesla bear cases.
• 14:19
  I'm like, based on the fundamentals, you all are completely correct.
• 14:22
  But the support for that stock has nothing to do with the fundamentals and has everything to
• 14:26
  do with communities on the Internet who are not reading your research, but are making different
• 14:30
  decisions.
• 14:30
  So you can write all the research you want about how the the fundamentals don't work.
• 14:34
  Fundamentals only matter when there's a corrective force.
• 14:36
  And if there's no corrective force, things can remain expensive, ludicrous, crazy for a very
• 14:40
  long time.
• 14:41
  And that's what I think I always thought of the public markets as that would be the corrective
• 14:44
  force.
• 14:44
  Yeah.
• 14:44
  But now we're just seeing a completely new thought enter in.
• 14:47
  And you're right.
• 14:47
  It might have existed always previously, but this feels it just felt palpably
• 14:52
  Yeah.
• 14:52
  Palpably different.
• 14:53
  I think ventures, in many ways, that was my takeaway from 2021.
• 14:57
  As you would have thought, a lot of people would have gotten fired for the excesses of
• 15:00
  2021.
• 15:01
  It didn't really happen.
• 15:02
  And I'm like, well, maybe there isn't much of a corrective force in our business in the short
• 15:06
  term on the part of LPs.
• 15:07
  Because, you know, they're thinking about this manager had one bad year, had one bad fund.
• 15:12
  Do I wanna fire this person and jeopardize what could be great returns in the future and great
• 15:17
  returns that we've gotten in the past over a lapse in judgment that was done by many of
• 15:21
  their peers?
• 15:22
  I think my view is the collective LP answer is I do not want to.
• 15:25
  Well, our last piece is from Sarah Guo on an essay in her subsect titled The Untrainable,
• 15:30
  and it's a more grounded take on AI and venture defensibility.
• 15:32
  The central argument of it is that anything you can measure, you can train against, which means
• 15:37
  anything measurable is already on its way to becoming a commodity.
• 15:41
  The real mode, what Sarah calls is the untrainable corner, is work where correctness
• 15:46
  exists only in private.
• 15:48
  So it's inside a specific firm's data, behind a specific firm's liability, inside the habits
• 15:53
  and the trust that a specific user base has built over years.
• 15:56
  She walks through why this matters practically.
• 15:59
  A majority of American doctors know open open evidence, which is one of her investments every
• 16:03
  day, and no amount of compute buys that kind of adoption.
• 16:06
  You can't gradient descent your way into a physician's daily workflow.
• 16:10
  Her framework boils down to a two by two of how saturated a task is versus whether its
• 16:14
  correctness is public or private.
• 16:16
  And the prize is the unsaturated work with private ground truth, the stuff that can't be
• 16:21
  scored from the outside.
• 16:22
  The piece closes with a useful challenge for builders and investors alike.
• 16:25
  The absorption frontier keeps rising.
• 16:27
  You can't find a defensible spot in rest.
• 16:30
  You absolutely have to keep stepping towards something that hasn't been scored yet.
• 16:34
  Her closing argument on the fact that you can't find a defensible spot to rest and you have to
• 16:39
  continuously move forward makes sense.
• 16:41
  But her whole moat framework is built on trust and habit and things that, by definition, take
• 16:46
  years to earn and and can't be rushed.
• 16:48
  So how can founder actually hold both of those truths at the same time?
• 16:52
  I like this piece a lot, and it made me think about I've been using agent loops to build some
• 16:59
  things in Cloud Code.
• 17:00
  And I was like, oh, it's very similar.
• 17:02
  I know what write looks like.
• 17:03
  It's actually pretty cool to be like, this is the answer.
• 17:05
  This is the canonical answer for these tasks, and I've built some things that are much better
• 17:09
  than the last version of things I've built.
• 17:11
  But it's only because I know what right looks like.
• 17:13
  And I read this and I was like, I think this is part of why the AI ROI conversation is so hard,
• 17:19
  is because of many of the things that people are building internally that work, it's hard to
• 17:23
  observe from the outside that those things are working.
• 17:26
  And it's also hard to know, like, well, what's what's that thing worth?
• 17:29
  And I think what you said is true.
• 17:31
  Spending an expensive token and model run on a question with a trivial answer is a dumb thing
• 17:36
  to do.
• 17:36
  You should use the cheapest, simplest model.
• 17:38
  And I think this is the evolution that we're going through right now after the lunacy that
• 17:42
  was token maxing.
• 17:43
  Yeah.
• 17:43
  People are like, hey.
• 17:44
  If we're gonna get value out of this stuff, it's gotta work on hard problems, and it's
• 17:48
  gotta be cost effective.
• 17:50
  And I think also about the Kirkland and Elle's piece we talked about before, which is like,
• 17:54
  were like, we don't get paid for average.
• 17:56
  We get paid for high end work.
• 17:57
  And I think there are a lot of firms who are just like, well, the answer for us is we've
• 18:02
  gotta find a way to do the quality of work that we have signed up to do for our clients,
• 18:07
  whether that be our physician or an attorney or whatever, assisted by AI, and that's hard.
• 18:11
  It's hard to do you know, most models can't tell you, is this contract good enough to ship
• 18:15
  to a client?
• 18:16
  Tell you maybe, oh, it's error free.
• 18:17
  It addresses all the issues.
• 18:18
  Doesn't mean it's good enough to ship.
• 18:20
  In the same way, Cloud Design can build you a presentation.
• 18:23
  It builds a lot for me.
• 18:24
  Doesn't mean I would ship the output directly.
• 18:26
  And so I read the piece, and I was just like, we are getting into a more nuanced
• 18:30
  understanding of where the opportunities are in AI.
• 18:33
  And it changes, and this is the thing that I find interesting about this current moment, is
• 18:37
  in public markets, if you decided that Micron is overdone and memory is no longer the big
• 18:42
  story, you could just sell it and go rebuy some NVIDIA or you could go buy Google because you
• 18:46
  think Gemma.
• 18:47
  In private markets, you can't do that.
• 18:49
  Yeah.
• 18:49
  If you're stuck holding that position, And that company better figure out how to navigate and
• 18:54
  migrate, or else you're gonna get crushed.
• 18:57
  And the stakes are high because of the dollars that are going into these companies.
• 19:00
  I think it was a good framing to think about it.
• 19:02
  Also, untrainable stuff is, I think, the stuff that companies are most afraid of handing over
• 19:06
  to the models too.
• 19:07
  They're like, hey.
• 19:07
  The only way for me to work on the untrainable is probably private inference.
• 19:11
  Models that I train and control where I can observe and manage the outputs.
• 19:14
  And I think this notion that, you know, ChatGPT is still the consumer app of choice.
• 19:19
  Claude does a pretty good job, so does Gemini.
• 19:21
  But in in the same way that Claude is that how do I know that my work would be any different
• 19:25
  if I just said I'm not using Claude anymore, I'm using Gemini for everything?
• 19:28
  I don't know that.
• 19:28
  I'm not gonna find out.
• 19:30
  For all I know, if I swapped Gemini in for Claude, maybe my life would be exactly the
• 19:33
  same, but that's not that's not what I'm doing.
• 19:35
  And I think her piece calls into this focus of it kinda does take to to make this all work.
• 19:40
  It does take the company itself building and shipping product, but then it also takes the
• 19:43
  customer where they are on the range.
• 19:45
  So to your point, I, as the large enterprise, need to be willing to let go or figure out a
• 19:51
  compliance and security protocol that works in order to take hold of this innovation.
• 19:56
  And if I don't do that, then I'll never basically unlock the growth.
• 19:59
  And she had a good quote from, I think, Noam Brown Yeah.
• 20:01
  Who sent the only way to surely evaluate an agent over a one year horizon may actually be
• 20:07
  to just run it for a whole year.
• 20:10
  And I think that's where enterprise customers have yet to kind of see that through because
• 20:15
  they
• 20:15
  are Yeah.
• 20:15
  Trying so many different pilots and different attempts at this simultaneously, and maybe
• 20:19
  cutting pilots three months in if they're not seeing the returns on it.
• 20:22
  I read this and I was like, this explains why I think my initial skepticism of the AI timing,
• 20:27
  not the order of magnitude, was really that technology can move faster than people.
• 20:31
  I remember in the early days of the Internet, my friend was like, we have this website.
• 20:34
  I'm like, what happens?
• 20:35
  Like, oh, people fill in this form.
• 20:36
  It's so cool.
• 20:37
  What do you do with the form?
• 20:38
  Oh, we print the form out.
• 20:39
  We're gonna be like, well, people fill out the form.
• 20:40
  It's cool.
• 20:41
  Have an Internet form.
• 20:42
  But then, like, we print the form out.
• 20:43
  Then everything after that form is the same old process.
• 20:46
  And I'm like, well, you're not gonna get very much gain if all you're doing is digitizing the
• 20:51
  very first step.
• 20:52
  But and I think that's sort of what we're working through with AI, and this is why I
• 20:55
  suspect the low ROI numbers are probably accurate.
• 20:59
  And it's not because the technology is not good, it's because the total workforce process
• 21:03
  transformation that has to happen to get value from it.
• 21:06
  Most people are unwilling or unable to do all of that today.
• 21:09
  Yep.
• 21:09
  And as they they look, in customer success and customer service, our friends are like, oh,
• 21:12
  we've moved almost all of our first line stuff to chat.
• 21:17
  The savings are real.
• 21:18
  They're like, we're not sure if the satisfaction is the same, but the cost savings
• 21:21
  are real.
• 21:23
  And I think as latency and voice agents gets better there are all these things I'm just
• 21:26
  like, if you are willing to make the process redesign, that will increase the odds that you
• 21:31
  will get the value.
• 21:32
  But that's transformational work, and you can't do that.
• 21:34
  That doesn't look like this.
• 21:36
  It doesn't look like the revenue curves of these companies.
• 21:38
  That takes time.
• 21:39
  It takes people.
• 21:39
  We're still early on.
• 21:40
  I will say, like, I met the first person in a conversation who bragged about how much tokens
• 21:45
  their company gives them for usage.
• 21:47
  And I like, ugh.
• 21:48
  We're still we've still got some time to figure this all out.
• 21:51
  I know.
• 21:51
  I know.
• 21:52
  Everyone has to.
• 21:53
  We're all out of time today.
• 21:54
  Thank you so much, Charles, for stopping in.
• 21:56
  Thank you to our listeners for hopping in as well.
• 21:58
  Please like and subscribe, and we will talk with you all in a couple weeks.
• 22:00
  We're taking off for fourth of July, but we will see you soon.
• 22:02
  Thank you.
• 22:03
  Bye.