Latest / The Learning Corner by Precursor / Episode #78: Owning Your AI Agents, When Your VC Leaves, Are You Actually AI-Native?

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Episode #78: Owning Your AI Agents, When Your VC Leaves, Are You Actually AI-Native? · The Learning Corner by Precursor

• 0:00
  And I think this notion of AI adoption having levels is true, but I think the tricky thing is
• 0:06
  it seems to change every two quarters.
• 0:08
  So I tend to think of what is the top 25% of companies doing versus what's the average
• 0:12
  company doing.
• 0:13
  A few quarters ago, having a GitHub repository with a bunch of shared skills on a Teams
• 0:18
  account maybe would have put you in the top.
• 0:20
  And I think every quarter, it feels like the things that were top tier advanced become
• 0:24
  average.
• 0:25
  It's the week of May 4.
• 0:27
  Welcome to the Learning Corner, a Precursor Ventures podcast.
• 0:32
  Welcome to the Learning Corner by Precursor.
• 0:34
  I'm Mia Farnam, and I'm joined by RGP and managing partner Charles Hudson, where we will
• 0:38
  be talking through the articles and Goodreads that caught our team's attention over the past
• 0:42
  week.
• 0:43
  Our first piece this week is from Forbes written by Nirat Cohen titled, can you take
• 0:48
  your AI agents with you when you leave a job?
• 0:51
  It explores a question that's becoming one of the more interesting and unresolved tensions in
• 0:55
  the modern workplace.
• 0:56
  Course, previously, the deal was quite simple.
• 0:58
  Companies provided the tools, the data, and the infrastructure.
• 1:01
  And when you left, all of it stayed behind.
• 1:04
  What traveled with you was what lived in your head.
• 1:07
  That deal is potentially changing with AI.
• 1:10
  Knowledge workers are now building what Nirik calls a personal capability stack, combination
• 1:14
  of AI agents and systems that learn how you think, how you structure arguments, how you
• 1:19
  weigh trade offs, and how you communicate decisions.
• 1:21
  And over time, these systems stop being productivity tools and start becoming something
• 1:26
  closer to a digital extension of your professional identity.
• 1:29
  The piece raises the key question, if your judgment and decision making patterns are
• 1:33
  encoded into an AI system you built and refined over time, does that system belong to you or to
• 1:39
  your employer?
• 1:41
  We talked about this yesterday as a team, how skills are something that have existed since
• 1:46
  the workplace has been in existence, and now skills should include Claude's skills, insert
• 1:53
  whatever foundational LM skills, agent architecture, etcetera.
• 1:56
  The question remains, are you allowed to bring those things with you that you've built into
• 2:00
  your next stop career wise?
• 2:02
  So Charles, I wanted to pause for your thoughts here.
• 2:05
  I think this is one of those new and old questions at the same time.
• 2:08
  I think there's always been like, hey, when you leave your job, if there's a cool slide format
• 2:12
  that you built, can you take that with you?
• 2:14
  That feels kind of low stakes.
• 2:15
  I think it's fascinating for two reasons.
• 2:18
  One, because of the shelf life of a lot of this stuff, it's very possible that if you leave, by
• 2:23
  the time you'd wanna take it with you, the thing you built may no longer be in production.
• 2:28
  And when I read the article, my immediate thought was almost opposite.
• 2:30
  It's like, what are companies gonna do with all of these agents or things that individuals have
• 2:35
  built?
• 2:36
  When the individual leaves, like, who's gonna who's gonna support that vibe coded thing
• 2:40
  that's become and ironically, I'm like, well, this is part of the reason that you buy
• 2:43
  software from other people, is that their responsibility is to keep the thing up and
• 2:47
  running and you're not dependent on a single person in your org.
• 2:50
  I think there's also some more structural challenges here, which is if I wrote a skill
• 2:55
  that really works, the fact that, you know, some people are doing their work using
• 3:00
  corporate provided team account or enterprise versions of AI, but some people are also using
• 3:05
  personal versions of ChatGPT or Clock.
• 3:08
  And, yes, of course, no one should be using their personal thing to do work account, but
• 3:12
  let's be honest, people are.
• 3:13
  The question then becomes like, what happens if I built it in my personal account?
• 3:18
  Or if I built something on my free time that makes me more effective at work?
• 3:22
  Does that tool even work without the context of the environment that I'm in?
• 3:26
  And conversely, if I wrote a skill that's like broadly applicable Yeah.
• 3:29
  Sure, maybe I leave the skill m d file at the office, but I still have all that knowledge in
• 3:34
  my brain.
• 3:35
  And so I think this is fascinating because it's not clear to me even that things that were
• 3:40
  built a year ago are still as useful as one would think.
• 3:43
  So I don't even be I don't even know how to begin to think about this question.
• 3:47
  It's like Yeah.
• 3:48
  So rich.
• 3:49
  The irony of it when I was reading it is that these large companies have placed the task onto
• 3:56
  the employee of getting smart on AI and building, and they might be left with they, as
• 4:01
  in the employer, might be left with, like, a lot more issues than they anticipated if people
• 4:06
  actually get really smart and up to speed.
• 4:08
  Because if they do leave or if there's a layoff, those systems and tools that they've
• 4:13
  asked them to build that maybe made the company more efficient don't just run autonomously in
• 4:17
  the world that we live in today.
• 4:18
  Like, we build stuff all the time internally here.
• 4:21
  I was rebuilding a tool to help us look at portfolio health, and I was working with
• 4:24
  Aliyah, one of our teammates, on building that.
• 4:26
  I built it on my own on our team account, but you can't, like, share co work projects in the,
• 4:31
  like, way that you really need to, especially if they're complex.
• 4:33
  And then I was like, alright.
• 4:34
  I'll extract out the text of this and then be able and you can be able to run it as well.
• 4:38
  She ran it, and she had all these questions.
• 4:40
  And I'm like, oh, yeah.
• 4:41
  I have this, like, system.
• 4:42
  I know that those questions weren't gonna happen, but you didn't know that because you
• 4:45
  didn't build it.
• 4:46
  I have this framework of like, no, no.
• 4:47
  It's not making mistakes.
• 4:48
  This is just like the step process.
• 4:50
  That back and forth took four or five days just to understand what gaps there were between
• 4:54
  people on the same team, and we have a small team relatively.
• 4:57
  Yeah.
• 4:58
  If you work in a massive organization and you're handing off multiple agents for multiple
• 5:02
  different projects, I don't really know how you're able to handle that transition.
• 5:06
  I think the thing that I find hilarious, I rediscover this lesson every week, is everybody
• 5:12
  whenever I tell people these problems, they're like, you know these are solved problems in
• 5:15
  software development.
• 5:16
  Right?
• 5:16
  Mhmm.
• 5:17
  Software developers have encountered these problems before, and this is why we have
• 5:21
  comments in code, and this is why you have documentation, and this is why you have all all
• 5:24
  of these things.
• 5:25
  And I'm like, yes, all of these non developers Yeah.
• 5:27
  Are learning all of the basics of software development, whether that's good documentation,
• 5:32
  whether that's version control, whether that's collaboration, like we're all learning all the
• 5:36
  things that professional software developers have solved.
• 5:39
  Although we're learning them in a different context because many more people are building
• 5:42
  and the things they're building are in some cases more siloed, but also more autonomous.
• 5:46
  So I do think at some point companies are gonna figure out better systems for building this
• 5:50
  stuff, better systems for documentation.
• 5:53
  Because I think most companies deep down abhor being reliant or dependent on a single
• 5:57
  individual.
• 5:58
  I just think people haven't figured out how do we both push the work of building this stuff
• 6:01
  down to the individual, but also make sure that we have a way to recover and operate if that
• 6:06
  individual leads.
• 6:06
  Where do you think legal arguments or any sort of regulation is gonna fall on this if there
• 6:13
  starts to being conversations in the background, which I assume there are happening
• 6:16
  right now?
• 6:16
  Well, mean, I think in some instances, if you have to build your agent using corporate
• 6:21
  infrastructure and it lives there, it's kind of I think to me it's obvious.
• 6:25
  But I keep asking myself, like, well, what does it mean to take an agent with you if the
• 6:30
  agent's power was the data to which it had access?
• 6:33
  I do think that the notion that you can take agent outputs that are like corporate data, I
• 6:37
  have a feeling companies are gonna win that argument that, hey, you can't use an agent to
• 6:41
  walk out the door.
• 6:42
  But a framework for doing an analytical project on top of a database, I don't know how you stop
• 6:47
  somebody from doing that.
• 6:48
  They're gonna have the knowledge of how to do it.
• 6:50
  Whether they copy the exact computer generated Python code to do it is another issue
• 6:55
  altogether.
• 6:55
  So I suspect this is gonna be very murky because it's not like, oh, I, like, stuck a USB
• 6:59
  drive in my computer and sucked down a bunch of customer records.
• 7:03
  We've we've kind of decided you're not allowed to do that.
• 7:05
  But hey, an architecture that cleverly helps me, you know, do a cohort analysis on customer
• 7:10
  data in a given system with a killer prompt, I don't know how you stop somebody from even if
• 7:14
  you don't let them take the text out the door, the knowledge is gonna walk out the door with
• 7:17
  them when they leave.
• 7:18
  That's protected.
• 7:19
  Yeah.
• 7:19
  And I can I can imagine there being some sort of infrastructure to protect this when you work
• 7:23
  at, a sub 100 employee organization?
• 7:26
  I do wonder how does this work in scale?
• 7:28
  How do you run after all these people if they have, say, five to 10 agents themselves that
• 7:32
  they've built up, and you work at like a 20 plus thousand organization?
• 7:35
  I don't know how you watch that in in today's world again.
• 7:38
  I think the answer for most companies will be eventually will be centralization.
• 7:41
  And that individuals will do less of this development.
• 7:44
  Right now, it's like a thousand flowers bloom, push it out to the edge.
• 7:47
  But at some point, think people will say, hey, this customer pipeline agent is a critical
• 7:51
  thing.
• 7:52
  We can't have the one person in sales who's AI build build this.
• 7:56
  We need to have a centralized team that builds and manages this agent.
• 7:59
  And I think we'll get there eventually.
• 8:01
  We're just far from it feels like far from them.
• 8:03
  One last comment back to your earlier statement about this is why people have worked with b to
• 8:08
  b software companies for so long.
• 8:10
  When I was in consulting, you would go and arrive at a client and you would take a look at
• 8:15
  their entire tech stack.
• 8:16
  When you saw that there were homegrown tools in the tech stack when you were doing a review,
• 8:22
  you would start to freak out because They were.
• 8:25
  You were being like, oh, no.
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  Who's responsible for this?
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  How did they build this?
• 8:29
  Mhmm.
• 8:29
  Like, how janky is it?
• 8:31
  Sometimes it's really complex, but that's even scarier.
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  How do we get rid of it?
• 8:34
  This is almost like that, but thousands of times over if each person has built their own
• 8:40
  homegrown tool.
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  I I literally remember we would have our own work stream assigned to homegrown tools running
• 8:46
  around our client, finding out the people who built them, and seeing if they still worked
• 8:50
  here.
• 8:51
  And then in most cases, like, well, we can't touch it.
• 8:53
  You can't.
• 8:54
  Because it it works, and nobody knows how to nobody knows how it works.
• 8:57
  No one
• 8:57
  And leadership doesn't want you to touch it either.
• 8:59
  They're like, just don't touch that.
• 9:00
  And you're like, okay.
• 9:01
  Well, our next piece is by Iwana Altnew, published on her Substack, Motive Notes titled,
• 9:07
  when your VC leaves, you are fundraising again.
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  It opens with a founder texting Iwana the morning their partner posted on x about leaving
• 9:14
  the firm, asking how to manage the risk.
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  The core argument is that when your VC leaves, your company gets quietly reevaluated inside
• 9:21
  the firm, not in a formal meeting or a memo, but in where attention flows, who's speaking up
• 9:26
  for you in partner discussions, and who uses their political capital on your behalf.
• 9:30
  All of that institutional memory, the reasoning behind early bets, the contacts that made your
• 9:35
  thesis legible before it was obvious walks out the door with your partner.
• 9:38
  Iwana walks through the two lenses founders need to hold simultaneously.
• 9:42
  The founder lens, which says your job as a CEO doesn't change, and the structural lens, which
• 9:47
  says the firm's internal ownership just reset regardless of how warm the emails stay.
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  The piece is full of really specific advice from asking directly who owns you internally
• 9:58
  now to recognizing that go raise from the market and we'll take our pro rata is not
• 10:03
  actually formal backing.
• 10:04
  It's a firm waiting for someone else to take the risk first.
• 10:07
  Mhmm.
• 10:07
  Obviously, our friend Hunter wrote a really good piece about this a few years ago.
• 10:11
  How real do you think this phenomenon is?
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  How much has it grown in occurrence?
• 10:17
  And what should the priorities be of a founder when they encounter this since it's going to
• 10:22
  happen more and more with increased movement across venture from firm to firm I've seen?
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  Ironically, the firm to firm stuff is less disruptive than the firm to industry stuff.
• 10:32
  Because the firm to firm, the person is still a VC.
• 10:35
  They can't help you in the same way, but they're still in the mix and in the flow.
• 10:38
  When Brussels and Son was in the industry, they're just done with venture for the part.
• 10:41
  Whatever connection that person had to your company is very different.
• 10:45
  And I think we're seeing I don't know about your LinkedIn feed.
• 10:47
  I, every day, I see someone I know.
• 10:49
  I see two flavors, junior partners leaving and going into TBD jobs that have not been
• 10:53
  announced, but I assume that they've already decided what they wanna do.
• 10:56
  I've seen more senior folks either leaving the business altogether or leaving to start their
• 11:00
  own firms.
• 11:01
  And so I think this is going to be every year I feel the half life of venture crews get shorter
• 11:05
  on a per firm basis.
• 11:06
  Seeing more and more instances of this, and I think a lot of founders I find are getting
• 11:11
  caught flat footed because the partners oftentimes don't tell them they're leaving
• 11:13
  until the very last minute.
• 11:15
  I think Iwana's advice is really good.
• 11:17
  It's very similar to what I tell people.
• 11:18
  Like you need to immediately figure out who's responsible for you.
• 11:21
  And if you don't think you have good sponsorship internally, you should ask for a
• 11:24
  better sponsor.
• 11:25
  I had one founder in our portfolio who was like, well, I really like this person and I
• 11:28
  want them to be my sponsor.
• 11:30
  I was like, well, person has no power in that firm.
• 11:32
  And the person who did this deal was a managing partner.
• 11:34
  So you're gonna go from a managing partner who could look out for you and make sure things
• 11:38
  happen for you to someone who's basically an operating partner who has a much looser was
• 11:42
  like, I don't think that's a very good strategic decision for you.
• 11:45
  You know, in a lot of cases, there's a moment when you've been abandoned as a founder where
• 11:49
  you can actually ask the firm for more.
• 11:52
  You can be like, hey, you guys, like this person left.
• 11:54
  I'm feeling kind of abandoned here.
• 11:56
  I want that person or I want this thing.
• 11:58
  And I think in a lot of firms do feel bad about doing this, but like the law at some point then
• 12:02
  it's just over.
• 12:03
  And I really do think it's hard because what I wanna highlight is the truth.
• 12:08
  It's it's really the advocacy and people's willingness to spend social capital on your
• 12:13
  behalf that goes away.
• 12:14
  And I've been on I've seen this from every side.
• 12:16
  When I was the founder, the person who led my seed round left.
• 12:19
  And the person who took over that person is like a very good person, but didn't have the
• 12:24
  same connection to the company.
• 12:25
  We've had people leave here at precursor where I've inherited companies where like I didn't
• 12:29
  have connection to the founders, and in many cases I've tried to get to know them.
• 12:32
  But in some cases, it's just not the same.
• 12:34
  And I've seen our portfolio companies go through this.
• 12:36
  I think it's really it's really hard.
• 12:38
  And all the rules I used to give them, make sure it's a senior person, ideally the founder
• 12:42
  of firm, even those rules don't apply anymore because people are leaving and leaving for all
• 12:47
  kinds of reasons.
• 12:48
  And what used to be like a safe profile of a sponsor doesn't feel safe to me anymore.
• 12:52
  Alana outlines different states for where founders could find themselves.
• 12:56
  And one of them is a truly abandoned one where there's no other person getting assigned.
• 13:01
  It just feels like people have have ghosted, which sounds crazy if you're outside of venture
• 13:06
  hearing that people kind of abandon from a board perspective, but I see it happen a lot.
• 13:10
  What do you think of her advice to seek help outside the cap table, especially if you're in
• 13:16
  the founder position where maybe the route is to start finding a soft landing for your
• 13:20
  company?
• 13:20
  Is it going to find other founders who've been through this situation and have gone down the m
• 13:25
  and a path?
• 13:26
  Is seeking out other investors that you've built relationships with who have have hopped
• 13:30
  around.
• 13:31
  What do you think of that?
• 13:32
  To me, there's like this progression where it's like partner shows up to the board meeting in
• 13:36
  person, then the partner only shows up on Zoom.
• 13:38
  Then the partner brings their associate, and the two of them are on the board meeting, or
• 13:42
  principal, excuse me.
• 13:43
  Then the partner comes every other board meeting, and all of a sudden that person's just
• 13:46
  not there.
• 13:47
  To me, that's a very common slow walk tour.
• 13:50
  It's a sign.
• 13:51
  And I think most companies are smart enough to realize that if you're getting a less senior
• 13:55
  resource, you're either helping to train that person, a.
• 13:58
  B, the firm thinks that person's ready for board work and you're still trying to train
• 14:02
  that person.
• 14:02
  Or c, the signal from the firm that like this isn't a high priority investment anymore.
• 14:06
  And I think as a founder, when you get that signal, you have to decide, well, what am I
• 14:09
  gonna do with this information?
• 14:10
  If I agree with the firm's assessment that this isn't going well, maybe I should be more
• 14:14
  actively trying to sell the company.
• 14:16
  If I don't agree with their assessment, it frees you from having to listen to them to some
• 14:21
  extent.
• 14:21
  You're now free to run the company as you see fit, which could include M and A, but which
• 14:24
  could also include a pivot, could include a lot of different things.
• 14:27
  But I do think if you don't have a great sponsor who's senior and who cares about your
• 14:32
  company, should assume that no one in the firm is paying attention to you.
• 14:35
  And unless you're a top, top performer, you're probably not gonna get any money or attention
• 14:39
  from that firm going forward.
• 14:40
  So your options are either turn your company into a top performer so that you can once again
• 14:44
  get their time and attention, or use your time elsewhere.
• 14:46
  I'm involved with the company, and where most of the existing investors are checked out, And
• 14:51
  it's sort of me, the founder, and one angel, and that's that person's support system.
• 14:55
  And we're working with this person because we care about them.
• 14:57
  I'm not sure that it's gonna have a huge financial outcome for for me or for them, but
• 15:01
  they're still working.
• 15:02
  Yeah.
• 15:02
  And I was like, they're working hard.
• 15:03
  We gave them their our money, and we should continue to give them some amount of our time
• 15:07
  too.
• 15:07
  It is just a constant reminder for founders to really think deeply about who you bring on your
• 15:11
  board and that it sticks with you round over round.
• 15:14
  I was catching up with a founder not within our portfolio, but one that I've known for a while,
• 15:18
  and she's going through like a really tumultuous time.
• 15:20
  And the board has kind of left her in the abandoned state where they're no longer
• 15:25
  interested they're not interested in re upping and providing more capital, but they're also
• 15:29
  not interested in supporting her pursue any acquisition paths.
• 15:33
  And I asked her if she was surprised by that, just knowing the folks around the table.
• 15:38
  And she said yes and no.
• 15:39
  She said no because, candidly, they hadn't been that helpful strategically for her in the past
• 15:44
  five years of the business.
• 15:45
  But, yes, she was surprised in that she was confused why they didn't seem more active to
• 15:51
  find routes to make back more money if that was the path.
• 15:55
  And I think that actually that that happens more times than you think.
• 16:00
  And not helpful at all.
• 16:02
  I also think there is a psychology in a lot of firms.
• 16:05
  So we've written that thing down to zero.
• 16:06
  Unless something changes, this is a zero.
• 16:09
  And unless you see something obvious you can change about the company, you're like, well
• 16:13
  this is a zero.
• 16:13
  It's a zero on the books already or it's a zero in my mind.
• 16:16
  But why do any work?
• 16:18
  And going from a zero to 10¢ on the dollar at most firms doesn't really change anything.
• 16:23
  So you're like, well really to change something for this to matter, I've gotta go from a zero
• 16:27
  to maybe 75¢ of a dollar for anybody to care.
• 16:31
  And boy, that feels hard when you're on zero.
• 16:32
  Our last piece this week is from Anne Yurico on X titled, everyone wants to be AI pilled.
• 16:39
  Most companies are still level one.
• 16:41
  And it outlines a framework to cut through the noise around what it actually means for a
• 16:44
  company to be AI native.
• 16:46
  The piece opens with the comparison between small startups where being AI native can be a
• 16:51
  founding team personality trait because the teams are strong and they're so close to the
• 16:55
  customer, and scaling companies where it absolutely has to be embedded into the DNA to
• 17:00
  be considered AI native.
• 17:01
  Anne draws an analogy to the levels of autonomy that defined the autonomous vehicle industry
• 17:06
  debate for many years.
• 17:07
  Cruise control was not autonomy.
• 17:09
  Lane keeping was also not autonomy.
• 17:12
  And for this instance today, 80% of our employees using AI Weekly is certainly not an
• 17:18
  AI native organization.
• 17:20
  And she maps out six levels from l zero where AI is essentially theater and nothing of
• 17:24
  consequence actually happens, all the way to l five, a virtually self driving organization
• 17:29
  where the system notices things, synthesizes across sources, and updates shared memory
• 17:33
  without a human initiating the process at all.
• 17:35
  Says that this doesn't really exist yet.
• 17:37
  Most companies today are operating in l one personal productivity where the best AI users
• 17:42
  workflows walk out the door with them, and the org chart hasn't changed at all.
• 17:45
  So kind of back to our first piece today.
• 17:47
  Charles, curious from your perspective Yeah.
• 17:49
  What percentage of companies that you talk to day to day?
• 17:52
  What level do you feel like they actually sit on, and why do you think they believe they
• 17:56
  probably sit on a higher level than they really are?
• 17:59
  And then maybe zooming out at the larger company level, what percent of companies are
• 18:04
  truly operating at a I would even say like l one or above.
• 18:07
  I think all startups always believe they're exceptional.
• 18:10
  So it's not surprising to me that everybody would rate their own AI adoption quite high.
• 18:14
  Also, nobody would wanna admit they're l zero or l one even if they are.
• 18:17
  To me, I read this and I'm like, we are so and I liked Anne's framework, but between token
• 18:23
  maxing and this, we are so desperate Yeah.
• 18:25
  To find a framework to figure out what matters.
• 18:29
  And I've always thought the token maxing thing is weird because in some ways it rewards
• 18:34
  inefficiency.
• 18:34
  I refactored two of my agents last weekend, brought the cost down by 90%.
• 18:39
  They consume less tokens.
• 18:40
  It's actually It's a more efficient agent.
• 18:42
  But if there were some token leaderboard, I would have probably
• 18:44
  gone Gunding.
• 18:45
  Yeah.
• 18:46
  And I think this notion of AI adoption having levels, think is true.
• 18:51
  But I think the tricky thing is it seems to change every two quarters.
• 18:55
  You know, a few quarters ago, having a GitHub repository with a bunch of shared skills on a
• 19:00
  Teams account maybe would have put you in the top.
• 19:02
  So I didn't think of what is the top 25% of companies doing versus what's the average
• 19:06
  company doing.
• 19:07
  And I think every quarter, it feels like the things that were top tier advanced become
• 19:12
  average.
• 19:13
  And so I don't know even know how by the time you end up measuring which level you're on, the
• 19:17
  levels will have shifted.
• 19:19
  But I do think a lot of these frameworks, I think, imply a couple of things that I'm not
• 19:22
  sure.
• 19:23
  Like, one, I I appreciate and acknowledging that level five doesn't exist yet.
• 19:26
  I'm not even sure that that's the right objective for most companies Yeah.
• 19:30
  Given the complexity of their business.
• 19:32
  I think what makes more sense to me is I've enjoyed following Jason Lemkin's journey of,
• 19:37
  like, using agents at Saster.
• 19:39
  And I think what he describes feels closer to me to what top usage looks like, is mostly
• 19:44
  autonomous agents doing a bunch of discrete tasks that are then rolled up either to some
• 19:50
  kind of orchestrator or a human, and they're being overseen and watched by a person who has
• 19:55
  judgement.
• 19:55
  You can look at something and say, oh, this is broken or this isn't producing the output I
• 19:59
  expected or wow, there's a new use case.
• 20:01
  We need to help teach the agent.
• 20:03
  I think this idea of like humans managing agents to me is what I see many of the most
• 20:08
  sophisticated companies doing.
• 20:10
  Are there some processes that run fully autonomously?
• 20:12
  Absolutely.
• 20:13
  And it's great.
• 20:13
  For a discrete task, I think that is great.
• 20:15
  But I think also a lot of companies, it's uneven.
• 20:17
  Your finance team might be l one, but your engineering team might be l four.
• 20:21
  What does that make your company?
• 20:22
  I don't know.
• 20:23
  Yeah.
• 20:23
  Do take the average?
• 20:24
  Do you, like, do you min max?
• 20:26
  And so I think we are so early in all of this stuff that my experience has been there are
• 20:32
  very few companies where everybody's consistently operating at a super high level
• 20:37
  unless it's three people.
• 20:38
  One of the things I've I've been having a long running conversation with one of our portfolio
• 20:42
  companies that builds it's been it's a fun one company.
• 20:45
  It's it's been around for a while.
• 20:46
  We've been sharing our AI building journeys, and her last update has a bunch of really
• 20:50
  amazing things that she and the company have built.
• 20:53
  Whereas a quarter ago, she was like, maybe I'm gonna have AI help us with customer support.
• 20:57
  Mhmm.
• 20:58
  And now she has an AI agent that is closing six or eight deals a quarter.
• 21:01
  And so I think the other thing is people, I think, are overestimating where people are on
• 21:06
  the average, but underestimating how quickly you can go from l zero to maybe l three.
• 21:11
  And I think we're gonna continue to look for frameworks and measurement methodologies that
• 21:15
  help us figure out kind of am I doing this right?
• 21:17
  And I think it's gonna take a long time before we know.
• 21:19
  And as soon as we find something that feels like it's working, the world will change again.
• 21:22
  She had a good quote, which was Steve Blank once said that a startup is not a small version
• 21:27
  of a large company.
• 21:28
  Mhmm.
• 21:28
  Similarly, an AI pilled company is not simply an AI assisted version of an old company.
• 21:33
  And so the one theme that rings through in the piece is that the entire infrastructure for
• 21:37
  what we think an AI native company looks like will likely not look like anything else that
• 21:41
  we've seen prior to your point about managing agents.
• 21:44
  I think the funny thing is every time someone tells me something, I'm I I hate like the what
• 21:48
  about ism.
• 21:49
  I'm like, but what about Google?
• 21:50
  They seem to have done a pretty good job.
• 21:51
  They didn't throw out search.
• 21:52
  So I I also think it's very comforting as a VC to believe that AI pills, startups, or or
• 21:58
  companies that are AI native from scratch will beat old companies in the same way.
• 22:02
  It was attractive to believe that every cloud would beat on prem every time.
• 22:06
  That that isn't actually what happened.
• 22:07
  That isn't on average, yes, cloud won.
• 22:09
  But there's a lot of funky weird on prem stuff still bought service and in production.
• 22:14
  And I suspect that not every AI built company will win every market.
• 22:18
  There will be the revenge of the incumbents, and, like, I wouldn't count them out just
• 22:21
  because they don't always fit a framework.
• 22:23
  We are all out of time.
• 22:24
  Thank you, Charles, for shopping in.
• 22:25
  Thank you for our listeners for joining as well.
• 22:27
  Please like and subscribe, and we will talk with you all next week.
• 22:30
  Thank you.
• 22:31
  Bye.