Latest / 1 to 100 / E54: Become AI Native with Jim Benton from Adapt

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E54: Become AI Native with Jim Benton from Adapt · 1 to 100

• 0:00
  I, I guess the thing that I'm most curious about, because
• 0:02
  Jeremiah, like mentioned organically in the, in the last
• 0:04
  conversation, that at this point, it's like the bill of his
• 0:08
  that's going up the fastest because of how much it's getting
• 0:11
  used inside of the company. And so the, the like the meta
• 0:15
  question that I have is, do you, do you find the way that?
• 0:19
  And, and of course you can like quickly describe the product,
• 0:22
  but I, I think the, the bigger learning that I'm most curious
• 0:25
  about for other SAS operators is or software operators is do you
• 0:30
  find that it is significantly more important to have that
• 0:35
  expansion, those expansion moments versus the land moment?
• 0:39
  And then how do you organize your company internally to
• 0:43
  mirror which side of it do you believe to be more important?
• 0:46
  Yeah, I think. Hey, Jeremiah, good to see you
• 0:48
  on that. Yeah.
• 0:49
  And actually, Jim, can you jump into and just tell, tell
• 0:51
  everybody a little bit about adapt and, and what it is that
• 0:54
  you do, because that'll, that'll help with this answer.
• 0:55
  Too, Sure, sure. So Adapt is essentially your
• 0:58
  company brain, but it's built and powered by the Adapt AI
• 1:01
  computer. And that is a very fundamentally
• 1:03
  different part of how we've approached things by being an AI
• 1:05
  computer versus just an LM call and using MCPS.
• 1:09
  And I think that the, you know, the key is once you connect all
• 1:12
  of these tools, so we'll see companies connect, you know,
• 1:14
  they'll start with five to 10 tools.
• 1:16
  Next thing you know, they've got, you know, 20 plus
• 1:18
  integrations, GitHub and linear and HubSpot and Google
• 1:21
  Analytics, you name it. Once you put those together at a
• 1:24
  team basis, it's this pretty insane thing where this, this,
• 1:27
  this computer has access to all of your knowledge, It can take
• 1:31
  action on the tools. It's all at the API basis.
• 1:33
  And So what you find is that people can know anything, do
• 1:36
  anything. And now it's just about how do
• 1:38
  you leverage that computer to do work that you just never thought
• 1:41
  was even possible before. And so I think to answer your
• 1:43
  question about what you, what's more important, landing or
• 1:45
  expanding? I think in the AI space, I mean,
• 1:47
  it is busy right there out there today.
• 1:49
  I mean, we see it, right? It's a, it's a fast space we're
• 1:52
  in, specially coming out of the SAS days.
• 1:54
  So landing is important. You got to break through the
• 1:56
  noise. You got to find that thing
• 1:57
  that's different, that resonates and I would say the big thing is
• 2:01
  just being frictionless. You know, the old SAS approaches
• 2:03
  of heavy salesmanship and you know, Click to sign up and talk
• 2:07
  to sales and go through the the full process.
• 2:09
  The best AI companies we see out there are the ones that are
• 2:11
  moving really quick, reducing the barriers, getting people
• 2:14
  right in on a self-service motion, and then having like
• 2:17
  wickedly strong sales assist motions to engage at the high
• 2:20
  levels, senior level, CE OS. But again, staying frictionless
• 2:25
  with them until we get those first types of tools connected
• 2:28
  and then we can hit on the expansion.
• 2:30
  OK, OK, so I'm going to try to say back to you like roughly 3
• 2:33
  steps that you think are it sounds like you have learned are
• 2:36
  really important. One is you want people to find
• 2:40
  that first magical moment without necessarily talking to
• 2:43
  someone on your team. When you because you you you
• 2:46
  said a few things, you said self-serve, you said they start
• 2:48
  with maybe 5 connections. So there was a few things you
• 2:50
  said that kind of triangulate to when they see that when they
• 2:54
  hear about a use case and when they set it up on their own,
• 2:56
  they have a starting point where they get that aha moment on
• 2:58
  their own pretty quickly. And then then, So now I have a
• 3:02
  question because you said sales assist.
• 3:04
  Yeah. Do you ask your sales team upon
• 3:06
  that aha moment to e-mail the CEO or the user who got the AHA?
• 3:11
  Like like yeah help help me understand what this where the
• 3:15
  Step 2 happens from that first moment?
• 3:19
  Makes sense. We went GA last month so that we
• 3:21
  moved from sort of this early access mindset where we were
• 3:23
  with design partners. You would sign up our sales team
• 3:26
  and reach out. We would do a, you know, a Zoom
• 3:27
  call and then we would connect. You literally live in the call.
• 3:29
  So in the 30 minutes we would have you up and running and
• 3:32
  connected, which is which is powerful, I think to to go
• 3:35
  deeper with GA. Yeah, CEO can get in.
• 3:37
  I saw one happen this weekend. CEO got in connected several
• 3:41
  tools over the weekend, started to run different queries against
• 3:44
  them and sort of got to their own aha moment and put a credit
• 3:47
  card in before sales could even reach out.
• 3:49
  And then at that point sales able to reach out and sort of
• 3:53
  paint the bigger picture really talk about an org wide piece.
• 3:55
  But that yeah, that is a massive change for us to get somebody in
• 3:59
  literally connecting linear, you know, I think it was Notion and
• 4:03
  different systems without talking to sales.
• 4:05
  That was a moment when I came in Monday that was like, we are, we
• 4:09
  are, we are doing the right foundational pieces to be one of
• 4:11
  the great AI companies out there.
• 4:13
  So, Jim, I'm going to do you a favor.
• 4:15
  Yeah. Could you save her?
• 4:17
  Because because your, because your sales team won't love to
• 4:20
  hear it directly from you. But CEO's play with stuff on the
• 4:24
  weekends. Like that's what we do.
• 4:26
  That's our play time. And so you're going to like,
• 4:29
  and, and, and so I don't know that you will see this
• 4:32
  consistently, but maybe you will see over weekends just like you
• 4:36
  just saw CEO's playing with your tool and then having that
• 4:39
  magical moment. And now the sales team is going
• 4:42
  to reach out on Monday. Yeah, I just wonder.
• 4:46
  Well, it's different. It's like, it's like, it's like,
• 4:48
  it's like in the restaurant industry, you would never have
• 4:50
  restaurants closed on the weekends.
• 4:51
  Yeah, it's interesting. At the end of the day, I don't
• 4:54
  know if the CE OS are really looking to have a human reach
• 4:56
  out to them at, you know, 10:00 PM on Saturday night in the old
• 4:59
  classic SAS way, right where it would either be a sequence or
• 5:02
  kind of a lightweight. Hey, saw you signed up That that
• 5:05
  that you're a of is over. I think that the human ear is
• 5:09
  not, but just sort of the generic, just a fast, quick
• 5:11
  touch of like, Hey, we're here. So I do think that getting them
• 5:14
  in and getting them to the aha moment in a self-serve way is
• 5:17
  such an unlock for an AI company and that the great companies we
• 5:20
  all know did that. I mean, think about the first
• 5:22
  time you used cursor. Nobody reached out.
• 5:25
  You literally downloaded it. You did a few things and within
• 5:27
  an hour you're like, holy crap, I have to tell every friend I
• 5:29
  know how cool this is. I think that's the experience
• 5:32
  now for us to get the AHA, just using adapt to do a search,
• 5:35
  similar to how you might be using, you know, Quad or
• 5:38
  ChatGPT. Although we actually do really
• 5:40
  remarkable things on that. That's an experience most people
• 5:42
  are used to, which is I didn't connect it to anything.
• 5:44
  I'm going to do a search. It'll look similar unless you
• 5:47
  really push us hard and, and leverage the computer aspect.
• 5:49
  It's when you connect a tool that we get a very big aha
• 5:52
  moment. And so connecting Slack is maybe
• 5:54
  a first use case and then doing deep analysis of your
• 5:57
  conversations and then you connect and then you quickly
• 5:59
  realize with a couple clicks, I can connect a couple more tools,
• 6:02
  maybe pop an API key in. And that is usually the quick
• 6:05
  aha. They ask something and they
• 6:07
  it'll cook and, and chew and 10 minutes later they're getting
• 6:10
  something that they just have never seen before.
• 6:12
  And at that moment, we've got a customer.
• 6:14
  Yeah, it's interesting. I mean, just to touch on this as
• 6:16
  somebody who is a customer, I think that that was the big
• 6:19
  thing for me is the ease of integrations, which actually
• 6:21
  Jim, at some point I think I want to come back to this, but
• 6:24
  integration piece is really compelling and one of the things
• 6:26
  you all have done and I, I'm curious, this is something I
• 6:29
  wish I could replicate. I don't know how to do it.
• 6:32
  Eventually the like the way integrations work is you
• 6:34
  literally take an API key and you give it to adapt and adapt
• 6:39
  there. There's some like something like
• 6:40
  a Slack connect, but a lot of like a lot of the tools use our
• 6:43
  smaller companies with their own AP is.
• 6:46
  And so we basically really just grab the API key, give it to
• 6:48
  adapt and adapt. We'll go figure out how to
• 6:50
  connect and get the information, which is incredible.
• 6:54
  So my team of non-technical people, like our technical
• 6:57
  people use or by and by technical engineers, they're all
• 6:59
  using clock code. They're not actually, they
• 7:01
  basically don't use adapt. Adapt is used by our more of our
• 7:04
  customer facing and, and internal teams.
• 7:06
  But in that context, those people with no training can
• 7:09
  actually go and give give adapt an API key and adapt just goes
• 7:13
  and figures out how to pull the data.
• 7:14
  Which to me that was one of the biggest things is within
• 7:18
  minutes, basically you have all these different things connected
• 7:20
  and you can start asking questions in Slack.
• 7:22
  And then for me, what I did with my team was when they would ask
• 7:25
  me questions, once I got this stuff connected, I would just
• 7:27
  say, hey, adapt and then give it the question, effectively a
• 7:30
  different version of it and show the team like, look, you can
• 7:33
  just get this. And so now the behavior in our
• 7:35
  company like very quickly has shifted.
• 7:37
  It's not 100% there, but has very quickly shifted towards
• 7:40
  that being the default where people actually just ask the
• 7:42
  question. And because it's so easy to
• 7:44
  connect to the integrations, it's been really easy to also
• 7:47
  drive the adoption. And so I think that's to me,
• 7:49
  that's actually, I agree with that as like the, the thing
• 7:53
  that's most compelling. And I'm curious like how, how
• 7:57
  did you come to I, I guess that that way of doing things,
• 8:00
  because I think typically what would have happened in the past
• 8:02
  is you would go in and there'd be a whole process.
• 8:05
  You would need a custom integration, you would need all
• 8:07
  this kind of stuff. But you've been able to say,
• 8:09
  just give us the API key and we'll figure it out.
• 8:11
  Yeah, I think it was a moment it was a little bit of a moment in
• 8:14
  the early days of of building adapt.
• 8:17
  One of my, you know, Co founders, incredibly strong
• 8:19
  technically had a had a lot of experience before adapt both on
• 8:22
  the database side as a founder building just a wickedly fast
• 8:25
  database, but also in the sandboxed containers and, and
• 8:28
  spinning up, you know, virtual machines for, you know, past
• 8:31
  work. And so when you, when you
• 8:33
  thought about how do we enable AI to have these special powers
• 8:36
  and to do incredible things with APIs by giving it its own
• 8:39
  computer, it means that the, the AI can figure out how to make
• 8:42
  sense of that API or you could give it its own instructions and
• 8:45
  adds it to the knowledge base that everyone in the company now
• 8:46
  has that. But essentially, AI knows how to
• 8:49
  make sense of these API keys of all these different tools out
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  there. It can write custom scripts to
• 8:53
  make it work. It can write the custom code.
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  And so instead of us preconfiguring thousands of
• 8:58
  integrations as the old SAS model would have been right,
• 9:00
  you, you go through and the engineers build it and it's
• 9:02
  very, very structured and rigid. We're able to give AI the key
• 9:07
  and say, what can you do with this thing?
• 9:09
  What's all the magic you could do?
• 9:10
  What's custom code would you want to write?
• 9:11
  So you could do exactly what the user wants.
• 9:13
  And every time the user asks a question, whether it's through
• 9:15
  Slack or a web app, it'll write that custom code to make that
• 9:18
  sense. And most importantly, it can
• 9:21
  spin up lots of these different, you know, swarm of different
• 9:25
  connection request at the same time.
• 9:27
  So unlike an MCP, like I get Claude, where you're going to go
• 9:29
  through one request at a time, It'll schedule a tool call, then
• 9:32
  a tool call, then a tool call. We'll swarm out and say, hit
• 9:35
  linear HubSpot, grab something from Notion and then pull the
• 9:38
  data back together in a very precise surgical way.
• 9:40
  Then run Opus, you know, 4.7 against it.
• 9:42
  And that's the magic why people say we've just never seen an
• 9:45
  answer like a DAP. Like how is it that you're
• 9:48
  generating such a different than what we're seeing even when we
• 9:51
  use Opus 4.7, you know, directly in cloud and that's the reason
• 9:55
  you give it a computer. It's writing surgical pieces.
• 9:57
  It's not having context issues and it's not scheduling one
• 10:01
  after the other. It's swarming.
• 10:02
  I got to ask, I imagine this is something that a lot of people
• 10:06
  building and specifically in e-commerce stats are hearing and
• 10:08
  thinking, oh, that would be nice because they just set up the
• 10:11
  meta MCP or CLI and they're like, it doesn't work right?
• 10:14
  Or they set up marketing API and they get their account banned.
• 10:17
  I'm like, why? Right.
• 10:17
  That's the number one question I just keep seeing on X my whole
• 10:20
  feed. Why is my account banned right?
• 10:22
  I set up the integration wrong and now I, you know, my ad
• 10:23
  account is banned or something. So integration stresses probably
• 10:27
  something that a lot of people can relate with.
• 10:28
  But why, why did you call it adapt?
• 10:30
  Like right now it, you know, I imagine there's a few people
• 10:32
  like me that are like monkey brain listening to this and
• 10:35
  going, wait, I I still don't get it.
• 10:36
  What why adapt? You know, good integrations,
• 10:38
  good context from all my different apps for the LLMS to
• 10:41
  use. But like what?
• 10:42
  What is adapt? Like, what does it actually do?
• 10:44
  And why would I sign up and get that aha moment from Adapt?
• 10:47
  You know, my side after we after Chorus dot AI was acquired back
• 10:51
  in 21, I was CEO, of course, we were leading AI pre LLM motion.
• 10:55
  I spent the last few years down at Stanford start X.
• 10:57
  I'm a mentor, lead mentor for the, the the Stanford start X
• 11:00
  accelerator, working at that just a lot of great teams and I
• 11:03
  was building myself. So I'm in it.
• 11:04
  I'm with these young and, you know, more seasoned
• 11:07
  entrepreneurs. And I do remember, you know,
• 11:09
  about a year and a half ago. So it's very early.
• 11:11
  One of the teams across from me mentioning are using cursor and
• 11:14
  I wasn't. I think our team was using some
• 11:15
  web flow and some other, you know, kind of previous
• 11:17
  generation tools. And a friend I was working with
• 11:20
  at the time said, let's let's get you into cursor, especially
• 11:22
  as a non engineer. I've always been leading a lot
• 11:25
  of great product teams and very close.
• 11:26
  And I love the front end. But I got into cursor myself
• 11:30
  with the guidance of like Acto that it's weird in production
• 11:33
  work. It wasn't just, you know, vibe
• 11:34
  coding something. It was it was tied to an old
• 11:36
  legacy app. And within 24 hours, I had that
• 11:38
  moment of, wait a second, there's two AIS out there.
• 11:41
  I had no idea that the developers had one AI.
• 11:44
  That's the greatest product market that I've ever seen.
• 11:47
  And everybody else I know and see at social events is using a
• 11:50
  completely different AI, like a ChatGPT experience, which was
• 11:54
  special and remarkable, nothing like the AI that developers had
• 11:59
  that actually did work for them. And so I had this moment of, Oh
• 12:02
  my gosh, the world is about to fundamentally change.
• 12:04
  And I got 12 to 18 month period and no one knows it on the
• 12:08
  business side. The developers know it.
• 12:10
  And that's what when I, when I connected with Sean and John
• 12:12
  Andrew by the two other Co founders, I saw the early roots
• 12:15
  of what we were doing. I was like, we're about to bring
• 12:18
  the other AI, an AI that can not only understand, but take
• 12:21
  actions for people, like do the work to every other user in an,
• 12:26
  in a completely natural language way.
• 12:28
  So not, you know, detailed UX work streams for agents.
• 12:30
  No, just talk to it. You want to build an app that
• 12:33
  sits on top of site, Just talk to it.
• 12:35
  And you want to do incredibly complex things like scan every
• 12:38
  sales call for the last, you know, year and build a product
• 12:41
  road map based customer feedback.
• 12:42
  You can't do that with an LM. You can do that when you have a
• 12:44
  computer. And that's the part that led to
• 12:47
  why we're about to get make everybody AI native.
• 12:50
  And maybe to finish that point. It's so important.
• 12:53
  Like I, I, we've had fun in our, especially in the SAS days, a
• 12:55
  lot of fun building these things up.
• 12:57
  We're here in San Francisco, we're in the Presidio.
• 13:00
  I mean, we have front row seats to this.
• 13:02
  If you don't go AI native soon, if your leadership doesn't help
• 13:06
  your team, you know, the teams go AI native.
• 13:09
  Personally, I'm really sad thinking about the outcome of
• 13:11
  what that is. I mean, just think about your
• 13:12
  friends, your your parent, whoever it is, if they don't go
• 13:16
  AI native, which means they just don't embrace it.
• 13:18
  They don't learn to get the superpowers.
• 13:20
  They will get pushed out of the workforce.
• 13:21
  They're not going to get hired by the new AI native manager.
• 13:24
  They're going to retire early. And so just think about sitting
• 13:26
  around the dinner table with people that have been
• 13:29
  marginalized out of the workforce.
• 13:30
  They're kind of bitter now on AI.
• 13:32
  They're, they're young, they're too young to be retired and
• 13:34
  they've just killed their earning potential.
• 13:36
  And so if we could solve that with just a click, you know,
• 13:38
  Jeremiah, you mentioned just click of an integration.
• 13:40
  Everyone in Slack had your tool. So it wasn't that they had to go
• 13:43
  install it. You put it in once they said add
• 13:45
  adapt, we're now instantly making everyone AI native.
• 13:49
  And literally the next day they're going home saying I've
• 13:51
  never had so much fun at work. They're having a cursor quad
• 13:54
  code like moment. And I mean, what a gift, right?
• 13:57
  That's why I keep telling people work has never been more fun.
• 13:59
  But we need to get these superpowers to you.
• 14:02
  Otherwise, you know, we're not doing our jobs as leaders.
• 14:05
  I really like the name now. OK, there's a bunch of things
• 14:07
  that I would love to dig into, by the way.
• 14:09
  Let's do that. The most important one being I
• 14:12
  love John Andrew and did not realize he was your Co founder.
• 14:15
  Yeah. So yeah, yeah, yeah, yeah.
• 14:18
  I I don't know how I did not make the connection prior to
• 14:20
  literally right now. And he the source, I mean, the
• 14:23
  initial just to play on that John Andrews, a solo founder of
• 14:26
  Wander Teal fellow very unique special person.
• 14:29
  If as you know, meeting him just brilliant.
• 14:31
  And as a solo founder, I mean, it's yeah, Ronnie Wander, he
• 14:35
  wanted a better way to use AI to run the business.
• 14:38
  And that's the early origins of, wait a second, what if we built
• 14:41
  this thing called Adapt? He pulled in, you know, an early
• 14:44
  engineer he'd worked with that, you know, very brilliant
• 14:46
  engineer. I got connected in and was like,
• 14:49
  this is exactly the future I see, especially this blank
• 14:51
  canvas kind of UX approach. And that was the early origins.
• 14:54
  And then we took that out and did our seed round and so forth.
• 14:57
  That's amazing. Yeah.
• 14:59
  One of the things that you said, first of all, I, I, you can push
• 15:05
  back on this, but you said something like early retirement.
• 15:08
  And I want to push on that because I am not sure that age
• 15:12
  is correlated to whether or not people are becoming more AI
• 15:15
  native. And the reason is I am seeing
• 15:19
  this very weird phenomenon where candidly, like roughly people my
• 15:25
  age seem to be the most resistant.
• 15:28
  So I'm like, I'm 40. I also see a bunch of people who
• 15:31
  are resistant who are like 23, weirdly enough.
• 15:34
  And conversely, I've like shared the story before, but my my
• 15:38
  mother is like embracing it big time.
• 15:42
  And I and so I just am not like and maybe look, I have no idea
• 15:46
  what bias my sample has, but for the first, usually technology
• 15:51
  has this bias where the adopters tend to be younger.
• 15:54
  I'm just not sure this time. Yeah, I'm not sure.
• 15:57
  I'm not sure that actually it's age Coral, especially inside of
• 15:59
  companies, the number of stories and and now this comes to the
• 16:02
  corporate adoption point that I was, I was curious about second.
• 16:06
  But I am actually seeing that the people who are like the best
• 16:11
  executives and they tend to be a little old, like they tend to be
• 16:14
  a little older. They're not 24 are the ones who
• 16:17
  are adopting at the fastest and they are having trouble getting
• 16:21
  their teams to adopt quickly. And and it's very unusual that
• 16:25
  this is like how these things would would play out, right,
• 16:29
  Especially for the non-technical teams.
• 16:31
  I'm seeing executives like your CEO story is actually exactly on
• 16:38
  point to this point. It's like you're seeing the more
• 16:41
  senior people be more hungry to learn and roll their sleeves up
• 16:45
  really fast. And it's just not obvious to me
• 16:47
  that that's happening in the more junior roles that tends to
• 16:50
  be aged lower. I'm curious if you're seeing
• 16:53
  that. I agree with your point that it
• 16:55
  can be across the spectrum for sure.
• 16:57
  And there there's been a, you know, a very young cohort that's
• 16:59
  been, you know, very much driving some of the cutting
• 17:02
  edge. I mean young, meaning 1920, I
• 17:04
  mean a little bit younger than what we saw even in the SAS
• 17:06
  days. And then you have a senior
• 17:07
  cohort that is great managers, managers learned how to use AI
• 17:10
  earlier. They know how to do leverage.
• 17:11
  They know how to ask, you know, something to do something for
• 17:14
  them. You know, they're not
• 17:14
  necessarily individual tasks. So I think we've seen a
• 17:17
  spectrum, but I do think in general there is a group that
• 17:20
  just hasn't latched on or found the magic moment or chose early
• 17:23
  to kind of fight it and say it doesn't actually help.
• 17:25
  I, I just met with a, a very strong engineer just the last
• 17:29
  couple weeks working at one of the large great companies out
• 17:32
  there. Yeah, publicly traded and you
• 17:35
  know, not there anymore. But I, when I asked about just
• 17:38
  using the new code editing tools, I, I sensed that there
• 17:41
  was a, a push back that surprised me.
• 17:43
  And I was like, and feedback was, hey, look, I would dig into
• 17:45
  that. I know you've just been doing it
• 17:47
  your way and you've been an incredible career.
• 17:48
  But I would, instead of saying you just use it as like a light
• 17:51
  review, I would really embrace it because what I'm seeing is
• 17:54
  that it's fundamentally different.
• 17:55
  And just last night that individual pinged me and said,
• 17:57
  hey, it was like 2 weeks later, I went deeper on what you said
• 18:01
  and I'm genuinely impressed and surprised by what I'm saying.
• 18:04
  And so it's a small example of if people don't do that, they're
• 18:07
  not getting hired. And I think the last point is
• 18:09
  the managers getting promoted over the next 24 months are not
• 18:12
  non AI natives. There's just no way the person
• 18:15
  that didn't lean into AI is going to be the one that gets
• 18:17
  promoted by the CE OS, etcetera. So what will happen is we'll see
• 18:21
  a very fast acceleration of people that have really embraced
• 18:24
  AI and learn to use it the right way are only going to want to
• 18:27
  surround themselves with high agency AI native people.
• 18:30
  And once that happens, you know, like it's a different world and
• 18:34
  and it accelerates as such a faster clip that I'm worried it
• 18:37
  really threatens people that are out of it.
• 18:38
  This is just moving faster than other innovations we've seen.
• 18:41
  And it makes me sad because nobody wants to be your friends
• 18:44
  or others to be outside of this. It's too good.
• 18:47
  It's too easy actually, once you get into it.
• 18:49
  You just need someone to help get you in it.
• 18:52
  I said exactly what you just said.
• 18:54
  I was at a reporter dinner yesterday.
• 18:56
  So there were folks from like Bloomberg, TechCrunch, whatever,
• 18:58
  and I made exactly this point about the AI natives will not
• 19:01
  want to work with the non AI natives.
• 19:03
  And there's a big sort happening and most of the table did not
• 19:10
  understand that. I think what you're, I mean, I
• 19:13
  understand it. Trust me, I am living it.
• 19:15
  I deeply understand it. I am as worried as you are.
• 19:20
  I don't even think most people have fully internalized that
• 19:23
  yet. And that's my like big yes.
• 19:25
  And, and and that makes it even scarier.
• 19:28
  You know, I think it's the closest comparison to, you know,
• 19:31
  the AI native people not wanting to work with the non AI native.
• 19:34
  People is when you meet people. Who say you can't about anything
• 19:37
  that you know that you can do. You know, I'm sure you people
• 19:40
  you've met people like this that are like, oh, you can't do that
• 19:42
  or that's not possible or this person can't do that.
• 19:45
  And you hear the conversation, you're like, oh, I know this
• 19:47
  isn't true. Why have you got stuck on this?
• 19:49
  The idea that like, everything is a red light and everything
• 19:51
  isn't possible. And I think it's you, just
• 19:54
  you're sort of living in two fundamentally different
• 19:56
  realities. 1 is super pessimistic and negative, right?
• 20:00
  It feels bad to be around. 1 is more optimistic, right?
• 20:03
  And more of a green light than a red light.
• 20:05
  The speed you, you find that the AI natives go fast, right?
• 20:10
  They, they just see things as like, well, I can quickly just
• 20:12
  spin these things up and get a, a first Rev or a, a detailed
• 20:15
  view of it faster. So there's a speed aspect.
• 20:17
  The second part is, and, and we're seeing changes, but when
• 20:20
  you see somebody come to you that did not use AI for some
• 20:23
  deep thinking on something. So maybe they're building out a
• 20:25
  new Commission plan or a new way of designing yourself service
• 20:29
  pricing. And you see that they just sat
• 20:30
  there and did it all by themself.
• 20:32
  Clearly we want the human side and I think we're all seeing it
• 20:34
  right now. We, we can't lose human thinking
• 20:36
  like it is so valuable, but you need to also then leverage AI to
• 20:41
  see what the gaps were. What did we miss?
• 20:43
  What other new external thinking can I mix in?
• 20:45
  And when you see a human do both, which is, hey guys, here's
• 20:48
  a new messaging strategy. And you know, I've run this
• 20:51
  through adapt, which knows our entire business incredibly well
• 20:55
  and does the external world incredibly well.
• 20:57
  And here's what it thought about my new messaging and how it
• 20:59
  rated it and what it also recommended.
• 21:02
  Well, then we're aligned. You basically are superhuman.
• 21:04
  You are incredible for who you are.
• 21:06
  You've used the best AI and you've used all the company
• 21:09
  knowledge, which I want, I want, I want everybody's mind
• 21:11
  involved. But when you just send me a
• 21:13
  Google Doc of your thoughts, you're not AI native.
• 21:16
  What I need to then go ask the AI.
• 21:19
  And again, I don't want the AI to do the thinking for us all
• 21:22
  the way. I wanted to review, identify,
• 21:24
  help make us better. On the point of people being
• 21:27
  resistant, I wonder how much that comes down to how worried
• 21:32
  are you about it taking your job.
• 21:34
  And I, I think that when you look at senior leadership in
• 21:35
  companies, you're not actually worried about that at all
• 21:38
  because your job is not delivery oriented.
• 21:39
  It's strategy oriented. It's focused on the you, you are
• 21:43
  used to saying, here's the thing that needs done.
• 21:45
  I'm going to go give that to somebody else to go do.
• 21:47
  If you are a software engineer who has been a software engineer
• 21:50
  for 30 years and your job has always been shipping code, it is
• 21:53
  a bigger threat to you than it is the, the, the C-Suite person
• 21:58
  who is used to delegating. And I think that's part of the
• 22:00
  problem here. I also think what Jack said is
• 22:01
  probably part of the problem too.
• 22:02
  But ultimately I think that makes sense.
• 22:04
  And there's your natural, it's the fight or flight, right?
• 22:08
  Like as soon as there's something that threatens you,
• 22:09
  that's, that is our natural reaction.
• 22:11
  And so I think that's a lot of what we see here is like, if
• 22:14
  you're closer to the, the, the delivery of it, of the actual
• 22:17
  like in product, I think that there's more risk to you
• 22:20
  ultimately on these things. And, and I think that's valid,
• 22:22
  actually, But the irony is that those who aren't willing to try
• 22:27
  end up being the ones most at risk.
• 22:29
  Can I can I make a a provocation and then ask a question on that
• 22:33
  point? OK my EA directly told me
• 22:38
  because we do this like we're doing this like big AI
• 22:40
  challenge. I think I've shared this story
• 22:42
  before, but my E directly told me I'm going to make sure that
• 22:46
  100% of my job is done by Claude and nothing has made me want to
• 22:51
  keep her more than when she stated that objective.
• 22:55
  Obviously right? Like every.
• 22:57
  This is like a CEO's dream that that's what someone would come
• 23:00
  to them and say. Word of We'll come back to it.
• 23:02
  OK, OK, so because, because now I'm sitting there thinking she
• 23:06
  has high initiative as she's automating these things.
• 23:09
  She's showing me that she was thinking about the outcome, the
• 23:12
  versus just arbitrary delegation.
• 23:14
  And now I'm like, Oh my God, I can trust her with all of these
• 23:16
  other things that I like previously would not have like
• 23:19
  even thought to trust her with, right?
• 23:20
  So she's showing me like the skills and attributes that I,
• 23:23
  that I care most about in, in terms of like more tasks and
• 23:27
  other projects and things like that.
• 23:28
  So at least for me, that is like my view of that.
• 23:33
  The question that that begs is first of all, and I'm curious,
• 23:37
  Jim, it sounds like you have a provocation on this, but is that
• 23:40
  generalizable, right? Because I don't know if it's
• 23:43
  generalizable and perhaps we will say it's not generalizable
• 23:45
  globally. The other thing I wonder though
• 23:48
  is how much of this is just what is around you.
• 23:51
  So like I've recently been asking my team to come spend
• 23:55
  some time in San Francisco. And I think it's because if you
• 23:58
  walk around in San Francisco, it's really hard to not become
• 24:02
  AI native. Like I can't see a billboard
• 24:05
  that is not something AI oriented like a cab, a bus, a
• 24:10
  train. Like I'm like no matter what I
• 24:13
  do, I cannot escape it. And so I'm wondering and, and so
• 24:19
  there's like this cultural question that I'm very curious
• 24:21
  about. It's like I can tell that this
• 24:23
  city, something special is happening right now, but I am
• 24:26
  wondering inside of organizations, what is the
• 24:29
  cultural setup in Jeremiah? One thing you are saying is
• 24:31
  people are worried about whether or not their job is going to be
• 24:33
  taken. But I think that's it gets a
• 24:35
  much harder question of what is the culture in your company as
• 24:37
  to whether or not that person is afraid that their job will be
• 24:39
  taken. Right, I mean, I think I've,
• 24:42
  I've 2 two thoughts on that. I'll start on Jeremiah's because
• 24:44
  talking about the coders word that, you know, suddenly cloud
• 24:47
  code can take their job. Clearly the way that we do our
• 24:50
  work has changed like on that role.
• 24:51
  Absolutely, But you're also seeing challenge right now where
• 24:54
  people are hiring engineers that don't actually fundamentally
• 24:56
  know maybe what great code looks like.
• 24:58
  And so there's a lot of vibe coding and it's creating some
• 25:00
  friction and some thrash. And let me give you an example.
• 25:02
  Take the thing that we each know really well.
• 25:04
  Like, what is the thing that you are literally an expert at after
• 25:07
  all these years of experience? When you ask AI on one shot to
• 25:12
  build that thing that you're an expert on, it does not get it
• 25:15
  right because you know, you know what the right answer is and
• 25:18
  you're like, whoa, whoa, this is wrong.
• 25:19
  But you know, this is good, but change this, change that and
• 25:22
  you'll do a few Revs basically teaching AI and it'll be like,
• 25:24
  yes, you're right. You know, I need to do better.
• 25:26
  But when you do things that you don't know very well, AI looks
• 25:29
  Florida State perfect. So when you take the coder that
• 25:32
  doesn't know coding that well, then the vibe code is perfect,
• 25:36
  right? What what are we going to do
• 25:37
  with it? And so my point that is that as
• 25:39
  you see people that are really strong technically and then they
• 25:42
  learn to use these tools in incredibly special ways.
• 25:45
  I think they have a very large unfair advantage over everybody
• 25:49
  else right now and can do magic with these tools that I don't
• 25:52
  think the tools are right now doing on their own.
• 25:53
  So that's one one point of it that the second quick point on
• 25:56
  the EA using 100% caught completely love AI native, but
• 26:00
  there is like a a balancing act of the human like we want
• 26:03
  ultimate humans to win. And they know that if you're EA
• 26:07
  use quad to write the most perfect, you know, AI response
• 26:11
  to me when I e-mail you. I'm now over it.
• 26:13
  I don't want it. That's not it's it's it was cute
• 26:15
  a month ago. It was cute maybe three months
• 26:17
  ago. I want an actual human response
• 26:19
  now. If the quad helped her to, you
• 26:22
  know, AI enabled her to be fast, to have some data points, to do
• 26:26
  something really authentic, it's great.
• 26:27
  But I think we're all starting to realize that human
• 26:30
  communication, there's a lot of trust built in the words we use,
• 26:33
  and there's a lot of noise that's coming.
• 26:35
  And so we want to use the deep thinking, yeah, that this
• 26:37
  company brain to help people think.
• 26:38
  But we still want them, you know, critically putting pieces
• 26:42
  together, putting their own stamp and touch on it.
• 26:44
  And I think people are begging for that right now.
• 26:46
  OK, I definitely agree with you. So I will amend my statement.
• 26:51
  The things that she are she is doing is actually all of the EQ
• 26:55
  parts of the job she is doing herself because that's what
• 26:59
  she's exceptional at right and everything else.
• 27:03
  But like the task organization Rich like the annoying me to
• 27:06
  remember to that way I actually do what I'm supposed to do.
• 27:10
  Like have you done these things? Here's what you promised people.
• 27:12
  You've not done it for four days.
• 27:15
  All of that is all automated. And and so like she has struck
• 27:20
  this like exactly the balance that you're describing, which I
• 27:25
  think is critical and and totally underappreciated.
• 27:28
  Jack, I don't know if you remember, but we made this joke
• 27:30
  in a previous episode around like humans should just worry
• 27:33
  about like the interaction with other humans and the like, human
• 27:37
  level thinking. But there's a lot of thinking
• 27:40
  that computers are are better AT and, and, and computers should
• 27:43
  do the computer thinking. So.
• 27:46
  Yeah, yeah, definitely. I think the EQ is a great way to
• 27:50
  think about that is that people really do need the EQI think
• 27:53
  you're, you're, if you talk to friends looking for jobs right
• 27:55
  now, what's challenging for them is that everyone's looking the
• 27:57
  same. They have a perfect cover
• 27:58
  letter. They got this whole
• 27:59
  presentation. And as a hiring manager, I
• 28:01
  can't, I don't know what it is. It's like there's a middle man
• 28:03
  that literally delivered their career to me.
• 28:06
  I, I need to see how they write what they do and I want them
• 28:08
  using AI, but not necessarily to be synthetic on their voice.
• 28:14
  And so I even I've been training AI.
• 28:15
  Don't, don't write. If you're going to try to take a
• 28:17
  stab at something, don't write something fake like, oh, I loved
• 28:20
  your XYZ. Give it to me straight.
• 28:22
  You signed up. I noticed this.
• 28:23
  I want to do this. Let's let's be really functional
• 28:26
  about this, but the IQ side, the ability to do special powers and
• 28:30
  EA plus AI should be able to do so much more and see a bigger
• 28:33
  thing and reason differently. And that's the magic and to
• 28:36
  understand your workload. I mean, if if you have a company
• 28:38
  brain and she had access to these tools that you're in, the
• 28:41
  speed in which she could react would be dramatically faster
• 28:44
  than waiting to connect with you.
• 28:45
  And the ability to build triggers of like, oh, if this
• 28:47
  meeting happened and you looked at the transcript and here's the
• 28:49
  notes. Now use your EQ to have the
• 28:51
  perfect follow up or gift, etcetera.
• 28:53
  It's magical. We just need the human touch
• 28:56
  though. Yeah, I I totally agree, Jeff.
• 28:59
  I'm really curious. Another thing that I think a lot
• 29:01
  of software founders are thinking about right now is what
• 29:07
  are modes that will persist? And so I'm curious how you think
• 29:09
  about that in the context of adapt and then how do you think
• 29:14
  about the I I get very curious right now about how to think
• 29:20
  about capitalization and like what are outcomes that are
• 29:26
  possible because the mark the shape of the market has never
• 29:29
  been stranger of the of the capital markets has never been
• 29:32
  stranger. And so, yeah, I'm two totally
• 29:35
  unrelated questions, but I am very curious on both, Yeah.
• 29:39
  How do you think about modes and defensibility?
• 29:41
  And then totally separately, how do you think about what is the
• 29:43
  right way to capitalize a business like yours?
• 29:46
  Yeah, it's, it's, it's and what if?
• 29:48
  I mean, how lucky are all of us to be in this right now?
• 29:50
  I mean, honestly, I've seen different ways, but I mean, just
• 29:52
  think about what we're doing right now.
• 29:54
  We are just at an epic, epic time of innovation and nobody
• 30:00
  knows where it's going. I, I talk to every friend, the
• 30:02
  smartest people that are in it and you say, where's it going?
• 30:05
  You talk to friends from open AI, etcetera.
• 30:06
  There is a sense of we're not even sure what that next open
• 30:10
  claw moment is in three weeks that might happen.
• 30:11
  Like there's this really fun early stage that we're in.
• 30:14
  I saw it back in the 99 era when we were doing, you know,
• 30:17
  evite.com and those startups. But this one's different and it
• 30:20
  is moving at a different speed because it's just it just
• 30:22
  there's so much more capability in it.
• 30:25
  And so when I think about when I think about the moats, when I
• 30:28
  think about the space one, how neat to know that you're working
• 30:32
  on something that is going to be an inevitability.
• 30:33
  Every single company will have a company bring not a bunch of AI
• 30:37
  tools, you know, not a license where hey, everybody here's like
• 30:40
  an individual AI tool that you can use to do your work.
• 30:42
  That was neat. That was like a 2025 era.
• 30:45
  No, hey, we run. I think the first interview
• 30:48
  question you will ask in about two years.
• 30:50
  Is he, before I even go, what's the AI?
• 30:54
  What is the company brain AI that we're using?
• 30:55
  Because I, I've been working at adapt companies and it has been
• 30:58
  the most insane experience. But I've heard friends are at
• 31:00
  these other companies running on the XYZ and it's miserable.
• 31:03
  It's a surveillance state. It's counting mouse movements.
• 31:05
  It's, it's some of the stuff we just heard about with meta doing
• 31:08
  right where they're, they're training off of this and these
• 31:10
  are decisions we need to make. And I, I talked to our team
• 31:13
  about this, like, I really want us to be on the side of making
• 31:17
  it so that our friends and family when they go to work,
• 31:20
  don't say you just screwed up work.
• 31:21
  I mean, it used to be great. Now all of a sudden, no, I want
• 31:24
  them to say we literally threw on adapt or I joined an adapt
• 31:27
  company and I've never had so much fun.
• 31:29
  And the way that you've sort of non emotionally brought our
• 31:32
  teams together, the way you sort of review analytics in a way
• 31:34
  that has no politics, the way that you've just augmented
• 31:37
  everybody. And so the first part of that is
• 31:39
  we're playing in just the most massive market.
• 31:41
  I mean, there is trillions of dollars of transformation.
• 31:44
  Every single company is going to have a single AI brain.
• 31:48
  And I've just watched SAS companies chase market share it,
• 31:50
  it goes to many different flavors on it.
• 31:52
  And I think this will be a horizontal play.
• 31:54
  I think there's a lot of vertical AI.
• 31:55
  They've done quite well right now.
• 31:56
  They'll continue to have grid growth, but this one's
• 31:59
  different. Once you start to put in the
• 32:01
  horizontal layer and what we see and Jeremiah, you, I'm curious,
• 32:04
  you start to realize, I'm not quite sure I need this other
• 32:06
  thing that just ties into this one silo of, of marketing or
• 32:10
  finance. And over the next, you know, 12
• 32:12
  to 18 months, you're going to see this like virus, this
• 32:15
  productivity virus of hey, why don't we connect more tools to
• 32:18
  the brain? The brain just got smarter.
• 32:19
  Let's have more knowledge in it. How do we create a reasoning
• 32:22
  engine that's always on and persistent behind the scenes,
• 32:24
  which is a whole new way to think about AI than just ask,
• 32:27
  query and generate, no, we're about to move.
• 32:30
  You know, this is stuff we're working on into a far more
• 32:33
  proactive, always on system of intelligence that truly starts
• 32:38
  to understand patterns that the teams would not be on the spot
• 32:40
  on their own and they're not even asking for.
• 32:43
  And so the Moat that these are the moats is removing from a
• 32:46
  tool. You ask, you get an answer, you
• 32:48
  know, add adapt. What do you think about this?
• 32:49
  I love it. That's what we do and it's
• 32:51
  powerful. At what point does Adapt see the
• 32:53
  bigger picture, bigger than ACEO could see start to cross
• 32:56
  reference patterns of why did we lose that deal?
• 32:58
  That's not just a query right now where you go to HubSpot and
• 33:01
  a few other pieces. It's already identified a
• 33:03
  product decision six months ago that had a chain reaction and
• 33:06
  it's identifying and bringing this to us.
• 33:08
  That's what we're about to see. And those engines, that
• 33:11
  reasoning engine is going to be different modes that are
• 33:14
  different than just the frontier models.
• 33:15
  And how we apply the frontier models to these extra reasoning
• 33:19
  will be a big deal. But if you're model agnostic and
• 33:22
  tool agnostic, then you really have the ability to tap into all
• 33:25
  the best models. So as you know, ChatGPT image 2
• 33:28
  comes out and you're like, that's amazing.
• 33:29
  Boom, top it in. And so I think that the mode is
• 33:32
  being agnostic. We know that the enterprise
• 33:33
  likes flexibility, likes to be able to make bets and make sure
• 33:36
  that it'll always be the most intelligent enterprise.
• 33:39
  And then two, it's what we do with this that goes far beyond
• 33:43
  ask and get a quick answer back that I think is going to be the
• 33:46
  next iteration that we see. I mean, we'll be launching this
• 33:49
  at the end of the month. It's a very powerful extension
• 33:51
  of what we're doing. I think the, one of the things I
• 33:55
  appreciate as a user is adapt is the the 1st, it's actually like
• 34:02
  a really good response. Half the time, the first
• 34:04
  response, right? And then as when you're asking
• 34:07
  something new that you haven't done before.
• 34:09
  And then the other half of the time there's something missing.
• 34:10
  There's missing context. There's there's information that
• 34:13
  needed that adapt didn't have to be able to give the right
• 34:15
  answer. But what I love is you basically
• 34:17
  just look at me like, OK, well, that's not quite right.
• 34:18
  Hey, Adapt, can you add this piece of context?
• 34:21
  And then you save it and it's done.
• 34:23
  And then every time after that, it has that context and it's,
• 34:26
  it's getting better. And I think that's one of the
• 34:28
  things that's going to be really interesting to see.
• 34:30
  I mean, honestly, Jim, I wasn't thinking about it.
• 34:33
  I am not thinking about this problem the same way you are.
• 34:35
  So just to even hear what you were describing there, I think
• 34:37
  it's really cool. Like I see the, I see that
• 34:40
  vision, I see what that can be. I think it's really interesting.
• 34:43
  And one of the things I, I would love to talk about, I love
• 34:46
  talking about pricing. And I think this is a really
• 34:48
  interesting thing when it comes to not just adapt, but any sort
• 34:51
  of AI where it's token based, basically like how you think
• 34:55
  about that. And, and just like, to be fully
• 34:57
  honest as a user, I mean, our spend is about four times as
• 35:01
  much right now as I thought it was going to be when we signed
• 35:04
  up. And that's not because it's like
• 35:08
  you're charging me more. It's because it just keeps
• 35:11
  compounding, right? The more people start using it,
• 35:13
  the more like it just keeps going and going and going.
• 35:15
  But there's an upper limit. There's a day in which I'm going
• 35:17
  to wake up and be like, wow, this is such a massive line
• 35:20
  item. Can I justify that?
• 35:22
  And I, I think the, this is something I'm thinking about
• 35:25
  with AI in general is what, what does that look like?
• 35:27
  I mean, Claude, for example, just got way more expensive.
• 35:29
  There's a world in which like token costs could rise to the
• 35:33
  point where we start to look at things and say, I'd rather just
• 35:35
  have a human do that or I'm not going to do that at all because
• 35:37
  it's just too expensive. So I'm, I'm curious how you're
• 35:41
  thinking about that and, and the future.
• 35:43
  And obviously if you're the brain, there's a premium that
• 35:45
  you can charge there that you couldn't charge if you are in a
• 35:48
  silo. But I just think this is a
• 35:50
  really interesting piece of the puzzle.
• 35:53
  I think this is going to be the hot topic.
• 35:55
  You know, we are in a six month window where you know, AI was
• 35:58
  very inexpensive, right? We were paying 20 bucks per
• 36:00
  employee or discounted on maybe an enterprise plan.
• 36:02
  And you know his joke, like if if the average employee pick
• 36:05
  round numbers, you know, 1020 thousand a month, just using a
• 36:07
  ballpark, you know, examples and then to give them $20.00 of
• 36:10
  intelligence. We all knew that was very
• 36:13
  undervalued for what we were seeing, at least if it was being
• 36:16
  used COD code and cursor showed you when AI actually creates
• 36:20
  value and does and increases productivity dramatically by
• 36:23
  doing work, you will pay far more for it.
• 36:25
  And with very little friction on that.
• 36:26
  I don't, I still don't think CE OS are pushing heavily back on
• 36:31
  that. They're concerned they're
• 36:32
  consuming budget way faster, but I don't think they're willing to
• 36:35
  say, you know what, I think that was a neat experiment.
• 36:37
  Let's go back and the second, and this will get into the
• 36:41
  trend. We can all just use less smart
• 36:44
  AI if we want. I mean, we can make this very
• 36:46
  inexpensive and have a high school or do your work for you
• 36:49
  instead of a PhD. And I kind of kid when I say
• 36:51
  that, but it's like, boy, to use the absolute best AI on these
• 36:55
  things and know that we're still, I don't know, I mean,
• 36:57
  what's your average per? And maybe I'll use general
• 37:00
  numbers. Let's say your average per
• 37:01
  employee went from 20 bucks a month to even 500 or 250 or 500
• 37:06
  if you averaged it across your team.
• 37:07
  That's about where we are. Think about how small that is.
• 37:10
  I mean, could you pay anybody on this planet to do this kind of
• 37:13
  work for 500 bucks a month and what time it would take?
• 37:15
  I think that we're kidding ourselves when we think it's
• 37:17
  expensive. I do think there is a limit and
• 37:20
  there's going to be a huge focus on efficiencies and new ways to
• 37:23
  do pricing. So I, I hear you on that.
• 37:25
  And that's something we'll be thinking about.
• 37:27
  But I think we're still in an era that if it's used
• 37:28
  thoughtfully. So you're going to see heavier
• 37:30
  inspection, heavier accountability on ROI, which
• 37:33
  would be very easy. Even just ask, I mean, I could
• 37:35
  just ask adapt for your account, build the ROI case study and
• 37:39
  really help to make sure Jeremiah realizes the value
• 37:41
  we're creating and it'll have it in an hour and that.
• 37:46
  I'm not. I'm not questioning the value.
• 37:48
  There's a reason we're spending four times as much as I
• 37:49
  initially budgeted as value. But actually one of the things I
• 37:53
  think it's really interesting, like when in the things that
• 37:54
  we're building for our customers, I'm thinking about
• 37:57
  how where we sit, we can actually help reduce their token
• 38:00
  cost and clot or whatever they're going to use to connect
• 38:02
  to this by being smarter with the way we pull the information
• 38:06
  for them and that kind of stuff. And I, I think if you're the
• 38:08
  brain, you actually have a massive ability there to where
• 38:10
  like overtime, there's probably a world in which you can
• 38:13
  actually deliver better outcomes for less tokens than you then
• 38:18
  you would be able to get with just connecting Claude or
• 38:20
  whatever directly into a system because you actually have more
• 38:23
  context and more ability to that's.
• 38:25
  Exactly right. To tune those the the inputs to
• 38:29
  get the right outputs. So I, that's, that's how I think
• 38:31
  about what I'm hoping that ends up becoming ultimately, but I
• 38:34
  don't know if that's part of how you're seeing it too.
• 38:36
  It's exactly right that as you start to have all that context
• 38:38
  and restoring, you know, this context and doing things with
• 38:41
  it, we don't have to do all these tool calls every single
• 38:43
  time. I mean, there's a different way
• 38:44
  to pull this context and share that in general, it's an ROI
• 38:47
  game. How much value are we creating?
• 38:49
  You know, that we can tune these things, right?
• 38:50
  I mean, it's all a tuning game of how much how much of the good
• 38:53
  stuff to put in. But I think that most people are
• 38:55
  pushing us towards keep it going like and we pride ourselves.
• 38:58
  We always ourselves by saying we want to have the single best
• 39:01
  answer, like we won't price optimize right now.
• 39:03
  We don't even give you an option to say use the dumb model.
• 39:06
  No, we want to actually give you the single best models we can
• 39:09
  find. Now there's there's work you can
• 39:10
  do on on on tuning this, but I think the world still is on his
• 39:14
  own of actually give me the best answer possible for this.
• 39:17
  And then help me maybe understand if there's use cases
• 39:19
  that we could maybe not use AI as aggressively on.
• 39:22
  But I think we're still in the zone of lean in and unlock and
• 39:26
  accelerate how people achieve their missions because it's just
• 39:29
  it's been too slow and we're in a massive productivity
• 39:32
  acceleration and most CEOs I talked to don't want to slow it
• 39:35
  down. And I would also say the best
• 39:37
  still isn't good enough actually in a lot of cases.
• 39:39
  So may as well just keep pushing that until you get to the point
• 39:42
  where it is good enough and then figure out how do you make it
• 39:45
  more efficient, more cost effective, whatever that is.
• 39:48
  There are people using code code for free right now because clock
• 39:51
  code leaked their entire thing online.
• 39:53
  And there's now like a repo that's like super popular of
• 39:56
  people using clock code for free.
• 39:57
  And then there's all the Chinese models.
• 39:58
  And these things are becoming so cheap so rapidly.
• 40:02
  There's going to be people, you know, there's no coercion.
• 40:04
  They're choosing to use the very best models, always up to date
• 40:08
  because they want the best result.
• 40:09
  But man, like the AI we're using now is going to feel like the AI
• 40:13
  that was available in like November.
• 40:15
  Last year in just a few months and we're not going to want to
• 40:17
  use it. You know, we're blown away by it
• 40:19
  now, but like in a couple months time we're going to be like, I
• 40:21
  can't imagine using anything apart from mythos.
• 40:22
  All right, I'm only going to use Mythos from now on, right?
• 40:25
  I mean, so I don't know. Someone put you on Sonnet or put
• 40:28
  you on a, you know, 5.4 when you knew that there was this magical
• 40:32
  thing that literally cost what, 100 bucks more a month for?
• 40:34
  I mean, when you actually think about how much we spend in these
• 40:37
  companies, I don't know if this actually is that big, especially
• 40:40
  if you look at the productivity gain.
• 40:41
  They'll be areas that need to be more efficient.
• 40:43
  And this will be very easy for the industry to solve.
• 40:45
  It'll just start to build more audits and actually, we'll just
• 40:49
  use AI to solve it. Hey, adapt.
• 40:50
  Is this a good use? Is this a good ROI positive
• 40:53
  query? How would you think about this?
• 40:55
  And there's a lot of ways to just use AI to manage AI.
• 40:59
  One of the things that we spoke about earlier was driving
• 41:01
  adoption in teams or even people, you know, outside.
• 41:04
  One of the awesome things that adapters doing is bringing
• 41:07
  people who are not AI native could be AI resistant for
• 41:09
  whatever reason. This, you know, thousands of
• 41:11
  reasons, but making it so that they can feel what we all felt
• 41:15
  when I'm not sure what tool it was for you.
• 41:17
  I feel like the tool changes fairly often for me, but right
• 41:20
  now it's just called Code and Terminal.
• 41:21
  But like, first it was Codex. And it's this amazing feeling
• 41:24
  when you're like, OK, all these complicated things.
• 41:25
  I used to have different specialists do the sequence of
• 41:28
  baton passes and it would take a week or longer to get done.
• 41:31
  Suddenly I can get done every day in the background and not
• 41:34
  think about them anymore. How incredible was that?
• 41:36
  I mean, yeah, I wonder what you guys think about gamification
• 41:40
  and bringing that experience to your teams.
• 41:43
  I've heard some people talk about like token maxing right at
• 41:45
  their teams where they're saying, hey, use as much tokens
• 41:47
  as possible. Yeah.
• 41:48
  How do you guys think about? That one of the use cases that I
• 41:51
  think just brings a lot of joy to people is if you connect to
• 41:53
  all the tools you use. So let's say you use a HubSpot
• 41:55
  or Linear, all these, all these different platforms using we
• 41:58
  have a, we have a product called adapt apps, which is like a
• 42:01
  cursor cloud code type experience.
• 42:02
  But when you let just like we have an AE on the team that
• 42:06
  decided to just a natural language build a new type of way
• 42:09
  to manage his accounts when he gets on a call.
• 42:11
  So instead of logging into HubSpot, which we don't want to
• 42:13
  vibe code HubSpot, that that would not be a good use of time.
• 42:15
  I wouldn't. I don't think any systems of
• 42:17
  records should be vibe coded right now.
• 42:18
  But to add a new UX layer that is very visual, that has trend
• 42:21
  charts of usage, that has the building data from Stripe, that
• 42:24
  has the usage data from Big Query, so we can see who's using
• 42:27
  it and is like a really full functional app and then has
• 42:30
  adapt intelligence of like signals.
• 42:33
  We never log into HubSpot. It writes back.
• 42:35
  And that's the example where Jack, I think that when people
• 42:37
  start to build their first apps, they have this like huge smile.
• 42:41
  They never thought they could do this.
• 42:42
  They in the past, they'd have to have an engineering team working
• 42:44
  with them. And then when they can share it,
• 42:46
  which is what adopts about it's team powered AI.
• 42:48
  This isn't the this isn't like a clod coworker.
• 42:50
  You're just very siloed. You share it.
• 42:53
  So then someone else uses the app to do their work or edits
• 42:55
  it. It's a pretty insane experience
• 42:58
  of just how it changes how you work.
• 43:00
  You basically have the most perfect UX for any situation you
• 43:04
  want. We have ATV on the wall like a
• 43:05
  frame TV in the office. That's just an adapt app that
• 43:08
  visualizes all of our usage in a funnel flow.
• 43:11
  I mean literally in the last 24 hours all the messages,
• 43:13
  connections, users, bubbles are floating, it makes noises and
• 43:16
  it's just someone built an adapt app and said this would be a
• 43:19
  more fun way to manage our accounts.
• 43:21
  Yeah, I've started using those just to build, to prototype
• 43:24
  things for customers. I've got the information I need
• 43:26
  connected to be able to pull their information and build
• 43:29
  these things out. And, and I think hopefully this
• 43:33
  comes for you at some point, like actually being able to
• 43:34
  share this externally would be cool.
• 43:35
  But even for now, just being able to take screenshots and say
• 43:38
  like, Hey, what do you think about this?
• 43:39
  It's something I can just do from Slack over the weekends.
• 43:42
  I'll literally like, hey, I don't want to log into adapt at
• 43:45
  all. I'll just ask you to take a
• 43:46
  screenshot and send it to me. So adapt is literally taking a
• 43:49
  screenshot of the app that it's building.
• 43:50
  And then I'll look at him like, OK, cool.
• 43:51
  Like edit these things. Well, what it's become for me
• 43:54
  because we actually got started with adapt around the same time
• 43:57
  that all the open class stuff was really going viral.
• 44:00
  And I actually started playing around the open claw and I was
• 44:03
  like, wait a minute. And this thing's actually better
• 44:05
  for me because it's embedded into the business and in a way
• 44:08
  that I would never be comfortable trying to embed open
• 44:10
  claw because of the the risks of that.
• 44:13
  And it's, I don't think it's there.
• 44:15
  Like there's, it doesn't have the same level of flexibility,
• 44:17
  but I actually don't want that. I want a little bit more
• 44:19
  control. I want things to be done in such
• 44:21
  a way that is shareable across the team and all that kind of
• 44:23
  stuff. And and so it doesn't solve all
• 44:25
  the same problems, but I do kind of see to set this brain concept
• 44:29
  that set or computer, however you want to describe it, that's
• 44:31
  some type of your business. It definitely that is the future
• 44:33
  as far as I'm concerned. So for me, it actually, I
• 44:35
  actually stopped, I threw away the whole idea of using open
• 44:38
  cloud because it's actually not that useful for me in a business
• 44:40
  context and just that for me. Jim, just one closing questions
• 44:44
  before we wrap here. If I'm trying to figure out what
• 44:47
  is the thing that I need to do in order to get my organization
• 44:50
  to become more AI native like not not really tool based, but
• 44:54
  more culture shift, right, Because you guys are providing a
• 44:57
  tool that can help and but there's a there's a big other
• 45:01
  part, which is just to change management part, right.
• 45:03
  What is your top one or two things that you would suggest to
• 45:06
  like a CEO or a CIO, Whoever is responsible for this in there is
• 45:11
  usually the CEO is responsible for this.
• 45:12
  Like what is the thing that you are telling them?
• 45:14
  Like, hey, I know you're like, you feel like you're banging
• 45:17
  your head against the wall trying to get your team to be AI
• 45:19
  native. Here's like the top two things
• 45:21
  that we see across all the companies we work with.
• 45:23
  It's. An interesting, I'm thinking
• 45:25
  throughout the answer that thoughtfully, because when I
• 45:27
  hear that, I think like AI empowered, which is, oh, we want
• 45:30
  our, you know, if we don't talk about the tool, then what you
• 45:32
  are talking about is I just want people to use more AI to augment
• 45:35
  their thinking to maybe help them see it differently.
• 45:37
  But when it's all just done in silos and not connected, I'm not
• 45:41
  it's hard to use the word AI native with that, because all
• 45:44
  that really is is I use an AI tool to to do things and like a
• 45:46
  weird, not weird, but just in a very isolated way.
• 45:49
  And I think sorry. I'm I'm saying like the choice.
• 45:51
  I mean, the choice of a tool like happens in the course of
• 45:54
  doing that. But at some point someone has to
• 45:57
  have the desire to want to work in this new way, right?
• 45:59
  But that's that's I guess what I'm talking about.
• 46:01
  Think that it starts at that somebody has to have the
• 46:04
  initiative. In our world, it usually starts
• 46:06
  with, you know, VPS or CEO. I'll give you an example.
• 46:08
  Let's say you created a skill in Adapt that was like the most
• 46:12
  perfect way that you like to connect with people and build
• 46:14
  relationships for your EA. So you save the skill and then
• 46:17
  your EA starts. You said, oh, by the way, when
• 46:19
  you when every time I have a meeting, can you just run that
• 46:21
  skill or just even ask adapt like how I think about this and
• 46:24
  it does it. You've now just made this person
• 46:26
  far more AI native. You've codified a way of
• 46:29
  thinking and taught them that they probably could codify a lot
• 46:32
  of their thinking. So if they hire a second EA or
• 46:34
  expand the team, it goes. And so I guess it comes down to
• 46:37
  how do you create these magical moments that others see that
• 46:41
  expands it. And maybe the last point of
• 46:43
  Slack is a wonderful way we use we use a concept of being
• 46:46
  instantly a native because at Jeremiah mentioned he he took
• 46:49
  the time to connect, you know, AP is into his account, but it
• 46:52
  was done at the organization level.
• 46:54
  So as his team jumped into slack, all they had to do.
• 46:56
  And he just probably sent a message to say, ask adapt what
• 46:59
  it thinks, say adapt. How would you do this or adapt?
• 47:01
  This customer has this problem. What should we do?
• 47:04
  And suddenly they had an aha moment that everyone can see in
• 47:07
  a team powered AI. And so I think it's about the
• 47:10
  reason why I push a little bit is without the connection to
• 47:12
  tools, we're just in a little bit of like AI, consumer AI in
• 47:16
  the business world, which we've seen in past iterations.
• 47:19
  But when you connect it to the actual work we do and how we do
• 47:21
  it, it's like, it's like an experience that no one's had and
• 47:24
  that you couldn't ever imagine not having.
• 47:27
  So like if someone said, you know what, tomorrow we're going
• 47:28
  to turn off this connected brain experience and you're just going
• 47:31
  to have your team in Slack and your team by itself doing the
• 47:34
  work. It would feel like turning the
• 47:36
  Wi-Fi off. You still have your laptops.
• 47:37
  We're all together, but we're really like Hanford, like 90%
• 47:41
  down. I think that's what it connected
• 47:44
  intelligence feels like when it's connected to tools.
• 47:47
  And it's very different than everybody having a ChatGPT
• 47:49
  license where if that went down for the day, I think most people
• 47:51
  are fine doing their job for the day.
• 47:52
  It's painful, but they, they would, you know, the work would
• 47:55
  go on because at the end of the day, they were doing the work
• 47:57
  and they were simply asking another tool to whisper to them
• 48:00
  a better version of the e-mail or to create something that they
• 48:03
  then as middleware, like a human middleware would go add to other
• 48:07
  systems. And that's what we're
• 48:08
  fundamentally changing. We're getting rid of the human
• 48:10
  middleware and just letting the humans do the part they're so
• 48:12
  good at, like the EQ thing that you mentioned.
• 48:15
  How many people do you guys know that are passionate about Google
• 48:17
  Docs or Gmail sending emails? None right?
• 48:21
  Demand drive supply. I felt like you got to like ask
• 48:23
  for it right from the team. Right.
• 48:26
  Yeah, I got to jump here too. But Jim, can you just kind of
• 48:29
  give everybody like a little last thing on ADAPT and how they
• 48:33
  can find you and where to go if they're interested in it?
• 48:36
  Yeah. So adapt.com company brain
• 48:40
  powered by the Adapt AI computer and you can now just go to
• 48:42
  adapt.com, sign up and if you use a business domain, you get
• 48:46
  $300.00 of credits. Our team will reach out as well
• 48:48
  and we will help make your company AI native.
• 48:51
  Yeah, awesome. And so when you found us here
• 48:53
  too, because I think it'd be fun to to see if anybody decides
• 48:56
  that they're going to go use adapt, Yeah.
• 48:58
  We're going to set up a code or something of that that's.
• 49:00
  Great. Yeah, that's fun, Jim.
• 49:03
  This was great. I love hearing these stories.
• 49:06
  You're just you're out there doing it and helping lots of
• 49:09
  teams become AI native.