Latest / 1 to 100 / E55: AI Native Teams with Jacob Posel from HQ

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E55: AI Native Teams with Jacob Posel from HQ · 1 to 100

0:00
Messaging with Jack with course like that happened.
0:01
You know, I like, I went out, I went out one night and I've left
0:07
my backpack at someone's house. A friend of mine called Jack.
0:11
And then I woke up the next morning super hungover and I was
0:13
like, shit, my backpacks in at my friend's house called Jack.
0:17
So I text him and I was like yo like I need to pick up my
0:20
backpack and he wasn't answering me.
0:22
So I like call him he like wasn't answering.
0:23
So I end up like calling his girlfriend and then getting my
0:25
backpack. And then like 3 hours later Jack
0:28
sends me a video of a baby like a little baby.
0:30
And I was like I was like what the fuck?
0:32
Like why is he sending me? Like why is my friend sending me
0:35
a video of a baby? And then I like I just didn't I
0:38
didn't understand at all. And Jack was like, I just had a
0:41
kid, so I'm showing you my baby. And I was like, OK, like I just
0:45
said like, OK, like I just didn't understand.
0:48
And then like, oh, like I think like a month later I go and I
0:52
actually go to fret message my friend Jack again.
0:55
And I realized that I had messaged the wrong Jack.
0:57
And I had messaged this Jack about his like real baby.
1:00
And I just felt terrible. He had like just had a child and
1:03
sent me a video. And my reaction was just like,
1:05
OK, like I guess I felt. I remember this exchange.
1:10
Yeah, I didn't. I didn't realize that you
1:11
thought you were messaging a different Jack.
1:13
That's fine. Yeah, anyway, so I'm so
1:15
embarrassed about that. Nah.
1:16
Don't be embarrassed, no hard FL.
1:18
Jacob, you're finally building SAS for everyone for.
1:21
Everyone I am. For everyone.
1:23
Yeah, yeah, yeah. You don't have a small town
1:26
problem as they say. No, HQ fortunately works for
1:29
everyone, for every type of business, which is really nice.
1:31
Yeah, Tell. Tell us about it cuz I I so I
1:33
I've learned not that much, but I didn't realize you were I
1:37
thought this was just you building it.
1:38
I didn't realize you had to partners in this as well or I I
1:41
don't even know that structure. But anyway, I'd love to learn
1:43
more about all of it the. Story is actually pretty cool
1:45
about how I, how I got, how I like joined and got involved
1:48
with the team. So I met Corey, Corey Epstein
1:51
about a year ago actually in I was in Richard's office and we
1:56
had a call and I remember it like vividly because I did, it
1:58
was like one of my first calls when I got to San Francisco.
2:00
I did it out in the hallway. Anyway, he like showed me this
2:03
product that he was building called Indigo and it was like
2:07
very ahead of its time, but it was like at a point where where
2:12
AI hadn't like quite caught up to what they wanted to build.
2:14
It was like this personal AI that lives on top of your
2:16
computer and just allows and just like it helps you do work
2:19
embedded directly into it was like it was very cool design
2:21
very well and I was pretty impressed.
2:23
But like they just AI hadn't caught up yet.
2:27
But like Corey was Corey's like a visionary.
2:29
He like, he's exceptionally smart and good at understanding
2:33
where AI goes, where AI is going.
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And I could like tell that pretty early on.
2:38
Anyway, him and I like went through Twitter, went back and
2:40
forth over the years. Eventually he reached out to me
2:42
and he was like, you should try a new product.
2:44
We'll try this new tool that we've built internally.
2:46
It was just started out as this internal tool called HQ, which
2:50
Corey runs live recover Voyage like and Indigo.
2:54
So he has to operate at a super high level of efficiency.
2:57
And so it was this tool that allowed him to use AI, use AI
3:00
more effectively. And anyway, he, he was, he on
3:03
boarded me onto it and I was like, holy shit, this is really
3:05
cool. Like I thought I was a good AI
3:07
user, but it made me so much more effective as like a
3:10
personal tool, right? It was like for me to be better
3:12
at AI and I was highly incentivized to help make this
3:15
product better because it was helping me in my work, in my
3:17
consulting work, I was working with multiple companies,
3:20
building things for them. And so I was incentivized to
3:22
help with the product. So I got pretty close to the
3:25
team, started working with them more directly.
3:27
I was consulting at the same time.
3:29
And the number one issue I was seeing across all these
3:30
businesses was it's just really hard to get team adoption of AI.
3:34
Like all these products are inherently designed to work
3:38
single use. Like there is some organization
3:40
sharing, but it's not robust and it's not a focus.
3:42
So everyone was just working in silos, everyone was quite,
3:46
everyone was just repeating work.
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People weren't kind of moving in the same direction, working in
3:50
the same place. And HQ at the same time was
3:53
building up all the context of my business.
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Like inherently the product what becomes better as you use it
3:57
more because it builds up context on how you work and how
4:01
you operate. So I pitched the team.
4:03
I was like, you guys should just build a version of HQ for
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multiple people for like a team version of HQ where you can,
4:10
where people can use it. It makes them better, more
4:11
effective, but you share these capabilities and solves a real
4:14
problem for the businesses. And they, they basically agreed
4:19
and asked if I wanted to ask if I wanted to join the company.
4:22
So I was like, yeah, I was like, I'm already, I really want this
4:25
to be better and I'm already going to be incentivized to make
4:27
this better. So I was like, yeah.
4:29
So at the same time, Ramp launched and internally like
4:33
we're an article about this internal product they built
4:35
called Glass. And that was really cool for
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that was really great for us because it validated it and the,
4:39
and like the market meaning like Twitter really liked it.
4:42
And so I tweeted like, we built Ramp Glass for everyone and I
4:47
just got insane demand. And so I've like pushed the
4:50
team. I was like less fucking like, we
4:51
have to, we have to get this to Mark, we have to push this out.
4:53
And we ended up building something really cool.
4:55
And then we launched it about two days ago.
4:59
And yeah, does that. I don't even remember what the
5:01
original question was but I just yapped about it for like 5
5:03
minutes. No, that was it.
5:04
Just wanted to get the context we had, yeah.
5:07
So wait, what do we do? I mean, I get the the general
5:10
idea that, you know, it doesn't it brings teams together to work
5:15
more collaboratively with AI. But like, was it?
5:18
Was it actually do? It's at its core a cloud based
5:21
file system that you interact with that you use when you use a
5:25
tool like Cloud Code or codecs or Open code or any kind of
5:28
agent harness. It syncs files to the cloud and
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helps you resolve conflicts. So it abstracts away Git level
5:35
complexity, GitHub level complexity for for knowledge
5:39
users. And then it has additional
5:41
features built on top to actually work for bigger
5:43
businesses. So it has access control built
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into the file system so you can control who sees what.
5:49
It has secret sharing because no skill like most skills interact
5:53
with external external services. So it has secure encrypted
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secret sharing. And then it also has app
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deployment, so easily deploy applications from directly
6:02
inside of HQ. It's really a super simple
6:04
level, super simple level, super simple thing like either go to
6:06
market team, they all have built their own separate junkie tools
6:10
for how they automate outbound like a super common problem.
6:14
This allows them to just create one all inside of HQ.
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They all interact with the same thing.
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Not only do we have do we know what they're interacting with?
6:21
But it gets better as they use it because they're all
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compounding on top of the same skills and knowledge systems.
6:25
So. Jacob, I mean, you and I know
6:27
each other, but people listening may not know that you and I know
6:30
each other. But when I first heard that you
6:31
were doing this, my thinking was you're finally working on
6:35
something that you should be working on.
6:36
Yeah. Which I won't go into all of the
6:38
reasons for that, but there was a series of other things that
6:42
you worked on which I did not think were a good use of your
6:45
time, which I have shared with you separately.
6:47
OK. Do you feel that way?
6:49
Yeah, I do. I think am I like calling or at
6:52
least where I get excited is getting people excited and
6:55
getting people using AI. And like I've always had this
6:57
tension of I felt like AI was super powerful and I was just,
7:01
and I always had such great experiences with it.
7:03
And not everyone has that. Not everyone gets up to speed.
7:05
And I feel like this really does, like it takes the zero to
7:08
1, but it also takes the one to 10 kind of thing.
7:11
So I feel excited about it. And I've had this like really
7:14
great experience where because I've been just like faffing
7:18
around with so many different types of businesses and business
7:20
models over the last two years, like SAS and agency and like
7:23
consumer and brands and stuff like that.
7:26
I feel like when I speak to people, I just have a really
7:28
good sense of where the value is for them and building with AI
7:31
can directly tell them this is where I think HQ is valuable for
7:34
you. And that's being that's been
7:35
quite nice. So it does feel like a good
7:37
product for me to work on and I'm super excited about it.
7:40
And also finally, I'm working with people with like really,
7:43
really smart cracked people, which is like really exciting to
7:47
me because like just working with it, like I'm like a like
7:50
not a good engineer. I'm like not a good engineer.
7:52
Like maybe I have a good product inside, but like I'm not a great
7:54
engineer. Now I'm working with great
7:55
engineers and that's just so it gives me so much energy because
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I don't have to focus on the things that I'm not great at.
8:01
Like I can just focus on what I'm great at and they and
8:04
everyone else in the team can focus on what they're great at.
8:06
So that's really nice. Yeah.
8:07
So there's a there's this thing that I wonder that we debate
8:10
forever on this pod about like SMB, mid market enterprise, what
8:14
could be like we have this conversation.
8:16
I don't know every is it fair to say every episode at this point?
8:19
It's. Going to be at least once a
8:20
month, right? Once or twice a month.
8:23
So roughly all the time. OK.
8:25
So, so, so I wonder as you're building it, where you think it
8:30
will have the most value over time, like in which segment of
8:34
the market and, and you, you don't need to share the segments
8:37
that you're currently working with, but you can share what
8:40
segments you're currently working with, what segments are
8:42
coming inbound. And I just, I just, or if you
8:44
don't want to, that's also fine. But I just wonder ultimately
8:47
what I'm curious about is where should the end state be?
8:50
And given where the end state should be, how does that
8:53
influence how you think about the go to market today?
8:55
And my and my push is basically when you post something on X,
9:00
you are only going to get one variety of those customers.
9:04
And I am wondering if that's who you want?
9:06
So in terms of who's come in, in terms of demo requests and in
9:10
the pipeline, we have very big businesses, like thousands of
9:13
employees. And we also have like 2 people
9:16
startups. So there's been a big from X,
9:19
Yeah, I'll share them with you afterwards.
9:21
But yeah, with yeah. No, no, don't share it here.
9:23
I'm so so. So you think that posting on X
9:25
can bring in enterprises? I mean, it did for me.
9:28
OK. I'm just built different.
9:30
I love that. No skill issue.
9:34
I mean, I guess I posted on LinkedIn and at the time we
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didn't have UTM tracking set up. So I don't know exactly where
9:40
they come in, but I think it's from Twitter.
9:41
But like I know from experience, like I have in the past gotten
9:45
enterprise inbound from Twitter, from a business that like we
9:48
both worked with. I think you probably know I'm
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talking about two others or three or four others, 2 from I
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think like Blodge yesterday really large businesses came in
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and I haven't even looked through like the rest.
10:01
But yeah, we definitely had enterprises and then like.
10:05
Part of it may be that your content is interesting to those
10:08
people, like the things that you talk about and post about in
10:10
terms of like AI uses and stuff. Like the big companies obviously
10:13
have these problems too, and they're trying to figure out how
10:15
to get adoption. So like, obviously those people
10:17
are there on those platforms and if you are speaking to the
10:20
things that they care about, you might be more likely to reach
10:22
them. I think it'll be interesting for
10:24
you like the, the stakeholders that come in haven't always been
10:27
executives though like some of them are.
10:29
I'm a head of AI, I'm leading AI enablement at this large
10:33
business. And so I'm interested in
10:35
learning more. And I feel like the persona of
10:37
that person at these businesses can now tend towards younger and
10:41
tend towards more online. So I think that makes sense.
10:46
I think those people coming in through Twitter definitely makes
10:50
sense. Who do you?
10:51
Want to serve with the product. So, so now, so now actually you
10:54
have the prototypical problem. So OK, so actually this makes
10:57
the question even harder, right? So like, because a lot of
11:00
businesses, they can only attract a certain type of
11:02
customer. And so then they just end up
11:04
saying, OK, if I attract this customer, I serve them.
11:06
But now you're saying I have everybody from 10s of thousands
11:09
of people to two people. And so now prioritization of
11:12
where you want to surf first becomes even more important.
11:16
And so how do you think, like forget you Jacob, the person.
11:19
Like the job is what is HQ's place in the world, right?
11:22
Like your job at HQ is to make sure HQ gets its place in the
11:25
world. So where where does where is
11:26
HQ's place in the world? I.
11:28
Don't know the answer. I don't know it exactly.
11:30
And that's the reason why we launched how we did kind of like
11:32
go through demo because I want, I want to have high touch in
11:36
rolling these out and see how they land.
11:38
But my intuition is that it works best for larger
11:40
enterprises, like a bigger business where a lean tech team
11:46
could build HQ, like a like a lean startup could build HQ or
11:50
their own version of HQ. Like obviously because we did
11:52
it, you know, like they could build it a super lean or even
11:56
like a relatively lean with a technical person could build it.
11:59
But, and they're already pretty strong AI users, like they could
12:02
figure out the issues that they could figure out ways to solve
12:07
the issues. Or at least they at this stage,
12:09
if they're, if they're early, if they're young, if they're small
12:11
and lean, then they're going to be AI 1st and AI forward.
12:15
I think the best company that would benefit the most from HQ
12:19
is you have a top down initiative.
12:21
We want to implement AI inside of our businesses.
12:24
And I'm just really struggling to get everyone using it.
12:27
Like I'm struggling to get the person who has been part of the
12:30
company for 10 years to fill some position that I don't know
12:33
that like I'm really startling to get this 40 year old member
12:37
of my like accounting team, a marketing team to use AI.
12:40
And I don't want to put them in the terminal.
12:41
I don't want them to, I don't them they don't even understand
12:44
what a CLI means, but I really want them.
12:46
But I see other people doing things that are so super
12:48
powerful and I want that for everyone else.
12:50
And I think that happens in a bigger business because kind of
12:54
by nature average skill level will tend towards the middle or
12:59
like decrease. So that's where my intuition
13:03
goes. Can I ask a question?
13:05
Yeah, I can't remember if this was in the video.
13:07
I feel like it was not. Does the tool also give you
13:11
reporting in terms of how people are using?
13:14
Yeah, I was about to ask this. It does.
13:16
And this is huge. It does.
13:18
And this is, I think this is really big, like being able to
13:20
see what people are working on, how much they're working on it,
13:23
like the token usage, stuff like that.
13:24
I think that's going to be really exciting for bigger
13:26
businesses. I don't even think you have to
13:27
be that big of a business to have this problem.
13:29
I mean, basically any business I think where people have been
13:31
doing something for an extended period of time in a specific way
13:34
and you have more than 10 people, I think this is actually
13:36
a problem. Did.
13:38
You have multiple levels between the person who's trying to
13:41
execute and implement AI and the person who's doing the work.
13:44
You have this problem. And so I think I think it's AI
13:46
don't know 1520 thirty people as being a problem.
13:50
So yeah, I. Mean, I just don't, I just don't
13:52
think those people are good customers, Jeremiah, like that's
13:55
you and me basically, right. You're describing you and me and
13:58
I just, I'm like thinking to myself like why would like like
14:02
it just feels like bad business for Jacob to spend his time
14:05
talking to you and me versus spending his time talking to
14:08
work day. Yeah.
14:09
Well, let's talk about the economics of it though, because
14:11
I think that's actually interesting, right.
14:12
Like I, I mean, Jacob, I just had, we had a guest on this
14:17
isn't out yet, but a company called Adapt.
14:18
So we're using something that's similar at least on the way
14:21
you're describing it at our company.
14:23
And it's a, it's a basically like the, the AI brain of our
14:29
business. And so it's a really interesting
14:31
concept. And I think it's a, it's a
14:34
conceptually very similar to what you're you're building.
14:36
But I'm finding us spending a massive amount of money on it
14:39
and based their model. We we paid them and they
14:44
basically run everything through a bunch of different models
14:46
depending on like what the task is.
14:48
It basically picks the right model.
14:49
So it's not, it's not just clawed in this context.
14:52
Yeah. So in that context though, I
14:55
don't know how their economics work, but I know that basically
14:57
there's like effectively like we're paying a, we're paying a
15:00
percentage of the token usage just that works out.
15:03
And so in that case, that's actually like quite lucrative I
15:07
would think for them, but I'm not sure how your model is.
15:09
So I'm curious what that that looks like.
15:11
Well, because we built on top of cloud code and codecs and
15:14
whatever you're using, we don't charge per token.
15:16
We don't charge for tokens. So like a customer I think costs
15:23
a dollar per month for us. So our goal, and this is like
15:29
something I think is worth discussing with you guys.
15:32
I just feel I feel like we live in a time right now where
15:35
there's like almost an arbitrage opportunity based on
15:39
distribution to get insane valuations or to get insane
15:44
opportunities based on distribution.
15:49
And I just want to land HQ in as many businesses as possible.
15:53
We are offering to charge for service.
15:56
So because we, we have this amazing, we have this like lens
16:00
into your business and we, it's like super powerful.
16:02
Like imagine I was working with you, Jeremiah, and you wanted
16:05
some skill across your business for some team to use.
16:08
Like if I'm part of your HQ, I can just push it in and everyone
16:10
else in your team can use it and I can teach them how to use it
16:12
or I can create a handoff skill or tutorial for them to use
16:15
right. So like I have a lot of access.
16:17
So we are offering service for an implementation which there's
16:21
been a fair amount of demand for, you know, like set it up
16:24
for us and teach and build some stuff for us.
16:26
But in terms of the actual like pricing, I just want to get it
16:29
in as many businesses as I can. I want as many people running
16:31
their businesses on top of HQ as possible.
16:34
And obviously like there's insane ways to monetize on top
16:36
of that. If like if you, if I'm the
16:38
primary interface for the ways that people are interacting with
16:41
AI, like well, I'm the, I'm the primary workspace or I'm one
16:43
level away from Claude or open AI and I'm the agnostic open
16:47
source provider to it. Then like I can sell, I can sell
16:51
or provide a lot of value on top of that.
16:53
What's wild to is it so one of the things I think about a lot
16:55
with this with any business built on top of token usage
16:59
effectively is that there's a in my business, I see a ton of
17:02
waste in the token usage because of the fact that like people are
17:05
doing the same things multiple times.
17:07
There's like, there's probably cheaper ways you could do the
17:09
same thing. There's all the, there's
17:10
different models, all this kind of stuff.
17:11
You could like, I am very certain that the things that
17:14
we're doing today could be done with a third, the number of
17:16
tokens if we actually knew what we were doing with that.
17:20
And so if you sit there and you have all that visibility, like I
17:23
actually think that will be a major business in the future is
17:25
how do we people coming in and saying, I'm going to help you
17:27
optimize your token usage, whatever that looks.
17:29
And I don't know if that's kind of what you're thinking about.
17:32
But I just think there's so much opportunity in that context of
17:36
if you are in all these businesses and somebody's
17:38
spending $10,000 a month on token usage and you can get them
17:41
to cut that in half, they're going to well while delivering
17:44
the same amount of value there. There's a opportunity for you in
17:47
that. Context yeah, and incentives are
17:48
aligned here. Like if you're using a provider
17:51
like adapter, whatever, where they charge per token, like they
17:54
may say that they're going to optimize your tokens, they may
17:56
say they're routing you through a lot like small models, but
17:59
incentives inherently are not aligned.
18:01
Like they want you to do more and you want to do you want to
18:04
use less. But our incentives are the same.
18:06
Like we use HQ, we use inside of our code, code and codec
18:08
subscriptions. We rolled out a skill called
18:10
Caveman Bro, which we found on X that reduces the number of
18:13
tokens because we want to save money because we're all blowing
18:17
through our subscriptions because we're also like because
18:19
we're also efficient now, you know, so it's just different.
18:21
So building on top of those things and working in the same
18:23
way that you guys do, it just changes the economics
18:25
significantly. Yeah, I like this distribution
18:27
play. I think it's great.
18:28
I think it's really strong. One of the things I wonder, and
18:31
this is I guess more of a product based question with
18:33
teams in AI no longer being solo.
18:36
You know, we talked about one of the problems of solving that.
18:38
Everyone is working on the same thing over and over again.
18:40
The work is getting redone let's say by the sales reps doing
18:43
their outreach thing. Your sales reps are all building
18:45
separate outreach methods that could consolidate into one
18:48
skill. But then I guess, and I just
18:51
want to battle test this one example, you lose the
18:53
personalization like I'm sure every organization has seen
18:56
their sales reps say, I actually don't want to do what the other
18:59
sales reps are doing. I don't believe in what they're
19:01
doing. And a small amount of variation
19:03
like that's getting standardized in like let's say at skill would
19:06
actually straight right. And you, you decrease your
19:09
exposure to people who do incredible net new work, right?
19:14
Like one of the things that I've done pretty recently that I
19:16
think is a pretty nifty is I managed to get my Mac mini to
19:20
hand write emails like a total perfect human simulation using
19:24
Gmail for my cold outbound as opposed to something like
19:26
instantly, right? So then it's just sending actual
19:30
emails as if it was a real user. I like that.
19:32
I think it's, I don't know if it actually does that much versus
19:35
sending e-mail via the API, but I like it.
19:38
Like there's something there that feels good to me, as if it
19:40
might have some benefit if I had to, I guess, comply with the way
19:46
that the rest of the team were doing outbound.
19:48
I might, like, find that frustrating.
19:49
And then the team at the whole might lose the ability to do
19:52
things, you know, individually, right, differently depending on
19:55
the preferences of the user. Yeah.
19:57
I just, yeah, would love to hear your thoughts on that.
19:59
Like, is there ability to fork off and say, actually, yeah, I
20:03
want to use these other people's skills.
20:04
I want to do my own thing here and build something net new,
20:06
completely different and not be a team, actually be a solo
20:09
builder. There is so like HQ has a
20:11
personal, there's like a personal version of it and a
20:13
company version of it. And not you're not locked into
20:15
the company cloud. Like I don't have to push
20:18
everything I work to the cloud. I don't have to pull everything
20:20
I work from the cloud. I can have personal things that
20:22
I don't share with the rest of the team.
20:24
So yes, like the capabilities 100% there and my HQ could
20:27
become personalized and I could say I want to use this version
20:29
of the skill, but I want to put my own twist on it.
20:31
But I would also challenge the premise of the question.
20:33
Like if one SDR is doing something better than the rest
20:36
of the team, then surely as like a head of sales, I should just,
20:40
that should become the default way that the team works.
20:43
And like, yes, maybe like, but yes, I can also roll this
20:46
personalization into that process or like a little bit of
20:49
a little bit of flexibility on top of that.
20:51
But like, I just think that if like if I have a team skill and
20:55
one SDR is doing something that's better, then it should
20:58
like that should just become the team skill.
20:59
So like in that example, yeah, percent.
21:03
There's chicken and egg, right? Everyone's standardized and
21:05
you've gone in a direction that is becoming concretized.
21:08
Like, how do you how do you fork out and say, I can imagine in a
21:11
sales team, you know, small sales teams, just like people
21:14
forget big sales teams, People just getting constantly
21:16
frustrated at what other people have built.
21:18
And they're like, Nah, I want to do things my own way, right?
21:19
The way that Dan is doing it is really stupid.
21:22
Like, you know, yeah, the metrics look good on a one week,
21:24
but what will they look like on a month, right?
21:27
When they're statistically significant, they'll have a
21:29
bunch of, you know, explanations for why what Dan is doing and is
21:31
the prevailing skill right now is is is not what they want to
21:35
do, right? And if the Commission
21:36
incentivize, they should have, I guess, the freedom to do that
21:38
right, to fork off. I mean, I think this is like a
21:42
short term problem. Like let's just take the sales
21:44
example in in in like in an ideal world, you wouldn't have
21:49
random humans doing what they think is best in some competing
21:52
way. Like you just will have criteria
21:54
for what is correct. You'll build skills around that
21:57
or you'll build capabilities around that.
21:58
Maybe you have one person operating at far more efficiency
22:03
and they can basically eat the rest of the team.
22:05
Like there's no bottleneck in output.
22:07
And with AI, like if I have 5 sales reps and I have one person
22:10
that's consistently outperforming, then they should
22:13
do all the outbound or I could build agents on top of it.
22:15
And that's the product direction that we want to go into HQ in
22:17
the future is like, you've built this company workspace, let's
22:20
now deploy agents on top of that knowledge base and skill base.
22:23
And I think like that would be an ideal direction.
22:25
But like to answer the main core of the question, it is, it is
22:30
customizable, It is personalizable.
22:32
And I think the way that you manage what is at a company
22:34
level versus a personal level is like a matter of preference of
22:37
the executive or the leader or the CEO.
22:41
Cool. It sounds great.
22:42
It sounds like a great product. Time, who do you think is the
22:44
best buyer of this product inside the company?
22:47
So you, you, you actually, or maybe this is a question we
22:50
should ask you in six months. But I, I'm just curious, like
22:53
what is the title of the person who you think would buy this?
22:57
To in my experience so far, it's the CEO.
23:00
It's like it's whoever has the most incentive to enable AI in
23:03
their business. So it's the CEO has been a lot
23:06
of the, a lot of the inbound because like they're putting all
23:10
the pressure down onto into under the AI rollout or for
23:13
larger businesses, there's this like head of AI enablement role,
23:16
which is recently popped up that I've seen coming up more and
23:19
more. And they are responsible for AI
23:21
rollouts. And so they are they're the one
23:24
buying it. But the way that we've been
23:26
landing it is like we'll land it with your strongest power user
23:29
and then distributor outwards from there.
23:31
So honestly, that's like usually the CEO and like, I'm curious
23:35
why you think that is the case that in so many businesses the
23:38
CEO I. Don't think it's you think is it
23:40
the CEO or is it the founder? Founder.
23:41
Sorry, why the founder? I guess now I've just answered
23:44
by reframing at that answer. Yeah, that makes sense.
23:48
That makes sense. I mean, OK, you don't think it's
23:50
CEO as well like for sure. I think the you don't think
23:54
that's true of CEO's like takeover businesses?
23:56
No, I I think depends. I think there's a small minority
24:00
of CEO's who have the mindset that it takes to do to do this.
24:08
The average, like the average CEO is an optimizer, not a
24:11
transformer. And the average founder is a
24:14
transformer and not an optimizer actually.
24:16
And so you find like founder CEOs have to augment themselves
24:19
with optimizers and like vice versa, right?
24:23
Like that's a that's a very common or like systems builders.
24:26
And I think that I think that the reason the founder is the
24:29
most active user of AI is because they're happy to go back
24:34
to a team of one or two. Yeah.
24:37
And that's what they're doing with AI.
24:38
Like, you know, like I've always been pretty impressed with Corey
24:44
at Jones Rd. but recently, much more, so much more.
24:49
So there's Cody. Cody, It's Cody.
24:52
Sorry, it's. Because I said Corey.
24:54
It's yeah, you said Corey because of Corey, I've seen and
24:56
now I'm like getting confused, but sorry Cody at Jones.
25:00
OK, so recently I've been very impressed with Cody, much more
25:04
so than than I've been in the past, because I think he's like
25:08
decided to go found Concord founder mode on a bunch of
25:11
things. And I'm like seeing him do
25:14
things. I'm like, dude, other people are
25:16
not going to do this. They're just not.
25:20
And, and it's, it's like so evident because he'll, the way
25:24
it's evident is he'll post something and the responses from
25:29
people is, can you share that? And that is the tell.
25:32
The tell is they want someone else to do the work and hand it
25:35
to them. Have you ever seen Cody's taking
25:36
sure that like Cody is just doing it himself?
25:38
The and that that is, that's the, that's the tell.
25:41
The tell is like, no, I don't see in the comments someone
25:44
asking like, dude, what in like, what was the first step you took
25:48
that got you on the journey to being able to do these things on
25:51
your own? If someone asks that question,
25:53
that would be like, OK, this is actually someone who is likely
25:56
to end up in the same spot as Cody, but that's not what people
25:58
are asking. And so I, I just, I just think
26:01
that like, yeah, I don't think, I don't think the average CEO is
26:03
going to do it. I think the total number of like
26:06
force of will that's required is just monumental.
26:09
Interesting thing there as well as that's not a technical
26:11
barrier. There's no technical barrier to
26:13
entry. There was in the past, but this
26:15
is the one thing where there isn't a technical barrier to
26:17
entry and you could just get stuck in this.
26:19
I've seen Cody's tweets as well. And yeah, you see people in the
26:23
comments saying, hey, can you basically hand this to me?
26:24
And he is looking to hand it to someone.
26:27
He wants to hand it off to someone, and that person's going
26:29
to have a job role. And I actually think that job
26:31
roles are very similar to the person that's in the comments
26:33
saying, can you hand it to me? Because they're given a title of
26:36
a thing that they do, and then they're given a system that they
26:38
have to follow and repeat that's set by someone, right?
26:41
Either by standards of the industry or by the, you know,
26:43
the CEO, the founder. And then they've got to go and
26:45
do that thing. And what you might find with
26:47
employees in certain organizations is an
26:49
unwillingness to adapt, to update their methods.
26:51
So take like, I guess the typical example of someone who
26:54
might be at Jones Roe beauty with Cody, someone who sends
26:56
e-mail in Cladio, right? That person has a system that
27:00
they've been going through for weeks and weeks and months and
27:02
months and years and years. And it could actually be really
27:05
hard to make them AI native. Same thing with I imagine they
27:08
weren't building all their landing pages with the CEO in
27:10
the past, right? But now they are, right?
27:12
So who was doing it before they have their processes.
27:15
Maybe they were using Rappler, maybe they were natively in in
27:17
Shopify. But now he's creating this new
27:19
role, he's shaping out what it's going to look like, and
27:22
someone's going to go in on train tracks and do the thing
27:24
that Cody trailblazed, right? I think in a lot of ways this
27:28
might be the reason for is the person that does it is because
27:31
they have that high agency to just go and get the thing done
27:33
right. Even without a technical Barrett
27:35
entry, that's just prompting. Jack that can I push back?
27:38
I think that's a massive mistake.
27:40
If, if, if what ends up happening is he hires someone to
27:43
go do that thing. I don't, I know, I don't know
27:46
that that's what he's doing. But if that's what he ends up
27:48
doing, the reason it's a mistake is that that thing that he built
27:52
today is going to be different in three months.
27:54
And this is actually what separates Cody from everybody in
27:57
the comments. What separates Cody from
27:59
everybody in the comments is that what he was doing 3 months
28:01
ago is different than what he is doing today.
28:03
Right. And actually, he chose to
28:05
continuously update what he's doing.
28:08
And that's exactly why you cannot be handed something
28:10
because the, this is, we are not settled.
28:13
Like AI is not a settled technology.
28:15
Like cloud is a settled technology.
28:17
AI is not a settled technology. So the, the, the, the you have
28:20
to be, you have to like, not hand someone something to say
28:23
like, here's how you have to think.
28:24
Are you going to get on the treadmill and keep running?
28:27
You can't say like, hey, this thing is done and hand it to
28:29
someone. And that shift in mentality is
28:31
exactly the problem. And I think that's why I Jake up
28:34
to your point on like the CEO versus the founder of like who
28:38
is the adopter of issue HQ by by the way, HQ also nothing static
28:43
about the output. You build a skill, you push it
28:45
back up to the parent organization how or a parent
28:49
organization it can. You can choose how, how, how
28:51
many hierarchies you want and in the parent and and and and the
28:54
permissions. But but the point is actually
28:57
that it is by definition evolving and it is a learning
29:00
system and, and most people want to be told, here's how you use
29:05
the tool. Now operate the tool.
29:06
And that's literally exactly not true.
29:09
And and that's why the the person who's going to be most
29:12
likely to buy as a founder and or is someone in the
29:14
organization who has that mentality, but they're super
29:17
hard to identify outside in super hard.
29:21
Yeah. Does that mean in your minds
29:22
that most people, while I agree with you that like this
29:26
technology is not finished, like it probably won't be for years,
29:30
right, In terms of like what the final form is?
29:32
So in your mind, does that mean that most people are going to be
29:34
perpetually behind until we get to some sort of steady states if
29:38
that ever happens? I don't even know what that
29:39
looks like years from now, but because like what I'm thinking
29:43
about here is somebody could go and enable HQ, but unless
29:47
everybody in the org is actively working on improving it, all
29:51
right, you don't need everybody, but there has to be a driver of
29:54
that. Otherwise it's going to stagnate
29:55
as well, correct? The single you, if I were a
29:59
salesperson at HQ, you know how I would sell it.
30:01
Madam or Mr. Founder, you have a distribution of talent on your
30:05
team today in terms of how AI forward and AI native they are.
30:09
And you're sitting to yourselves and your only tool is fire the
30:12
people who are not AI native and promote the people who are.
30:15
That's the that's the only like choice you have today.
30:18
What if I gave you a tool that took your top users and
30:21
automatically propagated what the skills are to the rest of
30:24
the organization? You can still do that sort, but
30:27
at least now you have a second lever to take the distribution
30:30
of talent on your team and through a tool, force the issue
30:34
on at least some larger portion of your organization.
30:38
That's how I would sell it and I would sell it as an
30:40
organizational issue and not not a product issue.
30:44
Our tagline is one person's breakthrough becomes everyone's
30:46
baseline, which is what you're saying, right?
30:49
Like you, you distribute down the capability.
30:52
Yeah. My suggestion is that you
30:53
directly provoke the question that they're already interacting
30:55
with, which is like what portion of my team do I have to fire?
30:58
Because it's not a mistake that Coinbase and like these
31:01
massively profitable companies, why do you think they're firing
31:03
people? It's not to save money.
31:05
I mean, like no one in their right mind thinks it's to save
31:08
money, right? I mean, can I assume we agree
31:11
that it's not to save money? Right.
31:13
Despite the impact on the stock price, I think that Brian
31:15
Armstrong articulated it really well, exactly why they're doing
31:18
it. Actually, I think Dorsey as well
31:20
did the same thing that they're describing.
31:22
It's not just to save money, right?
31:24
Why is it tell me I missed the Coinbase?
31:26
It's a fundamental restructuring.
31:28
They're like fundamentally restructuring everyone's roles
31:31
basically to have a different expectation from people.
31:33
And Coinbase been doing it for a long time.
31:34
They're the reason I first started using Cursor.
31:38
They've been at it since like early 2025, but they're they're
31:41
cutting now and it looks like they're changing the expectation
31:45
for every single employee of the business.
31:46
That might be a little bit too much of an absolute, but like
31:48
for a lot of people, right? Just can't stand crypto.
31:51
I stay. I try to stay away from all the
31:53
Coinbase. OK, fine.
31:54
I'm kidding. What?
31:55
I'm kidding, dude. I'm kidding.
31:56
I'm kidding. I'm kidding.
31:57
OK, whatever. Cloudflare.
31:58
OK, Cloudflare yesterday did a 20% layoff.
32:01
You know what I mean? Why do you think Cloudflare did
32:02
a 20% layoff? Do these people are printing
32:04
money right now? They're printing money.
32:06
So like the premises, if they could, if they could have N + 1
32:11
AI enabled employees and they would choose to keep them and
32:13
this allows them to do that, but they just can't.
32:15
They can't get that get that cohort to work.
32:19
This is the craziest labor market in history.
32:22
OK, you can't keep the people who are not a native.
32:27
There are for sure not enough AI native people in existence for
32:31
you to actually fill the roles in your company.
32:34
So you have more job postings than you've ever had before
32:37
because everyone is trying to find that subset of people who
32:40
belong to that cohort. But the total number of actually
32:43
employed in tech people is going down.
32:45
It's not big and none of it is for financial reasons, which is
32:51
the crazy part. They just don't like what?
32:52
Why are they firing them? You can't have those people in
32:54
the company. Why can't you?
32:55
You can't have them. I don't.
32:57
I want to push back a little bit on that, that it's not at all
32:59
for financial reasons. I do think one of the things
33:01
we're seeing is that the software market has seen really
33:05
big loss in stock price. And so you've seen what was at
33:09
the top 25 software companies are down 50% over the last six
33:12
months. I do know that that has pressure
33:15
and ultimately the the way to expand your price is better
33:20
revenues and better margin and basically giving confidence that
33:24
you're going to be able to succeed in the future.
33:26
And it's very hard for those businesses to show that right
33:29
now. But I think part of what we're
33:30
seeing is that you have things like debt covenants and stuff
33:34
that start to come into play when stock prices drop to
33:37
certain levels and you've got profit margin concerns and all
33:39
these kinds of things. I think there's a little bit
33:41
there that maybe goes beyond the just trying to save money where
33:45
we're seeing companies making some of these decisions based on
33:47
the future outlook of the industry, not necessarily just
33:50
the whether these people are AI native or not.
33:53
So I, I don't know if that made sense.
33:56
But anyway, that's I think there's, there's some stuff
33:57
there with the, the banking system ultimately that plays
34:01
into us as well, not just the AI versus non AI native people.
34:03
I think that's true if you have already signed yourselves up to
34:06
believing that you are not going to become an AI native company.
34:09
So under that context, that's true, but in the context of
34:12
companies where that's not true, Cloudflare being one of them,
34:16
because what's a big part of what Cloudflare is doing right
34:18
now, they're making, they're helping companies make decisions
34:20
on whether or not a particular bot is allowed to like crawl the
34:23
page. They're like, I mean, like,
34:25
again, we don't talk about them like an AI company, but they're
34:27
for sure an AI beneficiary because the total number of
34:30
pages that you have to render and how you decide whether or
34:32
not you allow an interaction on your pages, all of it is being
34:35
arbitrated by Cloudflare, right? This like random company that
34:38
controls like what, 90% of the Internet basically.
34:41
And I think that and, and it's a massively profitable company.
34:44
And so, yeah, I, I don't know man.
34:46
I, I think it's like, I think the total number of people who
34:49
are going to be effective is today not large.
34:53
And so you need to figure out a way to get that total number of
34:56
people who are going to be effective to become much larger.
34:58
And there's, I think there's way more pressure to doing that than
35:02
there is financial pressures when when you are when you are
35:07
cash flowing, if you're not cash flowing, it's a totally
35:09
different issue. Yeah.
35:10
But it in this context just just work on the like cloud flare.
35:14
So I just looked it up. They've got, I don't know enough
35:16
here, but I'm just as an example, they've got 3 1/2
35:18
billion dollars in debt. Sometimes cash flow with these
35:21
companies isn't actually the thing that matters.
35:22
It's your debt covenant some and what the stipulations are that
35:26
have been put in place. And so when your stock price is
35:27
down and the industry's down and you've got like margin pressure
35:31
and the bank can come to you and say, OK, I have a friend who who
35:34
worked in a a large public company that that went bankrupt
35:37
recently. It wasn't that they couldn't pay
35:39
their loans. It was that they tripped their
35:40
debt covenants and had to then pay back $100 million that they
35:44
didn't have at that moment. And so the bank said, you've got
35:47
60 days and like, well, we don't have, they went and tried to get
35:51
$100 million and they couldn't get it.
35:52
And then you basically just do an asset sale and and that's it.
35:55
So there's some of that kind of stuff.
35:57
I think that's happening too. I don't think it's all like for
35:59
Cloudflare, their debt, their stock is down.
36:01
It could also be that this is a good example, because I don't
36:06
know enough about Cloudflare, but there's businesses like
36:07
Cloudflare that flare that are doing layoffs in part just
36:10
because of the fact that a bank may be coming to them saying,
36:13
hey, you're, you're at risk here.
36:14
You need to be careful. And I think there's a lot of
36:16
that kind of stuff that's happening right now, too.
36:18
Yeah. I think to give like a really
36:19
concrete example of what Rashad was saying about those people
36:21
cannot exist at the business. If you take a look at just like
36:24
AI solving customer service, right, that decreases risk at
36:27
companies like the ones we were just talking about, the ones
36:29
that we were just talking about, the customer service sometimes
36:32
sell customer information. That's like a real risk that you
36:35
completely mitigate by having AI solve it.
36:37
There's also human error, right? There's some rate of human error
36:40
from these people. And then there's the economic
36:42
value of the service actually forcing compromise, right?
36:46
Bad English in a lot of cases, no one has a good experience
36:48
with human customer service for the most part, right?
36:51
For the most part, people are frustrated with their experience
36:53
with customer service. I don't get frustrated with AI
36:55
customer service. It just solves the problem.
36:57
I'm like, OK, cool, bye. I don't feel like I have to be
36:59
friendly. It's like, OK, how do I do this?
37:00
Here's it here it is. I took to the page, I'm like,
37:02
oh, wow, that's incredible. Or like I was in customer
37:04
service for 11 labs the other day.
37:06
I was actually speaking to it and it was taking me to
37:08
different pages and I was like, this is incredible, right?
37:10
This is what customer service should be.
37:12
So I don't think that humans can exist in that future, right,
37:16
personally, right. And it seems like these
37:18
businesses are choosing for humans not to exist in that same
37:21
capacity that they they used to. But I'd love to hear what you
37:24
guys think about this and especially you, Jake, if you
37:26
have so much surface area on these different types of
37:28
businesses. But everyone knows the romantic
37:30
view of product like growth, right?
37:31
No marketing line item adoption through frictionless problem
37:34
solving. People get into the app, they
37:35
love it, they use it, it solves a problem for them like Claude,
37:39
right? But we're still seeing AI
37:41
implementation experts headcount for the purpose of bringing the
37:44
team along because even with frictionless access to software
37:48
that solves problems with like an aggressive velocity, right at
37:51
this unprecedented ease, some people still don't adopt, right?
37:56
And they stay in their old ways. So you need people to come in
37:58
and basically usher them. So yeah, I'm interested from you
38:02
guys that are leading teams. And I know that Rashad Jeremiah,
38:04
you guys are actually confronting this problem right
38:06
now in your business. How do we bring everyone along,
38:08
right, and make them update their ways?
38:10
What is the role of, you know, software on this?
38:12
Is that gamification? Is there a way that we can
38:15
design the tools to help people come on board, like what you're
38:19
doing, Jacob, with HQ? What's the role of AI natives as
38:22
headcounts coming into the business and bringing people
38:24
along? And I guess the last one will be
38:26
what's the role of the expectation from the founder and
38:29
the CEO to say, hey, actually you've got to do this.
38:31
This is the new expectation, just like we expected to you to
38:34
use Google Docs. And no one was particularly
38:36
passionate about Google Docs, but you use it because it's part
38:37
of your job. And that's what you do.
38:39
You founder or the CEO or the team lead or whatever it happens
38:41
to be, now has the expectation that you're going to be AI
38:43
native. Yeah, that was kind of like a
38:46
really big loaded question. Yeah.
38:49
Founder software, designing the software in a way that's
38:51
frictionless and brings everyone along, like maybe gamification
38:54
or making fun. And then I'm in a new head
38:57
count, right? That's part of what we're doing
38:59
with my business. It is free.
39:00
We're trying to get as much adoption as possible.
39:03
But on the service side, we're helping businesses solve real
39:06
problems in their business with AI, right?
39:08
That otherwise required people who had opinions and didn't want
39:11
to update their process, right? I have a coaching piece is so
39:15
important. I think like Jacob, you're
39:16
talking about how you have the service aspect.
39:19
I think that's so critical right now.
39:23
I agree. Sure.
39:23
You're talking about the like constantly being behind the
39:26
things like Cody's doing today or not things he's doing 3
39:28
months ago. I mean, that's true for me as
39:30
well. And that's it's just constantly
39:31
changing. And I think the other thing
39:33
that's interesting here, Jacob, the amount of demand you had so
39:35
quickly with this launch, I think it's just indicative of
39:38
the fact that very few people actually know what to do right
39:40
now. And I actually be curious for
39:44
your take on that too. But it just seems like there's
39:46
this, we see a few examples of people doing things really well,
39:49
but then the gap between that and actually figuring out how to
39:52
make that work for yourself, for your teams, for your company,
39:55
whatever seems to be very large right now.
39:58
And Jack, I just, I direct directly answer your question
40:01
like I don't like gamifying software fixes that.
40:03
I think it's really like coaching people ultimately.
40:06
Like, yeah, AI is a new tool. Not everyone has time to spend
40:11
their entire life on Twitter and using AI like I do, you know,
40:13
like it's just real people with real jobs doing their real job.
40:17
And they actually don't have time to like get really good at
40:21
using a tool like core code. And it's overwhelming.
40:24
Like the product experience is overwhelming.
40:27
You know, like you do have. I think there's a reason why
40:29
it's quite barbelled is because you have this chat box.
40:32
There's like magic chat box, which is really easy to give you
40:36
a lot of flexibility. It's really easy to use, but
40:39
also it's like, what do I do with the magic cat box?
40:40
You know, like I put myself in the mind of some random employee
40:43
and they're like, what do I do with this thing?
40:45
You know, they don't understand the and it is a technical tool.
40:49
Like it just is a tech. Like if I'm going to hook it up
40:51
to my CRM, there's a lot of things that maybe I understand
40:55
or like you guys understand about how that mechanically
40:57
works because we work in software businesses, but like it
40:59
is inherently technical. So like, it's not, it's not
41:02
necessarily easy, it's not necessarily intuitive when you
41:05
get into it. And so I think it's fair to
41:07
assume that it requires coaching like, and you can't compare it
41:11
to the Google suite of tools. Like if I open a Google doc,
41:13
it's like very obvious what I do, right?
41:15
It's a page for me to write on. If I open in Gmail, it's a very
41:18
obvious I'm sending an e-mail. But when I open like Pandora's
41:21
box and I can literally do anything with, with this thing,
41:23
it's like, well, what does that mean?
41:25
So I do, I think it requires coaching, but I do think once
41:29
you've, once you've kind of shifted your mindset and once
41:31
you get an intuition for it, then you do become really good
41:34
at it. And that's why implemented
41:36
implementers are also valuable because they are able to take
41:40
the expertise and that what they've learned and they're able
41:42
to do that for people who don't know and able to teach them.
41:44
And then there's also a miss massive mismatch of
41:46
expectations. And this is something that I've
41:48
shifted my mindset on recently, which is I actually don't think
41:51
everything needs to be done with an autonomous agent, like a
41:54
fully autonomous agent that does everything end to end for you.
41:57
I and that's what people sell on Twitter and LinkedIn because it
41:59
gets the views and it gets the, it gets the retweets.
42:03
Like if I'm optimizing for retweets, then yeah, I'm going
42:05
to say I built a fully autonomous agent that automated
42:07
my entire business for me. But if I'm a realistic person,
42:10
that's I'm most effective when I'm inside of a tool and I'm
42:13
driving it and it's super and it's a very efficient assistant
42:17
for me. And it goes off and it does work
42:19
sometimes, but I'm driving it forward.
42:21
And so you have a mismatch, mismatch of expectations.
42:24
If CEO goes in, they say their employee, I want you to automate
42:26
my process of creating ads for me.
42:28
And they just can't do that because of what I said before.
42:30
And it's probably not the right product to build.
42:32
And ultimately they should be building something a little bit
42:34
more assistant based. And so they should be working
42:37
inside of a tool they shouldn't be building and they try and
42:40
build agents. So I think it's a combination of
42:41
a lot of things, but but ultimately it goes to like why I
42:46
built this, which is it puts people in the right place, which
42:50
is they should be in core code. They shouldn't be magically
42:52
summoning open core agents to do all their work for them.
42:55
It teaches them how to do it along the way.
42:57
It's designed in a way to abstract a way the complexity.
42:59
And I understand that not everyone's going to be an expert
43:01
straight away. So I try and teach them and
43:02
train them along the way. And I think the future of it,
43:05
sorry, I know this is like a really the future of it, I think
43:09
is I do think it's possible for AI to teach like we do have a
43:12
tutorial command, We do have a set up command.
43:14
I think AI is a good teacher and and that can help self enable
43:17
and self yield the product. And so that is a future product
43:20
direction when it goes to product LED growth, when it goes
43:23
to kind of self enablement and set up.
43:26
But in the meantime, I think humans can fill back up dude.
43:28
What a great note to end on. We should not continue.
43:32
I didn't hear your I gotta. Go.
43:35
OK, I'll do it. I'll do it really fast.
43:37
I'll do it really fast. But I really do gotta go, yeah.
43:40
On thoughts on the expectation from the founder, the role of
43:44
the founder of the software and I should add in the individual
43:47
because ultimately at the end of the day, the individual actually
43:49
needs to want to use these tools but yeah, the role of these
43:52
different pieces in driving the business to become AI native,
43:56
bringing those people who aren't using AI yet into using AI in
43:59
every. Part of the role, yeah, I have a
44:02
very simplified view of this, which is this technology is
44:05
evolving at a rate that no other technology in the past has ever
44:07
evolved at. There's a small subset of people
44:10
who want to move close to that rate or at that rate, and it is
44:14
their job to get everyone else to move as quickly as we are
44:17
able to make them. And that's it.
44:19
And I think that if we do that, like everybody wins.
44:23
And if we don't do that, we will experience pain in all sorts of
44:28
ways that I think are unpleasant, from capitalistic
44:32
ones to societal ones to like corporate ones, whatever.
44:37
But that's the TLDR. And, and yeah, I think what Jacob
44:41
described is like, hopefully AI is a way that we enable that.
44:45
But regardless of whether or not it is, there's some set of
44:47
people who are moving at the pace and you've got to.
44:51
That's the job, yeah. Going to run.
44:55
Yeah, you got sales goals until 8:00 PM, so I'll speak to you
44:59
guys.