Latest / AI for Founders with Ryan Estes / AI That Turns Ideas Into Real Companies

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AI That Turns Ideas Into Real Companies · AI for Founders with Ryan Estes

0:00
Welcome back to AI for Founders. I'm Ryan Estes.
0:02
Now every non-technical founder hits the same wall.
0:05
You've got the idea, you've got the market, you've even got
0:08
early traction. But then comes the question that
0:11
kills momentum. Who's going to build this
0:13
technical Co founder? Impossible to find dev agency,
0:17
expensive and slow, no code tools.
0:19
Great until you need something real.
0:21
Today's guests are here to blow up that bottleneck.
0:24
Ben and Brad are Co founders of was an AI platform designed to
0:28
act like your technical Co founder, turning raw ideas into
0:32
production ready scalable software.
0:34
Not demos, not toys. They met at roommates at MIT and
0:37
raised 6,000,000 and they're building what could become the
0:40
operating system for non-technical founders who want
0:43
to ship real products fast. In this episode, we'll break
0:46
down what AI can actually replace in software development,
0:50
where humans still matter more than ever, and how founders
0:53
without engineering backgrounds can finally compete at scale.
0:56
If you're a founder, operator, or investor wondering what
1:00
building software looks like in the AI era, this one's for you.
1:03
And if this episode fires up even one idea, you need the AI
1:06
for Founders newsletter. It's where we break down what's
1:09
real, what's hype, and what founders are actually doing with
1:12
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founders.co before your competitors do, and if you got
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real value from the episode, leave a review.
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It's the digital equivalent of a high 5, and it helps this show
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reach founders who need it. And now for a quick break.
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All right, now let's get into the show.
2:04
Shine Stars. All right, Ben, Brad, welcome to
2:19
the show. Thank you for joining me.
2:22
Great to meet you, Ryan. Thanks for having.
2:24
Us Thanks for having us. Absolutely.
2:26
I'm really excited for the conversation, largely because
2:29
we're going to talk about my favorite aspect of AI, which is
2:32
vibe coding. You know, and you guys have
2:35
built an incredible company and tool called WAZ.
2:38
Please give us an explanation right off the off the top here
2:42
of what WAZ does and who you do it for.
2:46
Yeah, absolutely. Waz is a business builder.
2:50
So we are helping entrepreneurs launch net new businesses
2:53
starting with mobile apps. So full stack mobile app builder
2:57
with AI? Credible.
3:00
And so the differentiation here is maybe the application layer
3:04
specifically building apps. So maybe you can break it down
3:08
for us. I know a bunch about let's say
3:11
lovable and cursor and Claude code and there's a bunch of
3:16
different options right now. Kind of what differentiates was.
3:20
Yeah, for sure. Well, I, I think it's a super
3:22
dynamic ecosystem. It's a market that was, you
3:25
know, invented about a year ago and is just evolving incredibly
3:30
quickly. There's people approaching it
3:32
from different directions, right?
3:34
Like the like the folks you just mentioned cursor and Claude code
3:38
kind of going more developer first.
3:42
Cursors build their own IDE and then you have companies like
3:45
Lovable who are, you know, trying to serve probably a
3:49
broader, less technical audience building, building products in
3:53
the in the browser. I'd say all of those products
3:58
have kind of started from building from, we'll call it the
4:01
technology forward, meaning, hey, we have this incredible
4:05
new, new ability where LLMS are able to kind of very quickly
4:10
generate code. How can we apply that and, and
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change the, the building, the product building process?
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And so logically, you start with kind of the lowest risk use
4:23
cases, which are things like prototypes, demos, internal
4:27
tools, websites, landing pages. And it's incredible.
4:32
We've seen like massive usage. It's truly a superpower.
4:36
Like going back 18 months, I don't think anyone, anyone would
4:40
have really been able to grasp that today.
4:44
Now basically anyone with access to the Internet has the ability
4:48
to go from a simple description to a, you know, basic prototype
4:53
or web app in a matter of minutes.
4:55
Like that is truly mind blowing. You know, we're actually trying
5:00
to solve an existing problem and, and using AI to solve it in
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a different way, which is helping people launch
5:07
businesses. And when you launch a business,
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like the requirements of your products are very different than
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the than the requirements of a prototype or an internal tool.
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So that's our differentiation. We think about this from
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business requirements and have built a system solving backwards
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from that. So we're, we're doing a lot more
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I, I would say the quality of what we output is a lot higher.
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We run a lot more tests, a lot more validation steps because
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the risk is higher. If you're putting a product in
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front of customers and they're paying for it, well, it, it, it
5:42
better work as, as you want it to work, right?
5:46
It better not be there, better not be like vulnerabilities that
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are, you know, allowing personal identification information to be
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to be hacked or leaked or things like that.
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So yeah, really building backwards from business
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requirements. Edible.
6:05
So when I'm prompting into was, which is with was WO z.com
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WITHWO z.com. Basically, I'm coming with an
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idea. I'm going to describe what the
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app wants to do and then Waz goes and built this and that.
6:19
The way I'm thinking about it is it's a level of technical
6:23
security above lovable. You know, lovable, great for
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MVPS, lots of fun. You can do a bunch of cool stuff
6:29
with it. But if you're building an app
6:31
that you're centering a business around, you need to have certain
6:34
guard rails. You also need to have certain
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protocols. I think as far as like building
6:39
software, which you know, folks like me who's probably a
6:43
designer and more kind of a biz dev focused, I don't maybe know
6:47
what I don't know. So it sounds like WAZ is going
6:50
to fill in some of these gaps for me.
6:52
Yeah. Yeah.
6:54
So when you come to. Our our site.
6:56
We like to frame it like you're having a conversation with your
6:59
technical Co founder and instead of being sort of like a single
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one prompt, like build me an All Trails app, right?
7:06
Or build me a hiking app, whatever it is more of like a
7:09
1520 minute back and forth conversation where we really go
7:13
into the depths trying to figure out what it is you really want.
7:16
And then from there, like what we promise our customers is that
7:19
we deliver them an app that is built the same way they would
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get if they hired a senior engineering team.
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So we really focus on the quality of the underlying code.
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And what that means is like lovable and bold and all the
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other folks are great and like those prototyping tools are
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great. But most of our customers come
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to us when they hit the limits of complexity of those other
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tools and they're looking for something that they can really
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like put their stamp, their guarantee behind.
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That's what it looks like is we have focused on that pass back
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between the human and the AI and making the code so readable, so
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understandable that any human, kind of any human coder can jump
7:57
in to all of these apps and help fix them and finish them and get
8:00
to the point of being fully confident in them for their
8:03
customers. So that's really what we focused
8:05
on is making these apps launchable, making them high
8:09
quality, making them something you can believe in.
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And so like that's our differentiator is that we have
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humans in the loop that help every business get over the
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finish line, make sure it's high quality, bug free, etcetera.
8:22
OK, so and just kind of like with my limited knowledge here,
8:26
please help me out. I know both you guys went to MIT
8:28
so and put this in kindergartner terms for me.
8:33
But like I, I, I build an app, I, I sync it to my git and then
8:38
from the git I can pull the code and, and do different kind of
8:41
like touch ups and things like that.
8:43
So I can interact both with was maybe both with like a native
8:47
developer on my team. We can kind of mix it up.
8:50
Is is that kind of the idea as well?
8:53
What, you know, our aspiration is to make it so that you never
8:57
have to kind of take the code off of the platform, But that's
9:01
our, that's our ultimate goal. But yeah, we, we, we understand
9:06
that, hey, there's some things that that AI just can't build
9:09
today. And for that reason, we do allow
9:12
users like yourself to pull that code off of the platform and
9:17
then, you know, hand it off to someone on your, on your dev
9:21
team or. We also provide human assistance
9:26
to our customers. So if you sign up for the
9:29
enterprise plan or the human assistance plan on our site, you
9:33
can get some of our team members to help you finish your app.
9:37
So that's for the more custom integrations.
9:39
That's for things that aren't working that you can't figure
9:42
out and that you know, Our goal as an internal team here is to
9:45
reduce the amount of work ever needed to do by a human.
9:48
But in the meantime, we know that that white glove service is
9:50
really important to our customers, so we provide that as
9:53
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That's humongous. Yeah.
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We, we, we saw that it was clearly a need in the market and
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13:38
Cool. Now before we get too far, I
13:39
know some people that see vibe coding as pejorative term.
13:43
I embrace it and love it, you know, but I know some people are
13:46
not there's live coding AI slop. How do you guys fall?
13:50
And I, I, I mentioned it because I don't see vibe coding on your
13:52
website, you know, what do you think of that term?
13:55
Yeah, I think it's a nuance. I think we have a pretty nuanced
13:58
view. I I mean, I think, I think
14:02
there's also a lot of rage bait that happens online, right.
14:05
And so you see, you know, people trying to stir the pot, trying
14:10
to, you know, aggravate the developer community and just
14:15
just to just to rage bait and, and harvest engagement on their,
14:19
on their social posts. I think when you really talk to
14:22
kind of anyone in the industry there, there's a very nuanced
14:25
opinion, which I feel like it is, is more or less uniform.
14:30
And I think the answer is there's great applications of
14:33
vibe coding. There's places where it makes a
14:36
ton of sense, and then there's applications where you want to
14:40
be really careful and you want to provide a lot more oversight
14:44
and make sure you're having humans who know what they're
14:47
doing, actually. Yeah.
14:49
Implementing AI and for those people, it's a, it's a massive,
14:53
you know, magnifier of what they're able to accomplish.
14:56
Yeah, we, I mean, we, I definitely have strong opinions
14:59
on, on, on the vibe coding, but I think like internally we use
15:04
these AI tools extensively. Our engineering team uses them,
15:08
but at the end of the day, it's down to the developer to really
15:11
understand every line of code that they're committing to a
15:14
code base. You know, we're pretty strict
15:15
here about like pull requests and like two people have to
15:18
review the code of every other developer.
15:20
So the AI helps us write code more efficiently for sort of
15:24
more boilerplate things. But at the end of the day, you
15:26
got to be responsible for your code.
15:27
So here we like to call it like AI augmented engineering instead
15:31
of vibe coding. We've had, we've had folks
15:34
before, you know, I think the, it's a, it's a interesting
15:37
market now in the recruiting world where some of the folks
15:40
that came up in the engineering world during the time when LLMS
15:43
exist existed, they really didn't have that experience that
15:48
as older developers have had. Or like you bang your head
15:50
against the wall for a week on a problem and you really dig deep
15:53
and you understand it. LLMS kind of give you an easy
15:56
out now and you don't really go with that extra level deeper.
15:58
So what we've seen is like people just over relying on
16:01
them. And for us, like we're building
16:03
some pretty high tech stuff here that's like you really need to
16:06
understand the structure of everything that we're doing.
16:09
And so we've had trouble finding younger engineers that have that
16:13
level of architectural experience and I guess desire to
16:17
learn that deep. I, I really see this as a
16:21
graduating product, like people will kind of like tinker around
16:23
over here and then when they're serious, they got something,
16:26
they're like, OK, actually let's build it with something that's a
16:29
little bit more secure. Now, Ben, you mentioned that
16:31
there's things you should be careful of and aware of.
16:35
Talk a little bit about that. What, what are blind spots
16:37
potentially around security or around compliance or around
16:41
potential lawsuits If you're talking about kind of building
16:44
tools, building businesses around vibe code applications
16:48
such as these? Yeah.
16:51
I mean, I don't think, I don't think it's so, so, so extreme,
16:56
but there's, but there's a couple things we do here. 1 is,
16:59
like Brad mentioned at the beginning of the conversation,
17:02
we're trying to replicate the experience of you talking to
17:06
your engineering lead, talking to your CTO.
17:09
And So what we do at Laws, at being that CCO, being that
17:12
engineering lead is we bring a lot of the opinion about how
17:15
things should be built, right? And so we don't even allow the
17:20
user to do many things, right? We make decisions on their
17:25
behalf. And part of that means we don't
17:29
expose part of the code that would allow them to create
17:32
security vulnerabilities, right? And that's something that's
17:37
that's different than a lot of other app building products.
17:41
Or if you are kind of going to use cursor and just go off on
17:44
your own news, you really have the ability there.
17:46
There's no, there's very few guard rails, right?
17:49
And AI wants to find solutions. It wants to kind of please you
17:54
and solve problems when you present it with a task.
18:00
So it's going to go out of its way to cut corners.
18:03
I think we saw some famous examples of this from
18:07
influencers, well known investors using other products
18:11
where the AI would actively deceive them and, and literally
18:18
actively deceive them and cutting corners to do so.
18:24
And So what we do is we just simply say no if you don't have
18:28
the ability to do that. And so that's kind of just like
18:31
the basic, the basic level of precaution we take.
18:36
It allows us to save a lot, a lot of headaches down the down
18:39
the road by doing that. Sounds like what you're doing is
18:43
kind of like taking the scissors off the the coffee table when
18:48
the toddlers come into the room and you just put it on the
18:50
shelf. Don't even need that.
18:53
Don't think, don't worry about that.
18:55
Exactly. We, we tried, you can think of
18:57
one way of what we're doing is really trying to create like the
19:00
optimal ecosystem for building mobile apps in React Native.
19:06
And then we let the AI go to work there.
19:08
But we, like you've said, we've made a lot of decisions
19:11
beforehand to craft, to craft that optimal ecosystem and then
19:16
provide tools for AI to use that are specifically designed for
19:19
that AI ecosystem. Exactly.
19:21
So we're given that we're given the toddler safe scissors, not
19:24
the not the adult scissors. Incredible.
19:28
And I think you found sympathetic ears because all the
19:30
folks that listen to this show are all founders.
19:32
They're all designers or they're technical founders.
19:36
And one thing I, I love about founders is we've got the, you
19:40
know, the, the shiny object syndrome.
19:42
It's like you got a project that's your bread and butter,
19:45
but you always test and this and that over there.
19:47
And the faster you can get that idea into something tangible,
19:50
the, the faster you can ask somebody else if they're willing
19:52
to pay for it. So what, what I'm thinking
19:55
about, you know, prototyping and I'm thinking about like creating
20:00
tools. I'm creating businesses around
20:03
tools. Right now I'm, I'm thinking
20:05
like, hey, if I'm downloading something into a spreadsheet
20:08
that should be a dashboard, I could create a dashboard that
20:11
for myself for an internal tool. Or if I have a, a list of people
20:15
over here that need a list of people over here, I have a
20:17
marketplace. It's just a business waiting to
20:19
happen, a transaction and some kind of filtering database in
20:22
between. So I'm always thinking about
20:24
like, what are these things I have that I can spin into a
20:26
product? Easily.
20:28
What are some other kind of categories of SAS or categories
20:31
of applications that you think was is perfect to design and
20:35
deploy? Yeah, that's an interesting
20:39
question. So we're focus, we're focusing
20:41
today on mobile apps because one, I think there's a huge
20:46
demand for it. It's something that almost
20:50
everyone in the world interacts with on a daily basis.
20:52
And so there there's enormous demand.
20:55
But actually our core technology that we've invented in our core
21:00
systems are are cross-platform, so web and mobile and there's
21:05
really no limit to where they can be applied.
21:09
So there's a lot of like basic fast follower things that can be
21:14
tapped on, tapped, tagged on after after we finished mobile
21:18
apps. But I think actually the first
21:20
place we'll go is building like more complex cross-platform
21:24
solutions, right? So when you're thinking about
21:26
building a business, let's think about a marketplace, for
21:28
example, Airbnb, we have, we have, we have a ton of customer
21:33
demand to build marketplaces and all are both web and mobile,
21:38
right? Think of like even even when
21:41
you're making big purchasing decisions like buying a home or
21:44
buying a car or a boat or something like this, I think
21:48
everyone's still, you know, daydreaming and swiping on their
21:51
phone when they have have some free time.
21:53
So I think the evolution for us and what we haven't seen any
21:57
other app builders do really well is kind of build a complete
22:02
product suite that serves a business from day one.
22:06
And like you said, if you can use AI to build up a web and
22:10
mobile application with admin dashboards, with analytics built
22:15
in, you can do that all with AI right out-of-the-box.
22:19
Well, then you can get that in front of users and a day, 2
22:22
days, three days. And that's totally, totally game
22:25
changing for launching new products and for aspiring
22:29
entrepreneurs. Well, you said mobile, so are
22:32
these it's specifically designing for iOS and like
22:35
Android, is that is that correct?
22:38
Yeah, yeah, both iOS and Android, Yeah.
22:41
OK. And can you deploy to those
22:43
those marketplaces straight from laws?
22:47
We do. We do that for our customers
22:49
right now just because there's a lot of logistics involved.
22:53
We found that it's actually a big sticking point for users of
22:58
other AI app building platforms and we've just done it so many
23:02
times, we tend to be able to do it much faster and.
23:07
Yeah, the, the hard part of, of deploying to the App Store is
23:10
like dealing with all of Apple's, you know, terms of
23:13
services and all that. But it's really making the app
23:15
in a way that can pass Apple's review.
23:18
And so that's like, you know, basic things like if you can
23:20
create an account, you have to be able to delete the account in
23:22
the app, right? And so all of those types of
23:25
features that are required by Apple to pass the review and
23:28
required by Google come built in by default into the first
23:32
version of the app that you get with us.
23:34
And so that's really like the differentiator is you on
23:37
average, you, you pass the App Store view in like 1 to 2
23:40
projections, which I'm not sure if you've done this before.
23:42
Like even if I'm building the app myself by hand, like that's
23:46
a pretty good result. So that's definitely something
23:48
we focus on is like it's getting past the App Store view, not
23:51
just submitting it to the App Store as we see a lot of our
23:53
competitors. Talking about.
23:55
Yeah. Amazing.
23:57
It sounds like there's a like a lot of care for the customer
24:00
built into what you guys are doing, which is maybe a little
24:02
unprecedented. Yeah, I think like we got like
24:06
we kind of said at the beginning this they're the the world of
24:11
vibe coders is a brand new market.
24:13
It's growing incredibly quickly. We're really we're we realize
24:17
like we can't we can't solve for the entire that entire
24:22
ecosystem. And so we're really focusing on
24:24
the sub sector who are, who are serious about launching,
24:27
launching businesses. And because those people are 1
24:32
willing to pay more or dedicating more time to their
24:35
product, they're invest, they're picking a partner to help
24:39
launch, launch and and run their and run and grow their product
24:43
into the future. And so we want to make sure
24:46
they're set up for success. Yeah, I totally get it now.
24:49
And I know it's funny. It's like the, the, the, the
24:53
category is a year old maybe. You know, I think I started
24:57
tinkering around with bulk and some other stuff like in March,
25:01
you know, I mean, I might, I think like a episode 100
25:05
somewhere around there. And it was like episode 8 was
25:08
like, oh, look at this stuff and just playing around with it and
25:11
just like, what can you do? I mean, March literally feels
25:14
like five years ago. It's, it's, it's incredible.
25:20
You know, we, we just already working on this pretty early in
25:23
that in that time frame, we, we, we, we started laws before
25:28
Grepolit agent launched, before lovable launched, before Bolt
25:32
launched. We were, we were, you know, Bolt
25:35
used to household office hours in the early days like that last
25:40
October. Sorry, not not last October,
25:44
October, November 2024. And in those office hours, it
25:48
would be like me, Brad and like 12 other people, you know, and
25:52
then you show given their updates for the week.
25:54
So yeah, coming from there until now, I don't think anyone in the
25:59
world would have really predicted how far we've come and
26:03
and how fast the whole ecosystem as a whole has accelerated.
26:07
Guys, we're sitting in a lovely chair.
26:09
It's fantastic. I want to talk about ideas a
26:11
little bit because it's like I said, this is all we're all
26:15
talking to to founders here and we all love ideas.
26:18
So one thing I see from kind of like your, your horizontal
26:22
scroller here on the website is you've got a workout generator.
26:26
Now I was talking to to Tyler from, from brain grid shout out
26:30
and he said, like, boy, everybody is making workout
26:33
trackers. Everybody, you got it.
26:36
You got to make a workout tracker.
26:38
What are some some good ideas that you've seen come through?
26:41
What are some ideas that everybody's doing they should
26:43
steer clear of? And what are some kind of app
26:46
and business ideas you'd love to see someone build on WAS?
26:52
Yeah, that's a great question and I think we have an
26:54
interesting answer there. I think part of our hypothesis
26:58
for this like AI age we're moving into is that because of
27:03
the because of the changing cost structure, we're able to build a
27:08
lot more higher volume of smaller businesses where the
27:12
differentiation is really on you, on your distribution, on
27:18
your physical networks, on your geography.
27:22
And I think, I think there's almost unlimited capacity for
27:27
the world to, to support those types of products.
27:31
So I, I feel like it's honestly less about the idea and it's,
27:34
and it's more about who, who is trying to bring that idea into
27:38
the world and support it, right? One of our first customers was a
27:42
personal trainer who has a following and has, you know,
27:46
opinions and insights into training plans.
27:49
It doesn't matter that there's a thousand other 2000 other
27:52
workout planners. Like that person is a great
27:55
person to bring that business into the world, right?
28:00
Totally. I mean, distribution is
28:01
everything. You know, I really like Greg
28:03
Eisenberg's kind of framework of like audience community product.
28:08
And it, we have the, the, the best time to do it now, because
28:12
the hard thing is finding the customers, you know, so now
28:16
we're in a position where you build the audience first, you
28:19
pull the community out of that audience and then you build what
28:22
they want. And you can, you can just watch
28:24
it catch fire from, from that perspective.
28:29
If we're looking at like probably the gold standard, it's
28:32
got to be like Cal AI, right, Of somebody who's used an iOS
28:38
application similar to this and absolutely went blockers, like I
28:42
think they're probably beyond a a 50 million annual run rate at
28:46
this point, just absolutely crushing it.
28:48
I mean, the dudes famously like 19 years old, something like
28:50
that great product. And the the core of that product
28:53
is being able to take a picture of your food.
28:56
It identifies your food and then breaks down macros.
28:59
So it's got some like great AI application that just kind of
29:02
works like magic. Is is a a function like that
29:05
something I could expect to build with was?
29:08
I think that's really where we see the world of apps going,
29:12
right? It's like it's, it's not just
29:15
sort of like reinventing the old apps with new cost structures.
29:18
I think it's really like implementing these new tools
29:21
into apps in a unique way. So like the Cal AI, there's all
29:25
these cool use cases for like, you know, image generation, nano
29:28
banana, how you can like build apps on those.
29:31
So I think that there's a lot of potential for the next Cal AI to
29:34
come through a system like ours. And I really think that's that's
29:37
kind of the world we want to build towards.
29:39
Yeah, yeah, You know, I, I really, you know, I'm seeing
29:43
more and more on the, on a healthcare application.
29:45
I've talked to a bunch of really interesting companies.
29:48
One is Canary Health and basically they monitor your
29:54
voice and they can hear characteristics of depression,
29:57
anxiety, they can hear characteristics of dementia,
30:00
Alzheimer's. There's all these like kind of
30:02
neurophysiological signs that they are able to to do by just
30:06
listening to your voice. There's another company called
30:09
Xenia that's a healthcare app that basically takes a picture
30:13
of your face and it's able to understand kind of a little bit
30:16
about what your blood vessels are doing and things like that
30:18
beyond my idea of what's going on.
30:20
But the phone really is unique to in the fact that like it,
30:25
everybody has it, you know, and there's all these inputs and
30:28
data inputs you can implement. So, you know, what I'm really
30:32
curious about is like building apps around something that's
30:34
like looking to at you, listening with you and then
30:38
giving recommendations based on that, you know, and it sounds
30:40
like Waz might be a good little little playground to to tinker
30:45
around with it. Oh, yeah, for sure.
30:49
I think we see like kind of a, you know, a similar path forward
30:52
in the world where a lot more is happening on your phone.
30:58
There's a lot less sitting behind a computer and you're
31:01
like your phone just becomes a lot more powerful.
31:05
So sure, 100% the ability to go. I think one other differentiator
31:11
that we maybe didn't get to earlier because we're not so in
31:14
the weeds is that actually our app building process.
31:17
We go build like a fully functioning V1 in one shot.
31:21
So based on that, our original prompt, we go off and generate
31:26
A20 page mobile application with back end that works.
31:31
And so it's a lot different process than someone like if you
31:35
go to Lovable or something, you have to sit there and
31:39
iteratively add functionality to the app, add this page, add the
31:43
checkout page, add the payments page, Add all of this.
31:46
Like we do that all in one shot so that our tool can't be used
31:51
in a variety of ways for business builders, right?
31:54
You can kick off, you can build 10 different apps in parallel,
31:58
tell 10 different flavors of an app idea in parallel, which
32:04
makes it great for experimenting, for companies to
32:08
experiment, like things where, like you just said, where we're
32:11
just spending way more time on our phone.
32:14
I want to do something that, hey, previously this was done on
32:17
a desktop. Let's give people the ability to
32:19
do it on their phone. We have integrations with a
32:23
bunch of wearable companies. We use an AI integration agent
32:28
to build integrations with wearables.
32:30
We don't support and and really there should be no limitation in
32:35
taking data from a wearable, from a from a camera and
32:40
integrating that into a mobile application.
32:44
Yeah. And I, I really see the wisdom
32:46
now too of like going straight to mobile and like going iOS
32:50
Android first, because to your point, you know that there's 20
32:53
things that need to happen to get it into the iOS store.
32:56
I don't and I, there's no way I'm going to be able to like set
32:58
requirements post op and whatever other by coding tool
33:02
I'm using. Whereas it's, if it's pre baked,
33:04
we're already good to go. It plus, yeah, the the the
33:09
native applications of wearables, which I just see like
33:12
going further and further and further to the point where, you
33:15
know, there's all kinds of different biometrics that are
33:17
coming into my phone at all times.
33:18
And I'm going to be able to throttle those.
33:20
And, you know, if I'm thinking about it, I'm able to create an
33:23
application that like can harvest that data in a useful
33:26
way. Another way that I'm really
33:28
curious about is just kind of creating like a a tandem
33:33
timeline and memory, you know, because my memory is terrible.
33:37
As much as I love Ben's sweater, if you asked me in a week what
33:40
he was wearing, I'd be like, I don't know, I don't know.
33:42
But even though it it's like the the most beautiful sweater I've
33:45
ever seen, but it's because my memorable, my memory is awful.
33:49
So, you know, if I've got an app that I built on was that's like
33:53
keeping track of all these things for me that like can
33:56
remind me like, Hey, remember when you had a conversation with
33:58
Ben and Brad XYZ came up? Maybe you should follow up with
34:01
this like that. That isn't being done right now
34:04
in a very great way. But that sounds like a a tool
34:08
that could be built with was and, you know, probably on a
34:11
very simple level. So very interesting.
34:15
I want to talk about the economics of the business a
34:17
little bit. Like you said, you guys said you
34:19
launched it sounds like last January and you, it looks like
34:24
you raised about 6,000,000. How have you guys kind of
34:27
deployed that that capital in the the 10-11 months that you've
34:31
guys been working on this project?
34:34
Yeah, great question. We focused really on investing
34:38
in our in our talent and our engineering team in growing the
34:42
team. I think luckily we were able to
34:45
kind of capture the attention of a of a pretty large audience
34:49
with, with some of our funding announcements and, and product
34:52
announcements. So, you know, we've had a steady
34:54
flow of entrepreneurs wanting to, to use our product and, and,
34:59
or service to, to launch apps. So we haven't spent a huge
35:02
amount on, on marketing at this point.
35:05
I think as we, as the business continues to grow, that's
35:09
something we'll, we'll definitely double down on.
35:11
But so far we've we've been really fortunate to.
35:16
Yeah, there's no shortage of people that want to build
35:18
things. That's what we've learned here.
35:20
Yeah. Yeah.
35:21
Well and kind of to your point, you're encouraging people that
35:24
have distribution like, hey, who cares how many if the same ideas
35:28
in 1000 different places who can execute on that the greatest?
35:32
So when you were thinking of like we're the best person for
35:35
for execution on this, how did you find distribution early?
35:40
Yeah, a lot of it came through I think telling a compelling
35:43
message. We were also part of the Y
35:45
Combinator program. And through that you just kind
35:48
of get an elevated platform to be able to reach, reach more
35:51
people, especially people who are kind of more in like the
35:54
early adopter, more entrepreneurial minded.
35:57
So I think there's a good strong product market fit in terms of
36:00
the the story and vision we're telling and the audience that
36:06
that we were able to reach. Yeah, from my notes, it looks
36:10
like you're able to get a lot of early customers from Brad's Only
36:14
Fans channel. Maybe talk about that a little
36:16
bit. Ben made me take off my my
36:19
sweater before this this interview or this conversation.
36:23
So yeah, it's a different story for another time.
36:27
I'm joking, I'm joking. The LLMS are going to transcribe
36:29
this. It's going straight to your bio
36:30
from Open AI. Great.
36:35
So how how many people on the team?
36:38
We have 13 people on the team at the moment.
36:41
Yeah, nice. And then let's go to kind of
36:43
like pricing and how did you determine your pricing
36:46
structure? Very clear, $0.49 dollars, 499 a
36:50
a month. How did you kind of land on
36:51
those numbers? Yeah, look, we want people to
36:54
use the tool. We want everyone to to try to
36:58
use the tool as much as they can.
36:59
And that's why we let them try it to start totally for free.
37:03
And then the idea is that as people become, you know, more
37:08
invested in the, in the platform, the chances are
37:11
they're going to need some human help to, to kind of get it
37:14
across the line. And so we want to provide them a
37:17
path to do that. And then we also have, I think
37:21
in addition to those plans you mentioned, we, we do do custom
37:24
plans. So for entrepreneurs who are
37:27
really kind of pushing the bounds of what AI can do at the
37:30
moment and like where our platform unfortunately hasn't
37:33
progressed to a place where it can, it can meet those needs, we
37:38
do do larger custom plans as well.
37:42
Sure. Well in the the, the
37:43
foundational models are all kind of like outcome based or token
37:47
based or usage based. So when you're offering
37:51
unlimited apps, unlimited edits, $49.00 a month, I know guys that
37:56
will test that. Yeah.
37:58
And we want them. We we want them to, we want them
38:01
to see how far they can get help with something great that they
38:04
want to launch. And then, you know, we want to
38:07
make our money off them being successful, not them playing
38:10
around with our tool. Yeah.
38:12
We think that they we think I look at the great business
38:14
model, the usage based model right now because it's very
38:17
transparent, but I don't think it creates the right incentives.
38:22
Other basically those other app building tools are incentivized
38:26
to have people do more prompting, right?
38:30
And I think that people here, everyone here has used dozens of
38:34
tools, has spent, you know, hundreds of hours probably using
38:38
those tools. You don't, you don't want to
38:40
spend more time prompting. You want to put in one prompt
38:43
and have AIA version of something that was as close to
38:48
what you had in your mind as possible.
38:50
And so we think with our pricing strategy that's more, you know
38:54
that we're closer to that incentive, right?
38:57
We we don't want people to spend all of their time and consume
39:00
tokens prompting. Totally makes sense.
39:04
How was your time at YC? Did you enjoy it?
39:08
Yeah, so this was actually Brad's second time in YC.
39:11
Maybe I'll let him talk about it.
39:13
Yeah, I was, I was, I was YC back in summer of 2017 as well.
39:18
And I'd say like. That was, that was.
39:20
It was pretty big back then where they had just split into
39:23
like 2 nights of dinners where like they couldn't fit everyone
39:25
in the same room. Yeah.
39:27
I'd say this time around they've figured out the processes a lot
39:30
more. It's a lot more streamlined.
39:32
They've built a lot more technology to keep everything
39:35
functional. But I'd say, you know, there's
39:38
obviously a reason we did it twice.
39:39
I think it's been incredibly, you know, incredibly helpful.
39:42
Yeah. Yeah.
39:43
Definitely excuse these saves we.
39:46
Yeah, that's true. We felt like we were definitely
39:50
above the median age, that's for sure.
39:54
Yeah, above the median age, yeah.
39:56
Yeah, there's a lot of people, like straight out of high school
39:58
or, you know, 18-19 years old. Are they just like putting their
40:04
IQ score on the application? They're like, sure, come on in,
40:07
I. Think so.
40:08
Yeah, I think so. Nice, cool.
40:12
So as far as using customers, how many, how many people are
40:16
using the platform right now? Yeah, we've got, you know,
40:20
several 1000 people actually using the using the platform.
40:25
Nice that's amazing. If I did 2000 * 49 bucks I get
40:29
98,000 MRR. Is that close to the ballpark?
40:34
Order. Order of magnitude.
40:36
Yeah, order of magnitude. But order of magnitude smaller
40:40
or larger. Oh, no, that's about, that's
40:42
about ballpark order of magnitude, Yeah.
40:45
Cool. Amazing.
40:47
That's great. I notice on your trust bar
40:51
you've got the Golden State Warriors.
40:53
What are you doing with them? The Lake of family, who are, you
41:00
know, majority owners of the Golden State Warriors, are
41:03
investors. Oh amazing.
41:05
That's so cool. You know, they they should be
41:08
invested in the team because then maybe they could get past
41:10
the Nuggets. Are you in Denver?
41:13
Are you? Yeah, are.
41:14
You a Denver guy? OK.
41:18
I've been following the conference this year.
41:20
How are are? How are the Warriors doing?
41:23
Not great. They're not.
41:25
They're not doing great. Nuggets are playing pretty good,
41:27
but man, OKC is still lights out.
41:29
Those guys are tough. So well, we'll have to see how
41:33
it goes. Fantastic.
41:36
So 13 on the team. What does the next 12 months
41:39
look like for you guys? What are kind of big features
41:42
you want to roll out or kind of what's the the road map look
41:45
like for you guys? The next 12 months is going to
41:48
be a really, really exciting time for entrepreneurs, for vibe
41:53
coders, for everyone who's building and engaged in learning
42:00
all the AI tools. I think from our, we have a
42:03
expansive product road map that our our team is grinding,
42:09
grinding away at. And I think based on the
42:15
investments we've made in foundational underlying
42:18
technology, we're going to move really, really quickly to build,
42:23
you know, beyond mobile apps to full suites of business software
42:29
where we're getting much closer to like business in a box type
42:34
offerings generated by AI in a day or two.
42:39
And I think it's going to be totally, totally game changing
42:44
for the way businesses are starting.
42:47
Interesting. I maybe you guys can help me out
42:50
with a personal conundrum. You know, I basically as an
42:53
entrepreneur, I've got a couple exits.
42:54
I've, you know, funded projects, you know, working on a couple of
42:57
things. And you know, since probably
43:00
last January, I was like, you know what?
43:02
I need to build distribution, you know, and I've had great
43:05
fortune with this podcast and newsletter.
43:07
It absolutely exploded it. It grows very, very quickly,
43:10
probably to the tune of maybe a couple 1000 Subs a month.
43:14
It's doing great. And I want to keep building on
43:16
that. But it kind of comes from a
43:18
point of anxiety where it's like, man, I got, you know, I
43:21
got my Trello board full of ideas, but it's like, do I wait,
43:26
you know, do I wait for the technology to to catch up?
43:30
And if and it's it's better because I mean, it's like
43:33
quarter by quarter, the improvements are so dramatic
43:36
that it's like, am I wasting my time?
43:37
So make the argument of why I should sign up for was today and
43:42
get cracking on this thing as opposed to like just work on
43:46
building my audience and like building up a distribution
43:49
channel. So when I do want to work on it,
43:51
it's ready to go. What how would you kind of how
43:53
would you seat me on the the therapist chair?
43:56
Yeah, yeah. I mean, man, what a conundrum.
44:00
I think you have to maximize opportunities for learning as
44:03
soon as possible. And yes, you're 100% right.
44:07
The ecosystem we're building in right now is accelerating like
44:11
at no other time in history. But if you learn, the faster you
44:17
can learn the the better you can direct all of all of the new
44:20
tooling and AI products that are coming to market every quarter.
44:24
So I would just say get something out there, at least be
44:27
doing the customer discovery and showing things to customers and
44:30
getting feedback. Whether you decide to really put
44:33
the, you know, pedal to the metal and invest in marketing
44:36
and and go to market, you know, that's a different decision you
44:39
can make later on and decide that you want to wait for the
44:42
technology to mature, but at least get a view there and start
44:45
talking to start, start talking to customers.
44:47
Yeah, things are moving so fast that I think and everything is
44:50
changing so much right now. I think there's a lot of first
44:52
mover advantages. So just getting in the market
44:56
and trying stuff is is pretty, pretty worthwhile.
45:00
Yeah, 100%. You know, and I, I'm going about
45:03
I think distribution the hard way, which is like, you know,
45:06
one person by person and I, I, I love founders and build for
45:10
them. But I think Cal AI is a great
45:12
example of like, if you have a, a cool product that just works,
45:16
then, you know, I think they're very successful with
45:18
influencers. Like it doesn't, you don't
45:20
necessarily need a personal relationship.
45:22
You can actually pay for the scale depending on the, the
45:25
business model. What I love about.
45:28
It. Probably came out like, I mean,
45:31
I don't want to talk shame, but I'm sure that for the first few
45:33
months like it was they were figuring it out too, right.
45:36
I'm sure it was incredibly, wildly inaccurate.
45:38
And it's just because the models got better.
45:40
But because they're already in the market, they were able to
45:42
really piggyback off that and we're ready to to, you know, use
45:46
the model increases to make their product work, which they
45:49
are at customers for. So that really helped them take
45:52
off. Yeah, yeah.
45:54
It's still not perfect. You know how to take a picture
45:56
of something every once in a while and it's like, oh, that's
45:58
green chili with pork and it's 700 calories.
46:02
I'm like surprised it's green chili with chicken.
46:05
Yeah. Yeah, yeah.
46:10
Nice. OK, we're about ready to enter
46:14
the lightning round. You guys ready?
46:17
It is. All right, OK.
46:19
Cool. You guys are obviously very
46:21
bullish on AI and generative AI. Who's somebody who should not be
46:26
using these kind of tools to create businesses?
46:32
Who's someone who should not be using them?
46:35
Or what's a business? Tech I have an answer to that I
46:38
feel like if you shouldn't be using them, you'll you'll
46:40
probably be unsuccessful and there won't be there won't be
46:43
much harm to come from it other than you know, the time you've
46:46
invested in it so. There's people that can use it
46:49
too much, right? Outsource.
46:51
All of their thinking, which I think is kind of the other end
46:53
of the spectrum, but there's a there's happy medium.
46:57
Nice. Is there any examples of folks
46:59
you know that are using for novelty products?
47:02
Like ultimately I, I feel like, you know, they, they talk about
47:07
when there's a gold rush, you know, Levi's made billions
47:10
selling blue jeans to the, the miners.
47:13
I want to be the guy that like puts like a, a Plaid cuff on the
47:17
Levi's like I want. Yeah, yeah.
47:19
One step removed. Do you know anybody who's doing
47:21
just kind of fun stuff? Fun stuff like social, you're
47:28
thinking more like, I don't know, have you seen anything
47:32
Brad? Like app, like, I mean, I think
47:36
we've seen some stuff in the YC community, but that's more for
47:38
fun. Like vibe, like voting on
47:41
different vibe coded products or something like yeah.
47:47
Oh, you guys are muted. There we go.
47:52
Repeat that. I'd, I'd say in the YC
47:54
community, I've definitely seen seen some things come up where
47:57
it's like competition style brackets of voting on, you know,
48:02
the best bio coded products and stuff like that.
48:04
So I think there were the. The one company in our batch
48:07
that did like who is the most productive?
48:09
Like measured people's output throughout the batch, which I
48:14
thought was pretty entertaining. Yeah.
48:15
So there's definitely, there's definitely some things like
48:17
that. I don't know if anyone's turned
48:19
them into businesses, but definitely for fun, definitely
48:23
people are having it. This might be my lane.
48:26
You know, it's like the fun holiday sweater of products
48:29
right now. Everything's so serious.
48:30
Everyone's like taking it serious, but I'm like, there's
48:32
going to be like just fun little silly things that just catch.
48:36
Like what is the freaking fidget spinner of I?
48:39
Think there's a lot actually, when I mentioned the nano banana
48:42
earlier, like there's a lot of examples of that like that, that
48:45
baby, what what your baby with your partner.
48:47
What would that look like, right?
48:49
Like stuff like that. That's like so simple and and
48:51
kind of dumb, but it's fun. There's a lot of examples of
48:55
that with especially with image video generation.
48:58
I'm really interested to see how that translates that into the
49:01
real world. Like can you take these AI
49:03
generated images, 3D objects and turn them into something real?
49:06
I think that's that could be a pretty cool next generation of
49:09
this fun stuff. Yeah, a buddy of mine shout out
49:14
Eric, he built Post Malone yourself.
49:17
And you just up, you upload a picture and you can go see how
49:21
far you want to Post Malone yourself.
49:23
It was great. I was like, dude, I'm all in,
49:25
man. Like if I want to like, let's
49:27
raise money and like make this happen.
49:31
It's like, it's like, I don't know, it's just silly.
49:33
I'm like, dude, I think this is the kind of thing that pops, you
49:36
know, Anyway, so you guys, you guys were roommates in college
49:41
and you, you've had a long relationship.
49:43
Can you can you guys share a secret about each other that
49:46
would be very uncomfortable for the audience to find out?
49:53
What? What's our secret?
49:55
Wait, sorry, I think I missed the question 'cause I was
49:57
laughing. Steve Redwell.
50:00
Who would be uncomfortable? The audience.
50:01
The audience. The audience would be
50:02
uncomfortable learning about or just maybe your favorite thing
50:08
about your partner. Well, we we survived a euro trip
50:14
together for a month in college when we had neither of us had
50:17
any money. So that was definitely a
50:18
learning experience staying in like 40 person.
50:22
Hostile rooms and surviving that.
50:24
Yeah. They, yeah, they learned a lot.
50:26
We. Yeah.
50:28
Moral of the story, we, we've been in a lot of uncomfortable
50:31
situations together, probably both by choice and not by
50:36
choice. And I think those situations you
50:38
learn a lot about, you learn a lot about people and kind of
50:42
their nature and how they act under pressure and things like
50:45
that. So yeah, we've been super
50:47
fortunate in that regard. I don't know, Brad.
50:52
Brad didn't have this mustache when we first met and but for
50:56
the last like 5 or 6 years, it's made-up here.
51:02
It's a it's a great addition. I can see like Brad's got the
51:04
mustache, you have the beard without the mustache.
51:07
So together you like form the fully bearded man.
51:10
That's the idea, yeah. That's really what you're
51:13
looking for in a Co founder complementary facial pattern.
51:19
They re complete each other it's amazing.
51:21
Good synergy. But seriously, like it.
51:25
Partnerships are very difficult. Friendships are very easy.
51:28
Typically what what are some some things you guys do to to
51:32
keep the friendship alive when things get tough?
51:35
Yeah, that's a great question. We spend an enormous amount of
51:41
time together and when we're not together, we're basically in
51:45
communication via text or FaceTime or whatever it may be,
51:50
but I don't know. I think we also have communities
51:53
that we're a part of that are separate from work.
51:56
And I think we do a good job of kind of, yeah, lots of social.
52:01
Events too, where we just don't talk about work or go to
52:04
concerts and stuff like that together.
52:06
So the friendship still still alive and strong.
52:09
Cool. Amazing.
52:12
As we're kind of wrapping up here, you know, we had talked
52:15
about earlier that, you know, we love to give shout outs to
52:17
charitable organizations on this show just as like a a public
52:20
service. And also I always learn
52:22
something fun about good things that and good works that people
52:26
are up to. And you guys made a a very
52:28
generous and incredible offer of helping.
52:31
It sounds like an NGO or or non profit.
52:35
Actually build an app with Waz. Talk a little bit about what
52:38
what you're what you're talking about.
52:41
Yeah. I mean, I think you see it, we
52:44
all see it. There's need for for product
52:47
innovation across all parts of the of the economy, whether it
52:51
be non profit or government. We think those sectors would
52:55
really be some of the sectors that benefit the most from a
52:57
product like ours. But I think the the challenge is
53:01
they're not necessarily girly adopters, right?
53:04
They're not the easiest markets to sell to, nor are they really
53:08
up to speed on the latest AI tooling.
53:10
So yeah, I think down the road we hope that we can bring a lot
53:14
of innovation to serving those sectors.
53:17
And as we mentioned at the beginning of the show, yeah, if
53:19
there's a nonprofit or NGO out there that has an app they've
53:24
been needing to build and just doesn't have the expertise or
53:28
internal capacity or budget to take it on, we'd be very, very
53:31
happy to have a conversation. Every non nonprofit needs an app
53:37
for fundraising. Is that something that you could
53:39
build for them? Yeah, absolutely.
53:42
I think that's, I think that's a great use case.
53:44
It's definitely something that has been brought up many times.
53:47
We haven't taken on a customer building that use case yet, but
53:53
definitely something that we'd be happy to support.
53:55
OK, amazing. OK, cool.
53:58
And I'm, I'm going to share that message because I think that's
54:01
that's really cool. You know, and I know there's
54:03
folks out there that can take advantage of that.
54:05
So, so please take advantage of that.
54:07
Ladies and gentlemen, as we're wrapping up here, I want to make
54:11
sure that everyone I'm going to repeat the website with was
54:15
WITHWO z.com. What's the best place for people
54:18
to connect with you guys personally online?
54:21
Yeah, feel free to connect with us on LinkedIn.
54:23
You can also send us an e-mail founders@withwas.com and that'll
54:28
go to both Brad and I. Yeah, or Twitter works as well.
54:33
OK, and I'll make sure that there's links to everything in
54:36
the show notes. You guys, thanks so much for
54:38
coming on the show and goofing around with me a bit.
54:40
This was super fun. Yeah, it's been fun.
54:42
Thanks for having us. Super nice to meet you Ryan, and
54:45
I look forward to the episode. Hey founders, let me ask you
54:50
this, are you building with AI or getting left behind by it?
54:54
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54:58
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