Can One Person Build a Billion-Dollar Startup? — The General Intelligence Company of New York

[music] My name is Andrew. Uh, and I'm going to be talking about how we go from here to the oneperson billion-dollar company.

Now, a little bit about ourselves. We

founded the general intelligence company in New York about a year ago. I'm going

to call it general intelligence because I only have so many words I can say. Our

mission is to enable the oneperson billion dollar company. We want to build uh organizations that run themselves with AI. There's a number of ways we're

with AI. There's a number of ways we're going to get there. I'm going to talk about them, but first a little bit about myself. Um, this is my second company.

myself. Um, this is my second company.

Uh, I've been CEO since I was 18. I

dropped out of college. About the world.

Now, in a couple years, we're going to start seeing all of this stuff um come together. So, agents finally work. They

together. So, agents finally work. They

can do basically anything you want them to do. What happens next? Well, we're

to do. What happens next? Well, we're

going to start seeing companies change a little bit. And eventually we'll have

little bit. And eventually we'll have one person that can run a company that's very wide and very I guess large in operations run by just one person and then below that will be a bunch of

agents. Um vertical agents like customer

agents. Um vertical agents like customer support, finance, marketing and things like that will be run on on their own and then there's going to be coordinators or like managers above them

and uh that's where we're focusing is the manager agents and the interface in which the people are going to use them.

So think about us like the like the the middle management layer and then we want to use other people's agents for things on the bottom. We don't want to make every agent for everything. That

wouldn't be possible. But let's talk about co-founder. So co-founder was our

about co-founder. So co-founder was our first product. We created it back in uh

first product. We created it back in uh September. We launched on September 8th

September. We launched on September 8th and uh it was like an assistant where you can go and you can run agent across a computer in the cloud. It's got

state-of-the-art memory so it knows about you. It can draft emails. It

about you. It can draft emails. It

really read like you. And so people were using it for all sorts of stuff. Um they

were using it to make their uh email spam for their sales thing work. They

were using it to look up candidates on LinkedIn. Some people just started

LinkedIn. Some people just started giving it API keys which we told them not to do but they keep trying to do it.

It was able to like automate different pieces uh of a company and people really liked it. So it was pretty successful.

liked it. So it was pretty successful.

We've had over 8,000 startups use co-founder to automate their operations which uh was was pretty fun. Um, we

learned a lot in that and we were able to just workbench on this state-of-the-art agent and get it to do really difficult things. An assistant is not a company, right? I got up here and

told you we're going to make one person billion dollar companies. Well,

something that writes your emails better is not a company. What is a company?

This is the question we started asking ourselves. And we wanted to figure out

ourselves. And we wanted to figure out how to go from co-founder to our vision of, you know, this this one person billion dollar company. And so we came up with this framework. Um this is for product based companies or services

companies which are different but you create a product you sell it you support it and then you operate. So you know in very simple terms this is an entire company. If you can create something

company. If you can create something like a piece of software and then you can go and sell it to people that give you money and then you can make sure that they keep giving you money and then you can exist. That's basically what I

do all day long as a founder is is these three things. These four things. Then we

three things. These four things. Then we

moved on to like how do we do what's next which is step one and that's creating a product and that's what I'm going to show you guys today is kind of some of our approaches there. Back in

the summertime we used co-founder to make a version of fully automated feature development. This was back like

feature development. This was back like two generations of models ago but we were able to set up these automations where let's say uh an email comes in with a bug report or a feature. We can

pull in some data. We can make a report on that and create a linear ticket to to track the feature. Then we can use Slack to kick off Devon to go code a fix and then update the ticket when it's done.

And then we were able to hack together this thing where we would generate a QA test list to see how how do you test this thing that you just got this report on and then actually use a browser agent

to see if we could get it to work. And

so this was a way of going from, hey, here's a bug report in an email all the way to it's now coded and merged and you have a browser that's using it. When we

started looking at this, we started thinking about, okay, well, you you kind of need a management layer. So, you need a manager that looks over these things like your product agent or your your

email agent or your your your coding agent to be able to actually work on these things, which is like, how do I make the product better? How do I get it

to a system where there's no bugs in it and it just runs itself? And this wasn't really possible in the summertime. It's

become more possible now. You can scale this all the way up. So, you know, if you have one agent that can manage another agent, you can have an agent on top that manages all of that. And this

is kind of what we we call super optimization. And so here's how it would

optimization. And so here's how it would work today with a system that was able to have a manager agent as well as a couple of lower level agents doing

things like code generation and browser testing. So you take claude to write

testing. So you take claude to write your code, use browser base to run a browser and then you deploy it with something like Verscell and then you manage that all together to be able to

develop products autonomously. This is

brand new. You guys are the first people seeing this actually. Uh, our alpha comes out today. This is the first fully autonomous engineering department. It's

all in the cloud and it allows you to build features, test them, deploy them, manage infrastructure, and run a software company autonomously. This is

our new product called co-founder CTO.

We've got a couple of other things coming out later that we'll play on this word, but you know, I have a co-founder and CTO. You might notice this doesn't

and CTO. You might notice this doesn't really look like an assistant, right?

This is kind of like a canvas. And you

know what it does look like? It looks

like a video game. And that's what we've developed it based on. We looked at couple games like Starcraft and Civilization. This has become a very

Civilization. This has become a very popular thing to talk about over the last couple of weeks, but uh we were doing this back in December. And you can spin up an agent that will code a

feature and then it will go through the entire life cycle of that feature and then uh merge it automatically. So, I'm

going to take this one and I'm going to copy it and we're going to show it from scratch. So, you create a new task.

scratch. So, you create a new task.

You've got your repository that you can assign it to. So, I'm going to select super optimizers, which is our our current repository. And I'm going to say

current repository. And I'm going to say make the blur on the canvas when a node is selected a bit darker. This means

white overlay instead of instead of white. We have a couple different ways

white. We have a couple different ways of doing this. I'm not very good at specifying my tickets, but like my co-founder Obby, who's much smarter than I am, will write very long ones and

it'll have many of these going all day.

This is going to take a minute. It's

agents running. It's going to go and it's going to start looking for repositories and then it's going to delegate to a coding agent and then that coding agent is going to actually code

this feature. Now, it's run this coding

this feature. Now, it's run this coding agent. I believe it's going to run

agent. I believe it's going to run claude code. Um, and all this is in the

claude code. Um, and all this is in the cloud. So you don't have to have a

cloud. So you don't have to have a computer locally. This is one of the

computer locally. This is one of the things that we decided we didn't want to do. So I was trying to figure configure

do. So I was trying to figure configure cursor cloud agents and I wasn't able to um because getting local development to work on on their cloud agents is just very broken. Okay, we've got cloud code

very broken. Okay, we've got cloud code running here. Um and we decided that

running here. Um and we decided that since local development was really hard, we would just get rid of it. CTO doesn't

use any local development at all. It

uses these things called preview environments. Every time a coding agent

environments. Every time a coding agent is spun up, it will make a PR and it will send it to your repository and then every PR is hosted like your production

and then it's put on on the web. So if

you have loginins for that, your agent can then use the login there. There's no

local development at all. It all happens in the cloud. Okay, so now we got cloud code running. Now it's going it's

code running. Now it's going it's looking at different things. It's

looking at colors and when it's done with this, it'll spin up a browser agent. We have it so that every time

agent. We have it so that every time it's spin up, it spins up a browser. And

so I'll be able to show you that right here. And this browser session all

here. And this browser session all happens automatically. So the agent goes

happens automatically. So the agent goes in, it logs in with your credentials.

And you can see this is like a little version of your app that's running in the cloud. And so we have this browser

the cloud. And so we have this browser agent go and test your feature. And this

one determined that it actually wasn't able to ask the the completion. It said

it wasn't wasn't good enough. So, it

went back up to the browser agent and it told it or it went back up to there, told it to code something again and then it did the browser agent again and then it worked. Now, it's tested it. It

it worked. Now, it's tested it. It

merges it successfully and that is now in your app. Now, I don't have that much time left so I'm going to show you some of the other stuff as well. We've also

added infrastructure monitoring. All of

your infrastructure can be monitored by CTO as well. So we also monitor infrastructure and whenever something happens, so we've got Verscell alerts and Versell deployment failures, uh it

will spin up an agent automatically and fix them so that you don't have to have a uh a person monitoring this infrastructure. And so you can now go

infrastructure. And so you can now go and ye features into your app and they get merged automatically and you have another agent that makes sure that your app doesn't break. that that means you can just send a bunch of features to

your app and develop at a very fast speed. You can also monitor the

speed. You can also monitor the deployments here. Um spin up agents

deployments here. Um spin up agents below that. But yeah, so there's a

below that. But yeah, so there's a there's a quick demo of CTO. We'll have

a much slicker, cooler looking version in a couple of weeks. Yeah. So it it plans and delegates, uses coding agents, uses Versell preview environments, and then watches the deployment, then writes

a testing plan, uses a browser agent to test, merges, and checks the infrastructure. Yeah, like I mentioned,

infrastructure. Yeah, like I mentioned, our team is 400% faster compared to before we launched this. So, we use this internally. Um, this number is actually

internally. Um, this number is actually out of date. We have an average of like 25 PRs per engineer per day. We've

started spending more on tokens than on on salaries depending on the day.

Sometimes we'll spend like I don't know like I think today we spent 4 grand on tokens on Opus tokens. Some days it'll be less. But this shows that we're

be less. But this shows that we're starting to shift our human capital to intelligence. I just showed you how to

intelligence. I just showed you how to make products but that's not a whole company, right? There's a couple other

company, right? There's a couple other pieces of a company that you need. Now,

some people disagree with us on that, but we said you need to sell the product, support the product, and operate. And we're not just making an

operate. And we're not just making an engineering department. We're making

engineering department. We're making everything. So, this is what we're doing

everything. So, this is what we're doing in the next 6 months. Um, you'll be able to try out co-founder CTO on it's I don't know if we're going to make March 1st. We'll make like March 6th. Then

1st. We'll make like March 6th. Then

you'll have customer support so you can build the product and support the product. And then we'll have a full CRO.

product. And then we'll have a full CRO.

uh revenue and sales stack by the summer. Um so yeah, that's that's

summer. Um so yeah, that's that's everything for me. If you want to sign up for the alpha, this QR code right there, it'll give you a Google form.

We'll get you a login. We have to only do a couple people at a time, but you can get on by the end of the week if you're really lucky. Yeah. Thanks

everyone.

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