The New Way To Build A Startup

**Garry** (0:00)
If you haven't tried Claude code in the last month, it's time to give it another shot. And if you have, you know what I'm talking about. It feels like AGI is here. One of Anthropix's own engineers writes, Claude wrote Claude Cowork. Us humans meet in person to discuss foundational architecture and product decisions, but all of us devs manage anywhere between three and eight Claude instances implementing features, fixing bugs, or researching potential solutions. Think about what that means. The team developing one of the most sophisticated AI products in the world, something many of you probably use every day, is using this AI internally to improve their product. I think this points to a fundamental shift in how startups operate. Right now, the best teams aren't automating one or two internal functions. They're automating all of them. Often, they're tiny teams able to beat huge incumbents thanks to internal automation. Their leanness is their superpower. I've been calling these startups 20X companies.
Several years ago, my friend Parker Conrad, founder of Rippling and Xanafits, coined the term compound startup to describe companies that build multiple integrated products in parallel rather than focusing narrowly on one thing.

**Parker Conrad** (1:30)
The theory of the compound software business is that there's this island of product market fit that's kind of over the edge of the horizon line that's sort of harder to get to. But if you can build multiple parallel applications at once, you can get there, and it actually ends up being a much more powerful type of product market fit that's much harder to displace at that point.

**Garry** (1:55)
The 20X company could be an evolution of Parker's idea, but applied to internal automation. Instead of just narrowly automating a few things like writing code or handling customer support, 20X companies build automations across all internal features, code, support, marketing, sales, hiring, QA and more. This makes each of their employees orders of magnitude more powerful than they would be otherwise. It also allows them to postpone hiring additional sales and ops staff for much longer, keeping payroll down and culture from drifting. The phrase 20X company was actually coined by the founders of GigaML, which builds voice-based customer service agents for enterprise, to describe how they managed to close DoorDash as a customer, going up against incumbents that were literally 20X as large.

**SPEAKER_3** (2:51)
When we got DoorDash as a customer, we were approximately like four to five engineers going against players who had like 100X engineers. So we kind of like coined the term, like hey, we are a 20X company because we are able to beat these much bigger players who are like 20X us by having a better product and better numbers.

**Garry** (3:08)
Giga was able to close DoorDash and several other Fortune 500 companies as customers because of a powerful internal agent they call Atlas.

**SPEAKER_3** (3:17)
So Atlas can basically do anything within the product which you want to do. So it can use browsers, it can edit the policies, it can write code, it can do anything within the product.

**Garry** (3:28)
Atlas dramatically expands the range of what each engineer can take on.

**SPEAKER_3** (3:32)
So let's say before Atlas, every engineer can probably work on four to five problems at once because they are bottlenecked by all the boilerplate stuff they have to do for the customers. Customers have integration, they would have to probably work on that. Now with AI FD taking care of all the boilerplate stuff, each engineer's scope is basically doubled or tripled because they don't need to work on the boilerplate code.

**Garry** (3:54)
But Atlas doesn't just accelerate Giga's engineers, it also acts as a full-time AI employee that works in tandem with a human FDE to service dozens of accounts.

**SPEAKER_3** (4:07)
Right now we have only a single human FDE within the company. As hard as it's to believe, because we have companies like Doordash using us, we are in pilots with multiple Fortune 500s, 10 plus Fortune 500s, where each of these companies probably have volumes over 500,000 or a million calls a day. It's only been possible because we have Atlas, and this person can primarily focus on just the customer relationships, the ask by the customers, taking customer requests and turning them into feature requests and everything.

**Garry** (4:36)
Building an AI teammate is one approach. Another is to build an AI integrated source of truth that gives employees instant context across your entire system. Legion Health, which is building an AI native psychiatry network, is one example of how to do this. Legion built a custom internal interface for their care operations team that lets them pull patient history, scheduling availability, insurance codes, and a lot more.