A technical cofounder who builds AI-native from day one.
You own the vision and the customers. We own architecture, the build, and the hard technical calls — and ship an MVP that’s AI-native from the foundation, not bolted on later. Fixed price or fractional. You own everything.
The technical half, without the wrong full-time hire.
Hiring a cofounder or first CTO is a bet you make before you can evaluate it. This is the alternative: senior engineering on day one, the early decisions made right, and a clean exit when you’re ready for your own team.
Architect + first build
We make the early technical calls you can’t take back later — stack, data model, auth, the shape of the product — then ship the first version with paying users on it. Not a prototype that gets thrown away. The thing you keep building on.
AI-native from the foundation
AI isn’t a feature we bolt on at the end. It’s in the data model, the workflows, and the product surface from week one — so your edge compounds instead of becoming a “v2 we’ll get to.”
The technical half, until you have a team
You own the vision and the customers. We own architecture, build, and the hard technical decisions — and when it’s time to hire your own engineers, we hand off clean and step back. No lock-in.
What “AI-native” actually means.
The phrase is everywhere and means almost nothing. Here’s the version we build to — concrete enough to argue with.
AI-native, not AI-bolted-on
Most products add an “AI feature” to a design that assumed humans did everything. AI-native means the opposite: you design the workflow around what models do well — drafting, classifying, extracting, routing — and keep humans on the judgment that matters. The architecture assumes AI from the first commit.
Your data is the moat
The durable edge isn’t the model — everyone rents the same models. It’s the proprietary data and feedback loops you capture by running. We build the product so that every interaction makes the next one better, and that compounding belongs to you.
Evals before features
Anything LLM-shaped ships with a written-down evaluation suite and guardrails. If we can’t measure whether the model is doing the job, it doesn’t go in front of your users. AI-native means measurable, not magical.
Boring infrastructure, sharp edges
Go, TypeScript, React, Postgres — the durable parts stay boring on purpose. The AI tooling does the heavy lifting on top of a foundation that won’t need a rewrite the week after you raise.
More on where this pays off: Where AI compounds →
Pick a starting point.
Fixed quote in 48 hours. Scope changes are a conversation, not a surprise invoice.
Your first real version — AI-native from the foundation, built to ship to paying users, not to demo.
- Architecture + data model
- Auth, billing, core flows
- AI woven in where it compounds
- 30 days of post-launch support
We act as your technical cofounder — roadmap, architecture, build, ship — until you’re ready to hire your own team.
- Weekly cycles, weekly demos
- Architecture + code ownership
- Fundraise-ready technical story
- Clean handoff when you hire, 30-day notice
Already shipping? A focused read on where your product should be AI-native — and where it shouldn’t. Written report, ranked plays, no upsell.
- Product + architecture review
- Ranked AI-native opportunities
- Effort/impact estimates
- 1-hour debrief call
Founders with a real market and a missing technical half.
Non-technical founder with a real market
You understand the customer and the problem cold, you have funding or revenue, and the only thing between you and a product is the technical half. You don’t want to hire a CTO you can’t evaluate — you want someone who ships.
Solo technical founder who needs leverage
You can build, but you can’t build everything and sell at the same time. You want senior engineers who plug in, make the AI-native calls with you, and move the roadmap while you’re in front of customers.
A product that should have been AI-native
You shipped a v1 before the AI shift, and now “add AI” keeps landing as a bolt-on that never quite lands. You want someone to rethink the workflow from the model out — without a full rewrite if one isn’t warranted.
Funded, with a deadline that’s already real
You’ve raised on a milestone, the clock is running, and you can’t afford a six-week hiring cycle followed by a six-week ramp. You need the build to start now and a working demo every week.
Senior engineering now. A clean exit later.
We run the same way we do for engineering teams: your branch, your review, your CI, a working demo every week. Led by Ryan Hill with a vetted bench of senior engineers across backend, infra, AI, and product. One point of contact, the right brains on every problem — and documentation in your repo from week one so you’re never dependent on us to keep moving.
Common questions.
Are you a cofounder or a vendor?
Do you take equity?
What does “AI-native” actually change about cost or timeline?
What happens after we raise and hire engineers?
Who owns the IP?
Will the MVP survive contact with scale?
Have a product to build?
A 30-minute founder call. Bring the idea and the deadline — we’ll tell you straight what we’d build, how AI-native changes it, and what it costs.