We build with founders. Not for clients.
Most startups hit a wall because the foundation they shipped at speed can't carry what comes next. We take the CTO seat at early companies, build the layer underneath, and take a stake in what gets built. That foundation now includes AI. Build without it and you ship something already dated.
- Platform
- .NET 10 · ASP.NET Core
- Data
- SQL Server 2025
- Cloud
- Microsoft Azure
- Role
- Fractional CTO — in the seat, in the repo
- AI
- Designed in, not bolted on
- Position
- Equity, not invoices
few years; the bottom is what companies rewrite at the worst
possible moment, or never have to. AI cuts through all four —
it is not a layer you add on top.
We're in it, or we're not in it.
We don't take briefs and hand back a codebase. We join a small number of companies a year — in the CTO seat, in the repository, and on the cap table.
We take the CTO seat
Fractional CTO for companies that need senior technical judgment now and can't yet hire it full time. You get the seat filled, not a report about filling it.
- AThe architecture calls that are expensive to reverse
- BHiring engineers, and knowing who is actually good
- CThe technical answer in the room when investors ask
And we build it too
Leadership that never touches the code goes stale within a quarter. We stay in the repository, so the plan and the thing being built remain the same thing.
- AWe join early, while foundations are still cheap to get right
- BWe sit in the product decisions, not just the ticket queue
- CWe hold a stake, so we're paid when the company works
Sometimes the founder is us
When we see a problem worth solving and nobody is solving it well, we start the company ourselves and run it as a product.
- ACommercial software in production with paying customers
- BCompliance and document-heavy markets others avoid
- CWhere the standards we bring to partners came from
AI isn't a feature. It's foundation.
A product designed without AI at its core is already behind on the day it launches. We build it into the model from the start — and we use AI to do the building, which is how a small team delivers like a larger one.
Designed in from the schema up
AI capability belongs in the data model, not appended to a finished product. What it reads, what it decides, what it must never guess — and which model does each job — are foundation decisions, made before the first screen exists.
- ADocument understanding and structured extraction
- BClassification and matching against reference data
- CModels picked per task, not one vendor stretched across everything
- DEvery result sourced, checked, and correctable by a human
A small team that delivers like a larger one
AI carries the mechanical work — scaffolding, schema, tests, first-pass review — so senior judgment goes where it compounds. For a company we hold a stake in, that difference is runway.
- AAnthropic’s Claude as our development AI, reviewed line by line
- BTests written alongside the code rather than promised for later
- CHuman judgment on the parts AI gets confidently wrong
What we have a stake in.
Companies we co-founded, companies we build with, and products we run ourselves.
Narrow on purpose.
One ecosystem, known end to end. A company we back doesn't get whatever is fashionable — it gets a stack we can still operate at scale in five years.
| Layer | What we use |
|---|---|
| Runtime | .NET 10 — ASP.NET Core, MVC, minimal APIs |
| Data | SQL Server 2025 — schema design, tuning, native JSON |
| Cloud | Azure — SQL, Blob Storage, App Service, Entra ID |
| Embedded AI | Models chosen per job on best fit — Anthropic, Azure AI, and others |
| Toolchain | Built with Anthropic's Claude — every generated line reviewed |
| Structure | Microservices with bounded contexts and clean seams |
| Delivery | GitHub Actions — every build versioned to its commit |
| Testing | Unit, integration, and Playwright end-to-end |
Show me your tables [the data model], and I won't usually need your flowcharts.Frederick P. Brooks, Jr.
Our founder studied under Brooks at UNC. It's the first question we ask a founder — and the reason we start with the data model, not the screens.
What we're like to build with.
Not slogans. These are the habits that decide whether a company can still move quickly in year three.
Foundation before features
Speed early is fine. Speed on a wrong data model is a rewrite you'll pay for right when you can least afford it.
We're paid when it works
Holding a stake changes the advice. We'll argue against work that bills well and builds nothing, because it costs us too.
Built to be taken over
Every build is versioned to its commit and tested where it counts, so your own team can pick it up without a hostage negotiation.
Tell us what you're building.
We take on very few companies a year. Send us the idea and where you are with it, and we'll tell you straight whether we're the right partner — and what we'd want to own.