Ship the smallest thing that proves the thesis
AI product work sized to runway: the narrowest build that tests the thesis, embedded engineers, and honest build-versus-buy advice.
Sequencing
One workflow, one segment, on a frontier API, with a human in the loop where reliability is not yet earned — shipped in weeks. If the thesis survives, the next build is justified by evidence rather than an architecture diagram.
Buy first
Buy the model, the vector store, observability and auth, and spend the rest on your product. Fine-tuning is nearly always premature: better prompts and retrieval beat it.
First build
4–8 weeks
typical time from scope to an AI feature real users are testing
Venture studio
12
AI-native brands GridStudio has built and operated itself
Embedded
We work in your repository, your standups and your review process, and the code is yours from the first commit. Pairing and a planned exit are part of the engagement.
Moat
What could a funded competitor not replicate in six weeks? Correction and outcome data has to be instrumented early: it cannot be backfilled once the traffic has passed.
Models
Application
Retrieval
Evaluation
Infrastructure
1–2 weeks
A hard look at the thesis, the architecture and the unit economics, with a recommendation on what to stop building.
Build-versus-buy recommendation, defensibility analysis, cost-per-resolution model
4–10 weeks
The narrowest version that tests the thesis, shipped to real users in your repository and owned outright by you.
Shipped increment, evaluation set, cost model, data capture instrumentation
Ongoing
Engineers scaled against runway, or a co-founding arrangement where we contribute product and engineering capacity for equity.
Engineering capacity, pairing and documentation, or deal-by-deal equity terms
Most of the time, at first. If a frontier API meets your latency and quality bar, your volume does not break the economics and your data is not legally trapped, use it and spend the engineering on the product. Fine-tuning and owned GPUs answer specific problems; if you cannot name yours, you do not have one.
You own everything from the first commit — repository, prompts, evaluation sets and weights, with no runtime dependency on us. We also co-found for equity where the fit is right, structured deal by deal with founders keeping control. It is a real commitment, so we decline more often than we accept, and quickly.
If you have strong in-house engineers and a clear thesis, hire another engineer — cheaper, and it compounds. If you are pre-product and changing segment weekly, the constraint is customer conversations, not code. Sometimes the honest answer is a landing page and ten interviews before anything is built.
Regulator, budget, deadline, legacy core, a board that has been burned once already. Tell us what you are working around.
