Most AI-assisted development runs on prompts and chat. It's quick, but there's no plan connecting one step to the next, so the work is hard to check and harder to trust. Model 2 is our method for making AI-assisted development dependable enough for a regulated institution.
Chat-driven AI work has no shared source of truth, so each step can drift from the one before it.
Reviewers see large volumes of generated output with little context about why it was produced.
When AI writes the work, it becomes unclear who the author of record is.
Model 2 is a spec-driven development method. A single specification becomes the contract between every stage of delivery, and the AI works to that contract instead of an open-ended conversation.
Each stage builds on the approved output of the one before it, so the work can't drift.
Reviewers check the work against the specification instead of reading generated output cold.
Each change links back to the part of the specification that called for it.
The AI works to the specification, flags what's unclear and never skips a gate.
Every accelerator on this page started as a problem we needed to solve. If you’re facing a similar one, we’ll show you the working version and help you judge whether it fits.
A live 30-minute walkthrough of any accelerator on synthetic data, with the engineers who built it.
A working session to match your use case to what the lab has proven, and to be clear about what it hasn’t.
A time-boxed pilot in your environment, with the evidence trail your risk team will ask for.
