Route
Classify the change as Brownfield, Greenfield, or Config/Infra before generation starts.
AI coding assistant governance
Govern AI coding assistants without locking into one model or vendor.
Teams are using Claude, Codex, GitHub Copilot, Amazon Q Developer, and other assistants. AIDLC Studio gives them one workflow language for scope, risk, review, evidence, release, and learning.
Operating model
One governance layer across many assistants
Contract
Give the assistant a model-agnostic prompt contract with allowed scope and non-goals.
Review
Require human explanation, tests, dependency checks, and product acceptance.
Evidence
Record what was accepted, changed, rejected, tested, released, and learned.
Start
Recommended AI coding assistant governance path
01Generate workflowStart with route, risk, and evidence requirements.02Preview repo instructionsUse AGENTS.md, CLAUDE.md, or PR templates.03Use scenariosApply common playbooks for refactors, dependencies, config, and release evidence.04Measure maturityUse shareable score output for leadership and team planning.
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