A structured methodology where machine-readable
specifications drive every implementation decision —
for humans and AI alike.
Modern LLMs generate code fast — but fast code that doesn't match the requirements is just technical debt in disguise.
SDD treats the specification as the contract. Every function, every edge case, every constraint is declared upfront — so what gets built is exactly what was agreed upon.
SDD is built on a feedback loop where specifications, tests, and implementation remain in constant alignment — each informing and validating the others.
Specifications are authored in structured, machine-readable markdown — versioned alongside code and treated as the canonical source of behavioural truth before any implementation begins.
Every AI prompt is grounded in the relevant spec — functional requirements, edge cases, and acceptance criteria — before a single line of implementation is generated.
Generated code is validated against the spec automatically. Approved deviations feed back into updated specifications — closing the loop and keeping intent and implementation in sync.
Define behaviour before touching code. Capture functional requirements, constraints, edge cases, and acceptance criteria in structured markdown.
Learn how →Inject the spec into every AI prompt. Generate implementation, tests, and types that are traceable to specific requirements — not just syntactically correct.
Learn how →Run automated checks that map every generated artefact back to a spec requirement. Surface gaps before review, not after deployment.
Learn how →When requirements change, update the spec first. Let the diff drive regeneration — ensuring every downstream artefact stays in lockstep with intent.
Learn how →A closed loop where specifications and code co-evolve — no drift, no guesswork.
SDD is a community-driven methodology. Contribute spec templates, share your workflows, and help define how humans and AI build software together.