Specs are the native operating layer for reliable AI coding.
Agentic coding gets messy when every task starts from a one-off prompt. fabriqa.ai makes the spec native to planning, routing, execution, and review.
Agents execute with context. Humans review with confidence.
The spec-native loop
From intent to shipped code in four steps.
Capture intent.
Turn product goals into requirements, constraints, and acceptance criteria a person and an agent can both read.
Decompose into tasks.
Break the spec into implementation, testing, review, and documentation work with explicit boundaries and outputs.
Route to the right agent.
Each task goes to the agent best suited for it, with shared context and provider history preserved across handoffs.
Review against the spec.
Diffs are evaluated against acceptance criteria, not against the last prompt. Anything that drifts gets routed back.
The contrast
Without specs, agents drift. With fabriqa.ai, they ship.
Plausible work that misses the goal.
Agents generate code that looks right, skips edge cases, ignores acceptance criteria, and optimizes for the last prompt instead of the real product intent.
Execution stays anchored to intent.
The spec is native to planning, execution, and review. Each agent has a clear task, and every change can be checked against the same source of truth.