coding-workflow

Multi-agent AI coding coordination is managed by enforcing a structured workflow that routes tasks, verifies outputs, and tracks progress to a merge-ready state. Confidence-based routing decides when to auto-execute or escalate to human review.

Confidence-based routing in an AI coding workflow evaluates task confidence to decide whether to auto-execute code generation or escalate to human review. This mechanism prevents regressions by enforcing output verification before merging.

Context across multi-step AI coding tasks is maintained through session management, which preserves state between steps and reuses sessions for efficiency. This ensures traceability when multiple agents handle linting, refactoring, and testing.

ACP coding workflows support feature building by coordinating specialized agents for linting, refactoring, and testing. The workflow standardizes prompts and enforces output checks to track progress toward a verifiable, merge-ready state.

Explicit prompts are required to prevent regressions in AI code generation, as the workflow standardizes prompt structures and enforces output verification. This ensures generated code meets quality constraints before merging.

A structured AI coding workflow may not suit simple, single-agent tasks that lack multi-step verification or session management needs. It is designed for complex scenarios requiring confidence-based routing, explicit prompts, and traceable merge outcomes.