dev-team

Coordinating multiple AI agents involves assembling a 2-4 role-specific team, including a Checker, to handle phased execution with enforced quality gates for software engineering work. This approach ensures reliable results through role-based task ownership and evidence-backed outputs.

Enforcing code review quality gates requires evidence-based output delivery that demands file and line citations for all claims. This ensures actionable, confidence-based review feedback by applying checker and security reviews where appropriate during the process.

Planning a safe implementation strategy uses a plan-first execution workflow that requires approval before acting on complex or unfamiliar code changes. This reduces rework and unsafe modifications by enforcing phased scoping and deep investigation.

Multi-agent orchestration works for strategy research and communication drafting by classifying the task type first, then assigning role-specific agents to investigate and execute. This ensures evidence-backed outputs tailored to the specific requirements of each domain.

Use multi-agent orchestration instead of a single agent for complex code implementation requiring verified results, deep investigation, and enforced quality gates. It is necessary when tasks demand role-based ownership, phased scoping, and evidence-backed outputs with file citations.