aidlc-full-cycle

Orchestrate the complete AI development lifecycle by initializing a Knowledge Base first, then coordinating feasibility, specifications, phase gates, and knowledge continuity. This enforces strict governance and controlled agent execution to preserve human leadership throughout the project.

Enforce phase gates and Go/No-Go decisions by applying a full-cycle methodology that compresses ideas, validates feasibility, and requires explicit sign-off before coding begins. This ensures structured, human-led governance across the entire AI project lifecycle.

You need a Knowledge Base for AI project governance when starting new client engagements, RFPs, or internal initiatives. Initializing it first guarantees institutional memory, traceability, and serves as the spine for all phased planning and decision-making.

Start a new client engagement by providing a Phase 0 intake and feasibility plan using the full-cycle methodology. This compresses the initial idea and validates feasibility before signing off on the Go/No-Go gate and proceeding to specifications.

Yes, you can use controlled agent execution where the orchestrator defines the direction and agents execute within defined boundaries. This approach maintains strict phase gates and ensures human leadership is preserved throughout the AI development lifecycle.

A strict phase gate methodology requires explicit Go/No-Go sign-off before coding begins, which may slow down rapid prototyping. It is designed for phased planning and governance, meaning it enforces boundaries that might constrain highly exploratory or unstructured development.