AWS AI-DLC Workflows
AI-Driven Development Life Cycle — a prompt/rules package that steers an AI coding agent through Inception, Construction, and Operations phases, emitting reviewable markdown artifacts at each human-gated stage. Not a CLI or MCP server: activated in-agent with the phrase "Using AI-DLC, ...".
Detection
A project uses AI-DLC when any of these exist:
- aidlc-docs/aidlc-state.md
- .aidlc-rule-details/
- .kiro/aws-aidlc-rule-details/
- .amazonq/aws-aidlc-rule-details/
- **/aws-aidlc-rules/core-workflow.md
Status Model
Method: task-checkboxes
Parse the "## Stage Progress" checklist in aidlc-state.md (respecting SKIPPED as done/not-applicable), then refine per-unit progress from the checkbox ratio in each construction/plans/<unit>-code-generation-plan.md. Formats are LLM-generated markdown — match checkboxes plus the keywords COMPLETED/SKIPPED/IN PROGRESS rather than exact headings.
Lifecycle
- 1 Inception
Planning — WHAT & WHY. Workspace detection, (brownfield) reverse engineering, requirements analysis, user stories, workflow planning, application design, and units-of-work generation.
- 2 Construction
HOW — per unit of work: functional design, NFR requirements and design, infrastructure design, code generation, then build and test.
- 3 Operations
Reserved for deployment and monitoring (placeholder in current release).