AWS's AI-DLC turns AI coding assistants into audited delivery pipelines
Aidlc: Adaptive workflow steering rules for AI coding agents
AI-DLC is an open-source methodology from AWS Labs that gives AI coding assistants a structured, verifiable software-delivery lifecycle. One harness-neutral core runs natively in Claude Code, Kiro CLI, Kiro IDE, Codex CLI, Cursor, opencode, and GitHub Copilot. It spans 5 phases and 33 stages, with 14 agents, 11 workflow profiles, human approval gates, and a 119-event audit trail. Install via curl or PowerShell, configure a harness, and start with /aidlc.
Ad-hoc AI coding loses context as projects grow. AI-DLC keeps requirements, decisions, implementation, tests, and operational work connected through one audited lifecycle.
- bessbd
> 5 phases and 33 stages from initialization through operation
> 14 agents: 11 domain experts, 2 reviewers, and an adaptive composer
wow, that's a lot of domain experts, I'm convinced
- daitangio
I prefer https://github.com/Fission-AI/OpenSpec because it works also on brown-field.
If you want an unbias-demo, take a look also at
https://github.com/daitangio/take-ai-control/tree/demo/nello...
branch demo/nello-openspec
- ernsheong
I'm not sure that it needs to be this complicated. But yes, I am interested in the problem of hard guardrails between multiple agents, and it is not an easy problem to solve.