AI-DLC Documentation
AI-DLC is a structured, gated methodology for AI-driven software development. This repository runs it natively in Claude Code, Kiro CLI, Kiro IDE, Codex CLI, Cursor, opencode, and GitHub Copilot.
Quick Start
1. Install
macOS, Linux, or WSL:
curl -fsSL https://github.com/awslabs/aidlc-workflows/releases/latest/download/install.sh | sh
Windows PowerShell:
irm https://github.com/awslabs/aidlc-workflows/releases/latest/download/install.ps1 | iex
The native installer sets up everything AI-DLC needs, every harness runtime
included; you do not need to install Bun or Node.js. On Windows, it installs for
the current account and automatically
registers the bin directory in User PATH; run it from a normal PowerShell window,
since one opened with "Run as administrator" gets a warning and a prompt. A
terminal app or IDE that was already open keeps its old PATH, so quit and reopen
it before using aidlc there; a new tab inside it is not enough. Use
-NoModifyPath to skip
both persistent and current-process PATH changes.
2. Configure
Run from your project root:
aidlc config --harness claude
aidlc doctor
Replace claude with kiro, kiro-ide, codex, cursor, opencode, or
copilot. A bare aidlc config starts the interactive setup.
3. Start
Open the configured harness and describe the work:
/aidlc Build a REST API for inventory management
Codex CLI uses $aidlc. See Getting Started for
provider setup, trust prompts, project refreshes, and the first workflow.
Choose Your Harness
| Harness | Guide |
|---|---|
| Claude Code | Getting Started |
| Kiro CLI | Running AI-DLC on Kiro CLI |
| Kiro IDE | Running AI-DLC on Kiro IDE |
| Codex CLI | AI-DLC on Codex CLI |
| Cursor | AI-DLC on Cursor |
| opencode | AI-DLC on opencode |
| GitHub Copilot | AI-DLC on GitHub Copilot |
Choose Your Guide
| Guide | Use it when |
|---|---|
| User Guide | Building software with AI-DLC |
| Onboarding Walkthrough | First-time team? The mental model and a guided five-run path |
| Workflow Profiles | Choosing Classic, Express, or a focused workflow |
| Facilitator Guide | Running a workshop or supporting a team: readiness check, recovery playbook, harness comparison |
| Install and Lifecycle | Updating, pinning, installing offline, using mirrors, uninstalling, or removing AI-DLC from a project |
| Harness Engineer Guide | Reshaping stages, agents, scopes, rules, sensors, or knowledge |
| Development and Releases | Taking a PR through AI review, preview testing, and stable publication |
| Developer Reference | Changing the engine, hooks, packaging, or test suite |
Development
Maintainers author in core/ and harness/. Generated dist/ and
dist-release/ trees are local outputs and must not be hand-edited.
See the Contributing Guide for the development workflow and Porting to a New Harness to add another runtime.