aidlc-workflows README

The project's README from github.com/awslabs/aidlc-workflows. As one markdown file: README.md.

AI-DLC - one core, many harnesses

AI-DLC (AI-Driven Development Life Cycle) turns AI coding assistants into structured, verifiable software-delivery workflows. One harness-neutral core runs natively in Claude Code, Kiro CLI, Kiro IDE, Codex CLI, Cursor, opencode, and GitHub Copilot.

version license

The Quick Start below installs the latest stable AI-DLC release.

Quick Start

1. Install AI-DLC

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 installer adds the native aidlc command and every harness runtime. Bun and Node.js are not required. If your shell cannot find aidlc, follow the PATH instruction printed by the installer or start a new shell.

Prefer to manage the project files manually? Install the matching native aidlc command, download aidlc-runtime-X.Y.Z.tar.gz from the release, and copy runtime/<harness>/ into your project.

2. Configure a project

From the project root, select the harness you use:

cd /path/to/your-project
aidlc config --harness claude
aidlc doctor

Replace claude with kiro, kiro-ide, codex, cursor, opencode, or copilot. Running aidlc config without --harness starts the interactive setup when a terminal is available.

3. Start a workflow

Open your harness in the configured project and describe the work:

/aidlc Build a REST API for inventory management

Codex CLI uses $aidlc instead of /aidlc. AI-DLC selects a workflow from the request, asks for missing decisions, and stops at approval gates before moving forward.

For provider setup, trust prompts, and harness-specific prerequisites, use the guide in the table below. The complete walkthrough is in Getting Started.

Pick your harness

Harness Configure Open Invoke Guide
Claude Code aidlc config --harness claude claude /aidlc Getting Started
Kiro CLI >= 2.6 aidlc config --harness kiro kiro-cli chat /aidlc Kiro CLI
Kiro IDE aidlc config --harness kiro-ide Open the project /aidlc Kiro IDE
Codex CLI >= 0.145.0 aidlc config --harness codex codex $aidlc Codex CLI
Cursor aidlc config --harness cursor Open Cursor or run agent /aidlc Cursor
opencode >= 1.17 aidlc config --harness opencode opencode /aidlc opencode
GitHub Copilot CLI >= 1.0.74 / VS Code >= 1.130 aidlc config --harness copilot Copilot CLI or VS Code /aidlc GitHub Copilot

Model-provider setup belongs to the harness. Claude Code and the shipped Codex configuration default to Amazon Bedrock; GitHub Copilot uses GitHub sign-in or BYOK; Kiro, Cursor, and opencode use their configured provider. The methodology itself is provider-independent.

AI-DLC works best with capable reasoning models. The current recommended model is Claude Opus 4.8.

Why AI-DLC

Ad-hoc AI coding loses context as projects grow. AI-DLC keeps requirements, decisions, implementation, tests, and operational work connected through one audited lifecycle:

Start with Workflow Profiles to compare Classic, Express, and the focused workflows. See the AI-DLC Workflows 2.0 Specification for the architecture and methodology.

[!IMPORTANT] Generative AI can make mistakes. Review generated output and costs before acting on them. See the AWS Responsible AI Policy.

Documentation

Guide Use it when
Getting Started Installing, configuring, and running your first workflow
User Guide Using workflows, profiles, agents, knowledge, and approval gates
Harness guides Handling provider, trust, and runtime differences
Install and Lifecycle Updating, pinning, installing offline, using mirrors, or uninstalling
Harness Engineer Guide Reshaping stages, agents, rules, sensors, and knowledge
Developer Reference Changing the engine, hooks, packaging, or tests

Repository Layout

Edit core/ or harness/<name>/, never generated dist* output.

Development

Install dependencies and generate every harness:

bun install --frozen-lockfile
bun scripts/package.ts

Useful commands:

bun scripts/package.ts <name>     # generate one harness
bun scripts/package.ts --check    # determinism guard
bun tests/run-tests.ts --ci       # smoke, unit, and integration
bun tests/run-tests.ts --release  # full release acceptance

See the Contributing Guide for the complete development workflow and Porting to a New Harness to add another runtime.

Troubleshooting

Run aidlc doctor from the project root first. Common fixes:

Symptom Fix
aidlc is not found Apply the PATH instruction printed by the installer or start a new shell
Project/runtime version skew Finish the active workflow, then run aidlc config
Codex hooks do not run Trust the project hooks as described in the Codex guide
Bedrock access fails Enable the configured models and verify AWS credentials and region
Plugin stages disappear after refresh Run /aidlc plugin sync
Refreshed skills do not take effect Start a new harness session

See Troubleshooting for diagnostic and recovery procedures.

References

aidlc-workflows (awslabs/aidlc-workflows)

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Aidlc-workflows
What is this?AI-DLC turns AI coding assistants into structured, verifiable software-delivery workflows, running a single harness-neutral core across Claude Code, Kiro, Codex CLI, Cursor, opencode, and GitHub Copilot.
Is this a standalone app or does it plug into my existing coding agent?It is not a standalone app; it is a harness-neutral workflow engine (14 agents, 33 stages, 95-event audit trail) that installs as a set of rules/commands inside agents you already use, like Claude Code, Codex, or Cursor.
How do I install and start a workflow?Run the macOS/Linux/WSL install script or the Windows PowerShell installer to get the aidlc command, then from your project root run 'aidlc config --harness claude' (or kiro, codex, cursor, opencode, copilot), open that harness, and invoke '/aidlc' (or '$aidlc' in Codex) describing the work.
Which coding agents are supported, and do I need to set up a model provider myself?Supported harnesses are Claude Code, Kiro CLI/IDE, Codex CLI (>=0.145.0), Cursor, opencode (>=1.17), and GitHub Copilot CLI/VS Code; the model provider is configured per-harness, with Claude Code and Codex defaulting to Amazon Bedrock and Copilot using GitHub sign-in or BYOK.
Does it just run on its own, or do I need to babysit it?AI-DLC stops at human approval gates before moving forward between stages, and the README explicitly warns to review generated output and costs before acting on them.
What model does AI-DLC recommend for best results?The README currently recommends Claude Opus 4.8 as the model best suited to AI-DLC's reasoning-heavy workflow steps.
Why would I use this instead of just chatting with my AI coding agent directly?Ad-hoc AI coding loses context as a project grows; AI-DLC keeps requirements, decisions, implementation, tests, and operations connected through one audited lifecycle of 5 phases, 33 stages, 14 agents, and 11 workflow profiles.
What kinds of workflow profiles does it ship with?There are 11 workflow profiles covering features, bug fixes, infrastructure, security, proofs of concept, enterprise delivery, and other common work, including lightweight 'Classic' and 'Express' variants.
What do I do if the aidlc command or a harness integration breaks?Run 'aidlc doctor' from the project root first; common fixes include re-applying the installer's PATH instruction, re-running 'aidlc config' after version skew, trusting project hooks in Codex, or starting a new harness session after a refresh.
What are similar projects?orca, pstack-claude, pstack, munder-difflin, no-mistakes, vicoa, operator-memory, compound-engineering-plugin
Which topics is it in?harness-engineering, github-copilot, aws, harness, opencode, workflow, workflow-automation, cursor, coding-agent, codex, agent, claude-code
Creator
awslabs
Size
108.2 MB
Stars
5.4K
Updated
CommitOct 17Releasev2.11.0Oct 08
Age
11mo
Commits · 90 Days