Aidlc: Adaptive workflow steering rules for AI coding agents

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.

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

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 sets up everything AI-DLC needs: the native aidlc command and every harness runtime. You do not need to install Bun or Node.js; a native install runs its hooks and commands through aidlc and does not call bun. On Windows, it installs for the current account and automatically registers the bin directory in User PATH. Run it from a normal PowerShell window; one opened with "Run as administrator" gets a warning and a prompt, since installing as administrator is less safe. Open a new terminal if another session cannot find aidlc. To skip both persistent and current-process PATH changes, use -NoModifyPath. Windows uninstall removes only the User PATH entry recorded as installer-owned. On macOS, Linux, or WSL, follow the installer's PATH instruction if needed.

Prefer to manage the project files yourself, or cannot install a native executable? The manual-copy path is the one place Bun is needed: install Bun, download aidlc-copy-runtime-X.Y.Z.tar.gz from the release, and copy the complete runtime/<harness>/ directory into your project. This path does not require the native aidlc command.

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. If you use Kiro IDE's own terminal in a project folder you have not trusted yet, Kiro first asks whether you trust it. Choose Trust Folder & Continue only for your own project or one you have checked, because trusting lets the folder's .kiro hooks run commands on your machine; otherwise choose Cancel and review the folder first (see First run).

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. In Kiro IDE, first choose aidlc in the chat panel's agent picker. 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.

Harness Configure Open Invoke Guide

Claude Code aidlc config --harness claude claude /aidlc Getting Started

Kiro IDE >= 1.1.70 / Kiro CLI >= 2.24.1 (v3) aidlc config --harness kiro-ide Open the project in Kiro IDE and choose aidlc in the chat panel's agent picker, or run kiro-cli /aidlc Kiro IDE

Kiro CLI >= 2.6 (legacy) aidlc config --harness kiro kiro-cli chat /aidlc Kiro CLI

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. Shipped project configuration keeps the provider and model already selected by the user. aidlc config providers can apply Amazon Bedrock settings on supported project surfaces or record manual setup for other harnesses. Kiro CLI and Kiro IDE need no provider answer because model access comes with Kiro. On Kiro CLI 2.24.1 or later, use kiro-ide, which pins Kiro's v3 engine; kiro is the legacy row (Kiro CLI says how an existing kiro project switches). The methodology itself is provider-independent.

AI-DLC works best with capable reasoning models. The current recommended model is Claude Opus 4.8. If Opus is not available to you, or you are not sure where to set the model and effort on your harness, see Choosing a Model and Effort.

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.

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

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

Development and Releases Taking a PR through AI review, preview testing, and stable publication

Developer Reference Changing the engine, hooks, packaging, or tests

Repository Layout

core/ - hand-authored, harness-neutral methodology and engine

core/tools/ - 93 aidlc-*.ts engine and authoring tools

harness/<name>/ - thin, harness-specific manifests and integrations

plugins/<name>/ - optional AIDLC plugins

scripts/ - packaging, binary, installer, and release tooling

tests/ - smoke, unit, integration, and end-to-end tests

docs/ - user, harness-engineering, and developer documentation

dist/ and dist-release/ - generated, ignored local outputs

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

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.

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

See Troubleshooting for diagnostic and recovery procedures.