aidlc: Adaptive workflow steering rules for AI coding agents

AWS Labs released AI-DLC, a harness-neutral workflow tool that runs natively in Claude Code, Kiro CLI, Kiro IDE, Codex CLI, Cursor, opencode, and GitHub Copilot, installable via a curl or PowerShell script from the awslabs/aidlc-workflows GitHub releases. The native installer sets up the `aidlc` command and all harness runtimes without requiring Bun or Node.js, while a manual-copy path using `aidlc-copy-runtime-X.Y.Z.tar.gz` is the only route that needs Bun. Developers configure a harness with `aidlc config --harness <name>` and invoke work with `/aidlc` (or `$aidlc` in Codex CLI), with AI-DLC selecting a workflow and stopping at approval gates.

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. 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 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 https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/18-install-and-lifecycle.md windows-powershell . 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 https://bun.sh/ , download aidlc-copy-runtime-X.Y.Z.tar.gz from the release https://github.com/awslabs/aidlc-workflows/releases/latest , 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 https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/harnesses/kiro-ide.md 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 https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/01-getting-started.md . | Harness | Configure | Open | Invoke | Guide | |---|---|---|---|---| | Claude Code | aidlc config --harness claude | claude | /aidlc | Getting Started https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/01-getting-started.md | | 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 https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/harnesses/kiro-ide.md | | Kiro CLI = 2.6 legacy | aidlc config --harness kiro | kiro-cli chat | /aidlc | Kiro CLI https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/harnesses/kiro-cli.md | | Codex CLI = 0.145.0 | aidlc config --harness codex | codex | $aidlc | Codex CLI https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/harnesses/codex-cli.md | | Cursor | aidlc config --harness cursor | Open Cursor or run agent | /aidlc | Cursor https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/harnesses/cursor.md | | opencode = 1.17 | aidlc config --harness opencode | opencode | /aidlc | opencode https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/harnesses/opencode.md | | GitHub Copilot CLI = 1.0.74 / VS Code = 1.130 | aidlc config --harness copilot | Copilot CLI or VS Code | /aidlc | GitHub Copilot https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/harnesses/copilot.md | 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 https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/harnesses/kiro-cli.md 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 https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/18-install-and-lifecycle.md 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: - 5 phases and 33 stages from initialization through operation - 14 agents: 11 domain experts, 2 reviewers, and an adaptive composer - 11 workflow profiles for features, bug fixes, infrastructure, security, proofs of concept, enterprise delivery, and other common work - Human approval gates and source-bound review evidence - 119-event audit trail plus persistent state, team knowledge, and learned rules - The same deterministic engine across every supported harness Start with Workflow Profiles https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/workflow-profiles.md to compare Classic, Express, and the focused workflows. See the AI-DLC Workflows 2.0 Specification https://github.com/awslabs/aidlc-workflows/blob/main/assets/AI-DLC-Workflows-2.0-Specification.pdf 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 https://aws.amazon.com/ai/responsible-ai/policy/ . | Guide | Use it when | |---|---| | Getting Started https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/01-getting-started.md | Installing, configuring, and running your first workflow | | User Guide https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/00-introduction.md | Using workflows, profiles, agents, knowledge, and approval gates | | Harness guides https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/harnesses/README.md | Handling provider, trust, and runtime differences | | Install and Lifecycle https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/18-install-and-lifecycle.md | Updating, pinning, installing offline, using mirrors, or uninstalling | | Harness Engineer Guide https://github.com/awslabs/aidlc-workflows/blob/main/docs/harness-engineering/00-overview.md | Reshaping stages, agents, rules, sensors, and knowledge | | Development and Releases https://github.com/awslabs/aidlc-workflows/blob/main/DEVELOPERS.md | Taking a PR through AI review, preview testing, and stable publication | | Developer Reference https://github.com/awslabs/aidlc-workflows/blob/main/docs/reference/00-overview.md | Changing the engine, hooks, packaging, or tests | - 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 https://github.com/awslabs/aidlc-workflows/blob/main/docs/reference/11-contributing.md for the complete development workflow and Porting to a New Harness https://github.com/awslabs/aidlc-workflows/blob/main/docs/harness-engineering/09-porting-to-a-new-harness.md to add another runtime. Run aidlc doctor from the project root first. Common fixes: | Symptom | Fix | |---|---| | aidlc is not found | On Windows, quit and reopen the terminal app or IDE a new tab inside one that was open during the install keeps the old PATH , or use the direct command printed with -NoModifyPath https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/18-install-and-lifecycle.md windows-powershell . On Unix, apply the installer's PATH instruction. | | 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 https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/harnesses/codex-cli.md | | 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 https://github.com/awslabs/aidlc-workflows/blob/main/docs/guide/15-troubleshooting.md for diagnostic and recovery procedures.