AI-DLC Workflows
A harness-neutral, gated methodology and engine that turns AI coding assistants into structured, auditable software-delivery workflows.
At a Glance
AI-DLC workflows core released under the MIT No Attribution (MIT-0) license, free to use, copy, modify and distribute.
Engagement
Available On
Alternatives
Listed Oct 2026
About AI-DLC Workflows
AI-DLC (AI-Driven Development Life Cycle) Workflows is an open-source project from AWS Labs that runs a structured, gated software-development methodology inside AI coding harnesses. It installs an aidlc command and per-harness runtimes for Claude Code, Kiro CLI, Kiro IDE, Codex CLI, Cursor, opencode, and GitHub Copilot. The latest listed release is v2.11.1.
What It Is
AI-DLC is a harness-neutral core that wraps AI coding assistants in a defined lifecycle so requirements, decisions, implementation, tests, and operational work stay connected. Users describe work with a command such as /aidlc Build a REST API for inventory management; the system selects a workflow from the request, asks for missing decisions, and stops at approval gates before moving forward. Codex CLI uses $aidlc instead.
How the Workflow Is Structured
The README describes 5 phases and 33 stages from initialization through operation, with 14 agents (11 domain experts, 2 reviewers, and an adaptive composer) and 11 workflow profiles covering features, bug fixes, infrastructure, security, proofs of concept, and enterprise delivery. State is tracked persistently alongside team knowledge, learned rules, and a 121-event audit trail. The documentation also covers sensors, plugins, and a harness engineer guide for reshaping stages, agents, scopes, and rules.
Setup Path
A native installer script for macOS, Linux, WSL, and Windows PowerShell installs the aidlc command and all harness runtimes without requiring Bun or Node.js. From the project root, aidlc config --harness <name> configures a harness and aidlc doctor checks the setup. A manual-copy path using Bun is available for those who cannot install a native executable. Model-provider setup belongs to the harness, and the README recommends capable reasoning models.
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Pricing
Open Source
AI-DLC workflows core released under the MIT No Attribution (MIT-0) license, free to use, copy, modify and distribute.
- MIT-0 licensed (OSI-approved)
- Native aidlc command and runtimes for Claude Code, Kiro, Codex CLI, Cursor, opencode and GitHub Copilot
- 14 agents and 11 workflow profiles
- Model provider/harness costs are external and not part of this product
Capabilities
Key Features
- Gated workflow with human approval gates
- 5 phases and 33 stages from initialization to operation
- 14 agents including domain experts, reviewers, and an adaptive composer
- 11 workflow profiles (Classic, Express, and focused workflows)
- 121-event audit trail with persistent state
- Team knowledge and learned rules
- Plugin mechanism for extra stages
- Native installer and `aidlc doctor` diagnostics
- Same deterministic engine across all supported harnesses