# AI-DLC — AI Coding Tool Review & Pricing

> AI-Driven Development Life Cycle from AWS Labs: a harness-neutral workflow engine that turns coding agents into structured, auditable software delivery, with phases, stages, specialist agents, approval gates and persistent project state.

Source: https://ai.dosa.dev/tools/ai-dlc · Updated Nov 7, 2026 · Category: Developer Productivity & Workflow · Published by dosa.dev

## At a glance

- **Tool**: AI-DLC
- **Company**: AWS (awslabs)
- **Category**: [Developer Productivity & Workflow](https://ai.dosa.dev/category/productivity)
- **Pricing model**: Open Source
- **Official website**: https://awslabs.github.io/aidlc-workflows/

## Key features

- One core that runs natively in Claude Code, Kiro IDE and Kiro CLI, Codex CLI, Cursor, opencode and GitHub Copilot
- Native `aidlc` command installed via `install.sh` or `install.ps1`; `aidlc config --harness <name>` and `aidlc doctor`
- 5 phases and 33 stages from initialization through operation
- 14 agents: 11 domain experts, 2 reviewers and an adaptive composer
- 11 workflow profiles covering features, bug fixes, infrastructure, security, proofs of concept and enterprise delivery
- Human approval gates with source-bound review evidence
- Audit trail, persistent state, team knowledge and learned rules

## Pricing

**Model**: Open Source

Free and open-source (MIT-0). Model usage is billed through whichever harness and provider you already use (for example Claude Code, Kiro, Codex or Amazon Bedrock).

## Who it is for

- **Best for**: Teams that want a repeatable, reviewable delivery process around AI coding agents across several harnesses, especially in AWS or Kiro environments.
- **Not ideal for**: Quick one-off edits or solo prototyping where approval gates and a staged lifecycle add more ceremony than value.

## Verdict

A thorough, fast-moving spec-and-gates methodology from AWS that works across the major coding agents; heavier than lightweight spec tools, but strong on auditability.

## Recent updates

v2.11.3 (Nov 4, 2026) ships a native `aidlc` built with Bun 1.4.4, team Units support end to end and OpenCode 2 support; 2.11.4 preview builds followed on Nov 5 and Nov 6, adding the `kiro-v2` harness name for Kiro CLI (V2).

## Frequently asked questions

### Is AI-DLC free?

Yes - AI-DLC is Open Source. Free and open-source (MIT-0). Model usage is billed through whichever harness and provider you already use (for example Claude Code, Kiro, Codex or Amazon Bedrock).

### Is AI-DLC open source?

Yes - AI-DLC is open source. Free and open-source (MIT-0). Model usage is billed through whichever harness and provider you already use (for example Claude Code, Kiro, Codex or Amazon Bedrock).

### Who is AI-DLC best for?

Teams that want a repeatable, reviewable delivery process around AI coding agents across several harnesses, especially in AWS or Kiro environments.

### Who is AI-DLC not ideal for?

Quick one-off edits or solo prototyping where approval gates and a staged lifecycle add more ceremony than value.

### What are the best AI-DLC alternatives?

The closest AI-DLC alternatives on ai.dosa.dev are Pieces for Developers, agenttrace, Vibe Kanban - all listed under Developer Productivity & Workflow.

### Who makes AI-DLC?

AI-DLC is developed by AWS (awslabs). It is listed in the Developer Productivity & Workflow category on ai.dosa.dev.

## Top alternatives

- [Pieces for Developers](https://ai.dosa.dev/tools/pieces-for-developers) (Paid) — Developers who work across multiple tools, IDEs, and environments and need to maintain a persistent, searchable history of code snippets, research, and workflow context.
- [agenttrace](https://ai.dosa.dev/tools/agenttrace) (Open Source) — Developers and teams needing to monitor and debug the efficiency, cost, and health of AI coding agents across multiple workflows.
- [Vibe Kanban](https://ai.dosa.dev/tools/vibe-kanban) (Open Source) — Software engineers who use multiple AI coding agents and need a structured environment to manage, plan, and review their output in parallel.
- [ai-memory](https://ai.dosa.dev/tools/ai-memory) (Open Source) — Developers or teams using multiple AI coding agents who need consistent context and project history persistence across different tools, machines, and sessions.
- [smolvm](https://ai.dosa.dev/tools/smolvm) (Open Source) — Running isolated coding agent sandboxes, untrusted code, and persistent local development environments that require a real Linux kernel boundary.
- [coop](https://ai.dosa.dev/tools/coop) (Open Source) — Running autonomous AI coding agents that require broad system access while maintaining a strong security boundary for the host machine.
- Full alternatives guide: https://ai.dosa.dev/tools/ai-dlc/alternatives