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AI-DLC (AI-Driven Development Life Cycle)

AI-DLC is an intelligent software development workflow that adapts to your needs, maintains quality standards, and keeps you in control of the process. For learning more about AI-DLC Methodology, read this blog and the Method Definition Paper referred in it.

Quick Start

Set up the AI-DLC rules/steering files as part of your supported platform.

Clone this repo:

git clone <this-repo>

Create a new project folder with a name of your choosing if you're working on a greenfield application:

mkdir <my-project>

Assuming your project is located under the same parent folder as the cloned aidlc-workflows repo, change directory to your project folder:

cd <my-project>

Amazon Q Developer IDE Plugin/Extension

AI-DLC uses Amazon Q Rules to implement its intelligent workflow. To activate AI-DLC in your project, copy the rules to your project's workspace under the <project-root>/.amazonq folder.

Copy the AI-DLC workflow to your project's workspace under the <project-root>/.amazonq folder:

mkdir -p .amazonq/rules 
cp -R ../aidlc-workflows/aidlc-rules/aws-aidlc-rules .amazonq/rules/ 
cp -R ../aidlc-workflows/aidlc-rules/aws-aidlc-rule-details .amazonq/

To confirm that the Amazon Q Rules are correctly loaded in your IDE, follow these steps:

  1. In the Amazon Q Chat window, locate the Rules button in the lower right corner and click on it.
  2. Verify that you see entries for .amazonq/rules/aws-aidlc-rules in the displayed list of rules.

If you do not see the aws-aidlc-rules rules loaded, please check the directory where you previously issued the mkdir and cp commands.

AI-DLC Rules in Q Developer IDE

Kiro CLI

AI-DLC uses Kiro Steering Files within your project workspace to implement its intelligent workflow. To activate AI-DLC in your project, copy the rules to your project's workspace under the <your-project-root>/.kiro/steering folder.

Copy the AI-DLC workflow to your project's workspace under the <project-root>/.kiro folder:

mkdir -p .kiro/steering
cp -R ../aidlc-workflows/aidlc-rules/aws-aidlc-rules .kiro/steering/
cp -R ../aidlc-workflows/aidlc-rules/aws-aidlc-rule-details .kiro/

To confirm that the AI-DLC rules are correctly loaded in your Kiro CLI, follow these steps:

  1. Start Kiro CLI: kiro-cli
  2. Check your context contents: /context show
  3. Verify that you see all entries for .kiro/steering/aws-aidlc-rules in the displayed list of rules.

If you do not see the aws-aidlc-rules rules loaded, please check the directory where you previously issued the mkdir and cp commands.

AI-DLC Rules in Kiro CLI

Usage

  1. Start any software development project by stating your intent starting with the phrase "Using AI-DLC, ..." in the chat.
  2. AI-DLC workflow automatically activates and guides you from there.
  3. Answer structured questions that AI-DLC asks you
  4. Carefully review every plan that AI generates. Provide your oversight and validation.
  5. Review the execution plan to see which stages will run
  6. Carefully review the artifacts and approve each stage to maintain control
  7. All the artifacts will be generated in the aidlc-docs/ directory

Three-Phase Adaptive Workflow

AI-DLC follows a structured three-phase approach that adapts to your project's complexity:

  • 🔵 INCEPTION PHASE: Determines WHAT to build and WHY

    • Requirements analysis and validation
    • User story creation (when applicable)
    • Application Design and creating units of work for parallel development
    • Risk assessment and complexity evaluation
  • 🟢 CONSTRUCTION PHASE: Determines HOW to build it

    • Detailed component design
    • Code generation and implementation
    • Build configuration and testing strategies
    • Quality assurance and validation
  • 🟡 OPERATIONS PHASE: Deployment and monitoring (future)

    • Deployment automation and infrastructure
    • Monitoring and observability setup
    • Production readiness validation

Key Features

  • Adaptive Intelligence: Only executes stages that add value to your specific request
  • Context-Aware: Analyzes existing codebase and complexity requirements
  • Risk-Based: Complex changes get comprehensive treatment, simple changes stay efficient
  • Question-Driven: Structured multiple-choice questions in files, not chat
  • Always in Control: Review execution plans and approve each phase

Prerequisites

Have one of our supported platforms/tools for Assisted AI Coding installed:

Security

See CONTRIBUTING for more information.

License

This library is licensed under the MIT-0 License. See the LICENSE file.

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