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AI-DLC Attribution and Sources

Official Amazon AI-DLC Framework

The AI-Driven Development Lifecycle (AI-DLC) is an official framework developed by Amazon Web Services (AWS) and introduced by Raja SP, Principal Solutions Architect at AWS.

Official Sources

  1. AWS Blog Post: AI-Driven Development Life Cycle: Reimagining Software Engineering
  2. Published: July 31, 2025

  3. Author: Raja SP, Principal Solutions Architect, AWS

  4. AI-DLC White Paper: https://prod.d13rzhkk8cj2z0.amplifyapp.com/

  5. Comprehensive methodology documentation
  6. Detailed terminology and rituals

Key AI-DLC Concepts (from AWS)

Core Philosophy: - AI-Powered Execution with Human Oversight: AI creates plans, seeks clarification, and defers critical decisions to humans - Dynamic Team Collaboration: Teams unite in collaborative spaces for real-time problem-solving

Three Phases: 1. Inception Phase: Transform business intent into detailed requirements through "Mob Elaboration" 2. Construction Phase: AI proposes logical architecture, domain models, code, and tests through "Mob Construction" 3. Operations Phase: AI manages infrastructure as code and deployments with team oversight

New Terminology: - Bolts: Replace "sprints" - shorter work cycles measured in hours/days instead of weeks - Units of Work (UoW): Replace "Epics" - primary containers for functionality - Mob Elaboration: Cross-functional team validates AI's questions and proposals (Inception) - Mob Construction: Technical team provides clarification on architectural choices (Construction)

Core Mental Model: 

AI proposes → AI clarifies → Human validates → AI implements
(This cycle repeats rapidly for every SDLC activity)

How AirSDLC Relates to AI-DLC

AirSDLC is a practical, open-source implementation of the AWS AI-DLC methodology, adapted and extended with:

  1. Domain-Driven Design (DDD): AirSDLC adopts DDD as the core modeling language for domain analysis
  2. Specific Artifact Definitions: Concrete specifications for DAA, ADR, TIP, RFC, and Playbook
  3. Technology Agnosticism: Emphasis on 100% technology-neutral domain modeling
  4. Extensibility Framework: Well-defined extension points for customization
  5. Lightweight Workflow Option: Pragmatic path for simple features (TIP-based workflow)

Attribution: - AI-DLC: © Amazon Web Services, Inc. - AirSDLC: Open-source framework implementing AI-DLC principles

References

  • AWS Blog: https://aws.amazon.com/blogs/devops/ai-driven-development-life-cycle/
  • AI-DLC White Paper: https://prod.d13rzhkk8cj2z0.amplifyapp.com/
  • Amazon Q Developer: https://aws.amazon.com/q/developer/
  • Kiro: https://kiro.dev/

Last Updated: December 7, 2025