AIDLC Methodology
Reading time: Approximately 2 minutes
The AIDLC methodology provides the theoretical foundation for AI-driven development. While traditional SDLC was designed around human-centric long iteration cycles, AIDLC reconstructs AI from First Principles and integrates it as a core collaborator in the development lifecycle.
Structure
The methodology track consists of 4 core documents. Reading them in order will help you understand the entire theoretical framework of AIDLC.
| Order | Document | Core Question |
|---|---|---|
| 1 | 10 Principles and Execution Model | What is AIDLC and how does it work? |
| 2 | Ontology Engineering | How do we ensure the accuracy of AI-generated code? |
| 3 | Harness Engineering | How do we architecturally enforce the safety of AI execution? |
| 4 | DDD Integration | How do we transform business domains into designs that AI can understand? |
Relationship with Other Tracks
- Enterprise Adoption: Interprets the methodology's concepts (ontology, harness) as organizational transformation and cost effectiveness.
- Tools & Implementation: Covers concrete tools (Kiro, Q Developer, EKS) that realize the methodology.
- AgenticOps: Builds a circular structure where operational data feeds back into the ontology Outer Loop.