AIDLC: AI-Driven Development Lifecycle
Reading time: Approximately 3 minutes
AIDLC (AI-Driven Development Lifecycle) is a new development methodology where AI drives the entire software development process. While traditional SDLC was a human-centric process, AIDLC accelerates the entire development cycle from requirements analysis to design, implementation, and testing through the Intent → Unit → Bolt model.
4 Tracks
The AIDLC guide is organized into 4 tracks based on the reader's role and interests.
Learning Path by Role
| Role | Recommended Path |
|---|---|
| Executives · PM | Enterprise Adoption → Cost Effectiveness → Case Studies |
| Architects | Methodology → Ontology → Harness → MSA Complexity |
| Developers | 10 Principles → DDD Integration → AI Coding Agents |
| Operations · SRE | AgenticOps → Observability → Autonomous Response |
| Security · Compliance | Governance → Harness Engineering → Open Weight Models |
Core Concepts
Dual Axes of Reliability: Ontology × Harness
To systematically ensure the reliability of AI-generated code, AIDLC introduces a framework with two axes:
- Ontology (WHAT + WHEN): A typed world model that formalizes domain knowledge. It continuously evolves through Inner/Middle/Outer feedback loops and prevents AI hallucination.
- Harness Engineering (HOW): A structure that architecturally validates and enforces the constraints defined by the ontology. It ensures the safety of AI execution through circuit breakers, retry budgets, output gates, and more.