Key Takeaways
- A structured knowledge base, not the model itself, is the real enabler of AIDLC. Consistent AI output depends on consistent shared context: specs, boundaries, decisions, dependencies, kept current.
- Spec-driven development makes AI output auditable, not a black box. Reasoning traces back to a documented spec, critical for regulated systems.
- The line between "AI can do this alone" and "needs human sign-off" moves as the knowledge base matures.
- AIDLC without a knowledge base collapses into repeated one-off prompting. Gains only compound when context persists across sessions.