AI

[!IMPORTANT] Core Pain Point: In fast-paced projects, the high cost of manual documentation updates leads to persistent “drifting” or loss of synchronization between code and architectural documentation (README, ARCHITECTURE.md). The Solution: Offload the cognitive burden of “documentation maintenance” from human developers to AI Agents with semantic reasoning capabilities, enabling “metabolic” renewal of architectural maps. After multiple rounds of conversation with AI regarding documentation governance, I’ve distilled a concept for “AI-Native Metabolic Governance V3.0.” This is not just an automation script, but a governance logic designed to make code architecture “come alive.” ...

In the AI era, raw coding skills are devaluing, while system design, cross-domain coordination, and the ability to master complexity are becoming core competencies. This post explores how to transition from executor to coordinator with the help of AI.

AI lowers the barrier to entry for coding but raises the ceiling for cognitive demand. In AI-driven refactoring, we need more than just prompts—we need the grit to hold the architectural line against complexity.

I’m not here to sell courses. I’m here to show you the mud.

Facing legacy code that is hard to change, AI gives us the courage to ‘flip the table’ and start over. This isn’t just a technical upgrade; it’s an opportunity to review the development logic of the past decade.