AI in Real Development Work
A practical reflection on how AI changed my daily work, why coding agents raise both productivity and risk, and why design matters even more now.
A practical reflection on how AI changed my daily work, why coding agents raise both productivity and risk, and why design matters even more now.
A practical account of the real implementation and maintenance problems I ran into while using AI agents for internal business system development.
A practical reflection on how I use ChatGPT, Codex, and Copilot to design first, code second, and reduce the risk of AI-driven development.
AI coding agents are useful, but they work from narrow context rather than stable architectural intent. That makes software design and compact feature boundaries more important, not less.
I do not follow development methodologies rigidly. Some environments break them entirely. What actually moves projects forward is adapting to the real constraints in front of you, not applying theory.
In teams of one to three people, continuity depends less on role separation and more on shared understanding, document granularity, and records that let the work be handed over when necessary.
A practical reflection on why a large CRUD-heavy internal business system with many screens was easier to build and maintain without making SPA architecture the default.