Engineer Argues Code Quality Over Speed Is Key When Using AI Coding Agents

A software engineer writing on DEV Community argues that working with AI coding agents requires a disciplined, hands-on philosophy rather than passive code generation. He follows a strict four-step framework: make code correct first, then maintainable, then fast, and finally clean — always in that order. His approach stems from concern that today's LLMs, including GPT-5 and GPT-6, tend to produce low-quality, bloated code without careful human oversight. He emphasizes that early-stage codebases demand especially close attention, as poor patterns introduced early are compounded by the relentless output of coding agents. In an era where writing code is no longer the bottleneck, he contends that a software engineer's greatest value lies in the judgment to reject substandard code and remain accountable for what ships.