AI Assisted Coding: How Spending 4x More on Code Quality Doubled Development Speed

What happens when you combine nearly 30 years of engineering experience with AI-assisted coding? In this episode, Eduardo Ferro shares his experiments showing that AI doesn’t replace good practices—it amplifies them. The result: doubled productivity while spending four times more on code quality.

Vibe Coding vs Production-Grade AI Development

“Vibe coding is flow-driven, curiosity-based way of building software with AI. It’s less about meticulously reviewing each line of code, and more about letting the AI steer the process—perfect for quick experiments, side projects, MVPs, and prototypes.”

Edu draws a clear distinction between vibe coding and production AI development. Vibe coding is exploration-focused, where you let AI drive while you learn and discover. Production AI coding is goal-focused, with careful planning, spec definition, and identification of edge cases before implementation. Both use small, safe steps and continuous conversation with the AI, but production code demands architectural thinking, security analysis, and sustainability practices. The key insight is that even vibe coding benefits from engineering discipline—as experiments grow, you need sustainable practices to maintain flexibility.

How AI Doubled My Productivity

“I was investing four times more in refactoring, cleanup, deleting code, introducing new tests, improving testability, and security analysis than in generating new features. And at the same time, globally, I think I more or less doubled my pace of work.” Continue reading AI Assisted Coding: AI as an Amplifier—Why Engineering Practices Matter More Than Ever