Lars Faye says heavy AI coding reliance may weaken novice engineers’ path to expertise

A long essay by engineer Lars Faye has stirred debate across the developer community after arguing that AI coding tools can get in the way of professional skill formation rather than simply speed work up. The piece, which gained 558 points and 542 comments on Hacker News, does not call for abandoning AI. Instead, Faye argues that the best use of large language models already presumes the kind of judgment that only experienced engineers tend to have: writing solid specifications, reading architecture clearly, and spotting when generated output is wrong. The article ties that argument to several studies. Faye cites the 2024 ACM Conference on International Computing Education Research paper The Widening Gap, which found that novices who relied most heavily on AI often performed worst, while restrained users did better because they learned to reject bad suggestions. He also points to a University of Pennsylvania study of 1,000 students learning math with LLMs, where the group using AI as a crutch scored 17% below students using only textbooks. Stack Overflow’s 2025 developer survey adds an industry angle: 84% of respondents use or plan to use AI tools, yet only 3.1% report high trust in output accuracy. Faye’s prescription is not to quit AI, but to use it as a tutor rather than a worker.