AI coding tools create an 'expert novice' trap that blocks real skill growth

Coding expertise is going to collapse from AI reliance

Lars Faye builds on his earlier 'Agentic Coding is a Trap' piece, this time focusing on junior developers. He cites a study shared by JetBrains where students who leaned heavily on AI skipped planning stages and ended up with an 'illusion of competence'; the best performers were those who heavily restricted or ignored AI suggestions. Faye describes an 'inverted learning' model where LLMs accelerate experts but mislead novices—like a compass that always points wherever you suggest north is. The core paradox: these tools demand expert-level judgment while bypassing the friction that builds it. The post doesn't offer a timeline for solutions but warns that if the industry keeps demanding both AI usage and higher-order thinking, newcomers will have no viable path to expertise.

Why it matters: Lars Faye extends his previous 'Agentic Coding is a Trap' argument with JetBrains study data to nail the 'inverted learning' problem: AI accelerates experts but manufactures competence illusions in novices. The argument has concrete research backing, not just opinion. Slight d...