His experiences reveal a pattern: AI can rapidly produce 70% of a solution, but that final 30% – edge cases, security, production integration – remains as challenging as ever. Meanwhile, trust in AI-generated code is declining even as adoption increases.
I'm very much intrigued by this contradiction where where adoption of AI is increasing, but the trust in the code it generates is declining. Is it a case of the more developers use AI coding tools, the more they become aware of the shortcomings and problems?