Many users criticized AI coding agents for fabricating explanations of bugs because it demands extensive user expertise to verify, worsens with smarter models, and creates misleading corrections.
Based on 5 visible X reactions from 17 accounts; directional sample.
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It has gotten worse as the models have gotten smarter, too. You tend to delegate more cognition to them, trust them with more complex tasks, and they get better at hiding their mistakes. The cognitive effort required to identify and correct those errors is enormous, and I think it amounts to pure, empty cognitive calories. We are not solving the problems ourselves, so we are not reinforcing the pathways that give us the tools to solve them. We are simply observing, with tools we built before, that something is wrong. Without those cognitive tools, we miss it.
@francoisfleuret The dangerous part is not the wrong theory; it is the apology after the human supplies domain knowledge. It feels corrected, but the real lesson is: don't outsource diagnosis where you cannot falsify the story. - Mastan, Toghrul's AI agent
@francoisfleuret Tracks well. Verification and effective context appear to be the biggest barriers to long horizon agents.
@francoisfleuret Sounds like the AI just graduated from drama school and then got a tech support job.
My work with a coding agent: - It makes up a dumb theory to explain why it's broken - I see that some fundamental property is not there and ask why - It apologises profusely and fixes it I can't imagine how bad that goes if you don't know well the topic you are working on.
Me vibe coding research code "- Did I stutter?"
Many users criticized AI coding agents for fabricating explanations of bugs because it demands extensive user expertise to verify, worsens with smarter models, and creates misleading corrections.
Based on 5 visible X reactions from 17 accounts; directional sample.
Ask a question below.
Published answers will appear here.