Example from work.

I described a problem to a new hire. Symptoms, how to reproduce, etc. and asked him to go investigate it, pin down the problem and solve it. It was a non-trivial and hard to reproduce bug.

Instead of doing any of that, he sent back very quickly a wall of text. Generic advice. Nothing relevant. Along with this he sent a PR that would have broken prod.

It was useless, and basically amounted to throwing the assignment back in my face. Since I, like literally everyone else, already have Claude Code, having an expensive person use it for me (slowly and badly) is worthless. In fact, it's negative value, and a huge waste of time. ChatGPT would have given me the same wall of text for pennies.

In the end I got rid of him.

I'm sure he thought I was "intimidated", and had "ego" issues. But he's actually just redundant.

No, that’s not it. Its easy as competent engineers for us to forget how terrible most people are at prompting AI, or reviewing and correcting AI output. Raw output from typical prompts is garbage. If I start reading something that no one even bothered to edit well enough to tone down the AI speak, odds are its garbage and I don't need to spend more time engaging with it than the author did.

Admittedly a controversial take, but I think some of the AI skepticism I see is driven by status anxiety, alongside the perfectly legitimate complaints about verbosity, low-effort output, lack of a human voice, etc.

The bar for what counts as expertise is shifting. If someone with relatively little background can use an LLM to get to a reasonably informed answer much faster than before, then experience and credentials alone carry a bit less signalling power than they used to. That obviously doesn't mean the inexperienced person suddenly has the judgement, context or intuition of an actual expert, but I do think some of the hostility toward AI comes from discomfort with that change.

AI is still wrong, goes in weird circular loops, and doesn't solve the fundamental human problems around judgement, organization, learning curves, accountability, etc. But it does seem to be raising the baseline expectation for what a competent knowledge worker should produce, and I feel that shift is genuinely uncomfortable for a lot of people who based their identities around being rigorous abstract problem solvers.

Reading a copy-pasted AI response feel the same to me as reading a massive wall of text with no punctuation. It may contain valuable information, but it's harder to extract the signal out from among all the noise, and the writing style is correlated with a lack of valuable information, so I generally give up and decide to spend my time reading something else.

Is that an ego issue? Doesn't seem like it to me.

Nah its just bad writing.

Plus I’ve been seeing where AI productivity is highest and it’s been when leveraged by an expert.