Interesting article.

I would share this with my colleagues on our ‘AI Discussions’ channel. But I know what the result will be. “Those people just aren’t using the agents correctly”, “they need to provide the agents with moar context!!1!”, “this article is bad because I don’t like what it says”, “those respondents are just lazy or stupid”.

Personally, I’ve noticed this kind of mental exhaustion myself. I’ve tried leaning more heavily into AI usage because my employer encourages it. But it’s usually so damn frustrating.

I’ve found even the better/cutting edge LLMs struggle with basic troubleshooting, even when you provide them with solid context and try to keep the scope limited. Half the time they do great, but the other half they fail pretty spectacularly, and I end up wasting time trying to police/hand-hold them.

And I can’t even rely on these LLMs to reliably perform more menial tasks like formatting CSV data into JSON. They usually just stop the conversion after some arbitrary point, or they fuck up the structure of the output. Again, no matter how much context it detail I provide them.

These are all things some of my colleagues have found as well. Meanwhile, I’m also seeing other people become overly reliant on LLMs/agents, and accept whatever slop they produce as gospel while claiming it as their own work.

And that’s not even covering the knowledge/skill atrophy that I’ve witnessed. A lot of people learn and hone skills through repetition. But overuse of AI kills that opportunity, while offering unreliable immediate results.