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I feel like this is incredibly obvious to anyone who's ever used an LLM or has any concept of how they work. It was equally obvious before this that the "skill"

I feel like this is incredibly obvious to anyone who's ever used an LLM or has any concept of how they work. It was equally obvious before this that the "skill" of prompt-engineering was a bunch of hacks that would quickly cease to matter. Basically they have the raw intelligence, you now have to give them the ability to get input and the ability to take actions as output and there's a lot of plumbing to make that happen.

skort 1y ago
Yeah, my reaction to this was "Big deal? How is this news to anyone" It reads like articles put out by consultants at the height of SOA. Someone thought for a few minutes about something and figured it was worth an article.
imiric 1y ago
That might be the case, but these tools are marketed as having close to superhuman intelligence, with the strong implication that AGI is right around the corner. It's obvious that engineering work is required to get them to perform certain tasks, which is what the agentic trend is about. What's not so obvious is the fact that getting them to generate correct output requires some special skills or tricks. If these tools were truly intelligent and capable of reasoning, surely they would be able to inform human users when they lack contextual information instead of confidently generating garbage, and their success rate would be greater than 35%[1]. The idea that fixing this is just a matter of providing better training and contextual data, more compute or plumbing, is deeply flawed. [1]: https://www.theregister.com/2025/06/29/ai_agents_fail_a_lot/ https://www.theregister.com/2025/06/29/ai_agents_fail_a_lot/