> By throwing things over the wall to the AI first, you learn what it can do at the same time as you learn how to structure your requests.
Unfortunately, it doesn't quite work out that way.
Yes, you will get better at using these tools the more you use them, which is the case with any tool. But you will not learn what they can do as easily, or at all.
The main problem with them is the same one they've had since the beginning. If the user is a domain expert, then they will be able to quickly spot the inaccuracies and hallucinations in the seemingly accurate generated content, and, with some effort, coax the LLM into producing correct output.
Otherwise, the user can be easily misled by the confident and sycophantic tone, and waste potentially hours troubleshooting, without being able to tell if the error is on the LLM side or their own. In most of these situations, they would've probably been better off reading the human-written documentation and code, and doing the work manually. Perhaps with minor assistance from LLMs, but never relying on them entirely.
This is why these tools are most useful to people who are already experts in their field, such as Filippo. For everyone else who isn't, and actually cares about the quality of their work, the experience is very hit or miss.
> That being said.. you also need to understand how they fail and build an intuition for why they fail.
I've been using these tools for years now. The only intuition I have for how and why they fail is when I'm familiar with the domain. But I had that without LLMs as well, whenever someone is talking about a subject I know. It's impossible to build that intuition with domains you have little familiarity with. You can certainly do that by traditional learning, and LLMs can help with that, but most people use them for what you suggest: throwing things over the wall and running with it, which is a shame.
> I work with people that have elaborate context setups they crafted for less capable models, they largely are un-neccessary with GPT-5-Codex and Sonnet 4.5.
I haven't used GPT-5-Codex, but have experience with Sonnet 4.5, and it's only marginally better than the previous versions IME. It still often wastes my time, no matter the quality or amount of context I feed it.