From my perspective, the whole problem with LLMs (at least for writing code) is that it shouldn’t assume anything, follow the instructions faithfully, and ask the user for clarification if there is ambiguity in the request.
I find it extremely annoying when the model pushes back / disagrees, instead of asking for clarification. For this reason, I’m not a big fan of Sonnet 4.5.
I know what you mean: a lot of my prompts include “never use em-dashes” but all models forget this sooner or later. But in other circumstances I do want it to push back on something I am asking. “I can implement what you are asking but I just want to confirm that you are ok with this feature introducing an SQL injection attack into this API endpoint”
For that reason, I don't trust Agents (human or ai, secret or overt :-P) who don't push back.
[1] https://www.cia.gov/static/5c875f3ec660e092cf893f60b4a288df/... esp. Section 5(11)(b)(14): "Apply all regulations to the last letter." - [as a form of sabotage]
Sometimes pushback is appropriate, sometimes clarification. The key thing is that one doesn't just blindly follow instructions; at least that's the thrust of it.
There are shitloads of ambiguities. Most of the problems people have with LLMs is the implicit assumptions being made.
Phrased differently, telling the model to ask questions before responding to resolve ambiguities is an extremely easy way to get a lot more success.
We already had those. They are called programming languages. And interacting with them used to be a very well paid job.
You'd just be endlessly talking to the chatbots. Humans are really bad at expressing ourselves precisely, which is why we have formal languages that preclude ambiguity.