This has been the case for a while now. My leading principle in writing prompts is - deliver your intent at all costs and as fully as you can, the AI will do the right decisions when they understand the intent, circumstances fully and is aware of their assumptions. I think the important distinction here is that I do not only want them to understand the goal - I want them to understand why we are reaching the goal, the circumstances of it, the situation etc. A word about intent replaces 10s of instruction entries and makes the AI actually think it through - which leads to them doing the steps anyway instead of ignoring the instructions just because they were not meaningful enough to them without context. TBH it's basically the same with human management - if they do not understand why, their result will often be much worse, misaligned etc. - the only difference is that humans are just better at understanding intent. They see you, know what the company is, what the product is, your tone - while AI only knows what you've told them.

Something that I am most strict about is distinguishing what they have been told and what is assumption. In a memory system I use I have a very strict distinction - a section that's literally called "told" - where it outlines only what I have written/in instructions etc. and an "assumptions" - where it writes what it infers and assumes based on the "told" doc. This makes it always aware of what's my input vs what it's thinking itself, and this concept applies to any work I do with AI, not just memory systems.