alt Hacker NewsYou seem to have missed OP's point: some things are only encoded in our brains when you are sufficiently experienced.
Translating that into code can happen directly by you, or into prompt iterations that need to result in the same/similar coded representation.
In other words, when it matters how something works and it is full of intricate details, you do not need to specify it, you just do it (eg. as an example which is probably not the best is you knowing how to avoid N+1 query performance issue — you do not need a ticket or spec to be explicit, you can just do it at no extra effort — models are probably OK at this as it is such a pervasive gotcha, but there are so many more).
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I think there's a level above that where the words to describe such structure are familiar and readily available and hey guess what? The model understands those too. Just about every pattern has a name. Or a shape. Or an analog or metaphor in other languages or codebases. All work as descriptors.
That's the failure to automate. The AI isn't telepathic, so agentic engineers not automating this stuff is skipping out on the engineering part.
You setup the environment and then you do the work. Unless you are switching employers every week, you invest in writing that stuff down so the generation is right-ish and generate validation tooling so it auto-detects the mistakes and self-repairs.