I mean, it's not actually autocomplete. But it serves the same role. I know approximately what I want to type, maybe some of the details like argument-order are a bit foggy. When I see the code I recognize it as my own and don't have too much trouble reading it.

But I use LLMs one level higher than autocomplete, at the level of an entire file. My prompts tend to look like "We need a new class to store user pets. Base it on the `person` class but remove Job and add Species. For now, Species is an enum of CAT,DOG,FISH, but we'll probably turn that into a separate table later. Validate the name is just a single word, and indicate that constraint when rendering it. Read Person.js, CODE_CONVENTIONS.md, and DATA_STRUCTURES.md before starting. When complete, read REFACTOR.md"

With the inclusion of code examples and conventions, the agent produces something pretty close to what I'd write myself, particularly when dealing with boilerplate Data or UI structures. Things that share common structure or design philosophy, but not common enough to refactor meaningfully.

I still have to read it through and understand it as if I'd written it myself, but the LLM saves a lot of typing and acts as a second pair of eyes. Codex currently is very defensive. I have to remove some unnecessary guardrails, but it will protect against rare issues I might not have noticed on my first pass.