Comment by kubb

> When I use AI to build software I feel like I can create almost anything I can imagine very quickly.

In my experience there is a vague divide between the things that can and can't be created using LLMs. There's a lot of things where AI is absolutely a speed boost. But from a certain point, not so much, and it can start being an impediment by sending you down wrong paths, and introducing subtle bugs to your code.

I feel like the speedup is in "things that are small and done frequently". For example "write merge sort in C". Fast and easy. Or "write a Typescript function that checks if a value is a JSON object and makes the type system aware of this". It works.

"Let's build a chrome extension that enables navigating webpages using key chords. it should include a functionality where a selected text is passed to an llm through predefined prompts, and a way to manage these prompts and bind them to the chords." gives us some code that we can salvage, but it's far from a complete solution.

For unusual algorithmic problems, I'm typically out of luck.