[ianbicking]

There's a hundred ways to use AI for any given work. For example if you are doing interesting work and aren't using AI-assisted research tools (e.g., OpenAI Deep Research) then you are missing out on making the work that more interesting by understanding the context and history of the subject or adjacent subjects.

This thesis only makes sense if the work is somehow interesting and you also have no desire to extend, expand, or enrich the work. That's not a plausible position.

[wolvesechoes]

> This thesis only makes sense if the work is somehow interesting and you also have no desire to extend, expand, or enrich the work. That's not a plausible position.

Or your interesting work wasn't appearing in training set often enough. Currently I am writing a compiler and runtime for some niche modeling language, and every model I poke for help was rather useless except some obvious things I already know.

[ianbicking]

Some things you could do:

1. Look up compiler research in relevant areas

2. Investigate different parsing or compilation strategies

3. Describe enough of the language to produce or expand test cases

4. Use the AI to create tools to visualize or understand the domain or compiler output

5. Discuss architectural approaches with the AI (this might be like rubber duck architecting, but I find that helpful just like rubber duck debugging is helpful)

The more core or essential a piece of code is, the less likely I am to lean on AI to produce that piece of code. But that's just one use of AI.