Almost no one knows if a project/business idea will be successful or not, so it's not much use asking. It's more productive to ask smart, experienced people how to best validate and execute an idea. People generally give useful and actionable feedback based on their experiences. Just make sure you understand who you're talking to when evaluating someone's advice.

> That's exactly what everybody advised me against doing - finetuning on own projects

Why would someone advise against it? IMHO that sounds as the end game to me. If it weren't so darn expensive, I'd try this for myself for sure.

Fine tuning to a specific codebase is a bit strange. It's going to learn some style/tool guidance which is good (but there are other ways of getting), at the risk of unlearning some generalization it learned from looking at 1,000,000x more code samples of varied styles.

In general I'd suggest trying this first:

- Large context: use large context models to load relevant files. It can pickup your style/tool choices fine this way without fine tuning. I'm usually manually inserting files into context, but a great RAG solution would be ideal.

- Project specific instructions (like .cursorrules): tell it specific things you want. I tell it preferred test tools/strategies/styles.

I am curious to see more detailed evals here, but the claims are too high level to really dive into.

In generally: I love fine tuning for more specific/repeatable tasks. I even have my own fine-tuning platform (https://github.com/Kiln-AI/Kiln). However coding is very broad. Good use case for foundation large models with smart use of context.

Other people have spent a lot of time on it and gotten nowhere, so I suspect there is some art to it.