Absolutely. So my codebase is huge, it's a monolith. But my work is in very specific parts of the codebase, I don't pull the entire code base into context (and I don't think that is common practice even with claude) - I start at a specific point with a specific task and work with the agent to achieve something clearly defined, for example writing tests, extracting things into separate files, refactoring or even scaffolding a new feature. You have to periodically start new threads, because you'll start hitting the limits of the context, but I max it out at over 200k because I have the memory overhead on my 128gb mbp to do that, so I can get quite a lot done.

I really recommend trying the Qwen models - 3 coder next is really incredible. GLM 4.7 flash is also incredibly performant on modest hardware. Important things to consider is setting the temperature and top_p and top_k values etc based on what is recommended by the provider of the model - a thing as simple as that could result in a huge difference in performance.

The other big leap for me was switching to Zed editor and getting its agent stuff just seamlessly integrated. If you run LM Studio on your local machine it's super easy and even setting it up on a remote machine and calling out to LM Studio is dead simple.

Yesterday, I got Qwen-Coder-Next to build a python script that reads a Postman collection, pulls the data from it to build a request to one of the endpoints, download a specific group of files whose URLs were buried in the JSON payload in that endpoint, then transform then all to a specific size of PNG, all without breaking a sweat. I didn't even have to tell it to use Pillow, but it did everything to a T.

Use case means everything. I doubt this model would fare well on a large codebase, but this thing is incredible.