QuillAI tackles local codebase context

The interesting problem here is no longer whether local models can write code. It’s whether your editor can surface just enough project signal, fast enough, for the model to stay useful.

• –QuillAI leans into context plumbing: open tabs, imported files, project tree, and memory facts instead of brute-forcing giant prompts.
• –Running local with llama.cpp and Qwen2.5-Coder keeps code private and avoids API dependence, but it makes retrieval quality matter even more.
• –Manual context selection still works for narrow tasks, but embeddings, vector search, and hybrid retrieval are the obvious next move if you want this to scale.
• –The project feels more like a lab for local AI workflows than a polished answer, which is exactly why it’s interesting to other people experimenting with local LLMs.