2 sessions on gguf with a coding agent: the agent failed at least once in 1, and 1 finished without a human stepping in.
Takeaway: Next time I'd tell it upfront that the eval reuses training examples so it doesn't have to discover that itself, and that .gitignore excludes models/ so it can plan the tracked-vs-mirrored file split from the start.
Takeaway: Next time I'd start by checking the app's actual inference stack (llama-cpp-python, not vLLM) before pushing any model format, since that assumption cost a lot of back-and-forth on GGUF conversion that turned out to be a dead end for MiniCPM-V-4.6.