Two kinds of post, kept apart on purpose. Findings are write-ups of systems I built, each one anchored to a run that went wrong and the measurement that caught it. Notes are explainers that stand on other people's work.
One system, one run that failed in a way nothing was watching for, and the measurement added afterwards. Every number is reproducible from the repository it came from.
Assay establishes whether a coding agent's repair actually solved the task. A frontier model spent 100 steps and 65 cents, finished with all 133 visible tests passing, and had fixed none of the eighteen that graded it.
Ratchet turns an observed integration gap into a scoped, evaluated change. Schema F1 rose to 0.91, the tests passed, a human approved it, and the mapping produced a value for zero of 1,931 records.
Vendor vs Valor builds a reviewable build-or-buy comparison without redoing the research every time the question comes back. It cites every source, argues with itself, and hands the call back to you.
Explainers on things I had to understand properly before I could use them. No original measurement; they stand on published work and say whose.
LLM latency isn't one number. It's prefill and decode, pulling against each other. A mental model for finding the milliseconds before you reach for a quantization library.
Most vector databases run the same core algorithm, so 'which is fastest' rarely decides anything. The differences that bite are operational: who runs it, how it filters, what it costs at scale.
Fine-tuning is the most over-reached-for tool in the LLM toolbox. A grounded guide to deciding between prompting, retrieval, and training, before you spend the weeks.