Tag: mlops
All the articles with the tag "mlops".
-
Fine-Tuning Small Models in 2026: A Practical Pipeline
An end-to-end pipeline for fine-tuning a small model in 2026: distill the data, train adapters, hold an eval bar, ship behind a canary, and watch for the drift that quietly eats your accuracy.
-
Eval-Driven Development: How I Actually Build LLM Features Now
My day-to-day loop for LLM features in 2026: write the eval first, then the prompt, then the code, and fold every production failure back in as a case.
-
The LLM Observability Stack I Wish I'd Built Sooner
What to instrument for LLM and agent apps before the first incident: full request and tool-call tracing, token and cost per request, latency breakdown, eval scores in production, and turning real failures into eval cases.
-
Shipping ML to Twenty Teams: The Platform Bet That Paid Off
Two years of running a self-service ML platform across twenty-odd product teams. What the paved paths got right, what we built too early, and the only success metric that turned out to matter.