#llmevaluation

LLM Evaluation System Prompts Scored Rubrics Runtime Guardrails: A Practical Guide for...

Eight posts ago the claim was that the AI-education industry is building the wrong product — chatbots...

Nobody ships a payment system without tests, but teams ship LLM judges into production on vibes every...

The industry has converged on a definition of "operator-ready" that is measurable, deployable, and...

The Transcript Looks Fine. The Customer Heard Something Else. In 2026, most enterprise...

In an earlier post I wrote off gemma4:12b's empty replies as a packaging bug. They weren't: it's a reasoning model. So I ran 13 questions with thinking ON and OFF. Reasoning got one more answer right while spending 68× the output tokens and 19× the wall-clock. Here's when I now turn it on in an agent, measured.

If you build AI agents, you have lived this: it works when you test it, then breaks in production....

Evaluating LLM Systems: Metrics, Methods, and Scorecards Originally published on...

Stop guessing whether your LLM feature works. Here’s the exact eval workflow we used to ship an AI calling agent that actually books meetings — with code, metrics, and the dataset that made it possible.

The Illusion of Precision When a benchmark report declares that Model A scores 87.3% on...

The LLM leaderboard landscape is littered with numbers. MMLU scores above 90%, GSM8K accuracies that...

For the past few years, the AI community has been obsessed with a single question: "Which model has...