📐Paid course
Evaluating LLM Systems
How to know whether your prompt change improved anything or broke something else: datasets, LLM-as-judge and its biases, and regression suites.
📐
Evaluating LLM Systems
🎓 3 levels📚 12 lessons
1. Why You Need Evals
- •The problem: you do not know whether your change improved anything
- •Your evaluation set: where it comes from and how to build it
- •What can actually be measured, and what cannot
- •The small-numbers mistake
2. LLM as a Judge
- •LLM as a judge: how it works and why it is so widely used
- •The judge's biases, and what to do about each
- •Calibrating the judge against humans
- •Rubrics that produce agreement
3. Evals in Your Workflow
- •The regression suite: making sure a fix does not break what worked
- •Offline and online: two different questions
- •Traces: without observability there is no diagnosis
- •Your minimum eval system, running this week
$10one-time payment
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