LLM Evals: Everything You Need to Know – Hamel’s Blog - Hamel Husain
A comprehensive guide to LLM evals, drawn from questions asked in our popular course on AI Evals. Covers everything from basic to advanced topics.
Technical Guide
Summary
A seven-step guide for building LLM-as-a-Judge evaluation systems, covering domain expert collaboration, dataset creation, pass/fail judgments with critiques, iterative prompt engineering, error analysis, and specialized judges.
Highlights
- Seven-step framework for building LLM-as-a-Judge evaluators
- Importance of domain experts and binary pass/fail judgments with critiques
- Dataset creation using real and synthetic user interactions
- Iterative prompt engineering until LLM judge converges with expert judgments
- Error analysis, critique shadowing, and creating specialized judges
auto-generated
Context
Audience
AI teams, machine learning engineers, applied researchers, and product managers building or improving evaluation systems for LLM-powered products
DomainMachine Learning
Formatlong-form article
Accessfree online
Topics
Related
LLM evaluationprompt engineeringAI product evalssynthetic data generationfine-tuning LLMsML operations
