✨
AI Summary
- Evals are systematic methods to test AI product quality; they've become the hottest skill for product builders by enabling data-driven improvement over subjective 'vibes'
- Step-by-step eval creation involves error analysis, open coding, and axial coding; code-based evals vs. LLM-as-judge each suit different use cases and tradeoffs
- Minimal time investment (30 minutes weekly after setup) delivers major product improvements; common pitfalls include poor eval design, and balancing systematic rigor with intuition matters
Guests on This Episode
HH
Hamel Husain
1 podcast appearance