Atlas · GenAI 2026
LLM Evaluation Design
LLM evaluation: metrics design & test set engineering
conceptPeak: 2024Evaluation DesignAI consensus: 1/3
Prerequisites
- hardModel Evaluation
Designing LLM-specific metrics builds on classical metric theory — understanding precision/recall helps design faithfulness/relevance
Test set engineering requires preventing data leakage between training and evaluation — dataset design principles apply directly
Recommended reference
Anthropic (2024) 'Evaluations' — docs.anthropic.com/en/docs/build-with-claude/develop-tests; practical eval design methodology
Notes from AI deep research
Anthropic Opus
Projektowanie metryk i test setow. Osobna kompetencja od uzywania frameworkow — wymaga domain + stats
OpenAI Deep Research
Bez mierzenia jakości nie da się iterować. Core [OA#73]
Related skills
- → is part of: LLM Testing(3/3)
- ← is subcategory of: RAG Evaluation(3/3)
- ← is subcategory of: LLM Benchmarking(2/3)
- ← is subcategory of: LLM-as-Judge(2/3)
- → is part of: LLM Evaluation Frameworks(2/3)
- ← is subcategory of: BERTScore(0/3)
- ← is subcategory of: ROUGE(0/3)
- ← is subcategory of: BLEU(0/3)