GenAI in production · pillar 4 of 6
Knowing whether it works
The part teams skip, and the reason nobody can tell if a change helped.
- 10 "It looks good" is not a measurement Without a fixed set of inputs and a repeatable way of scoring the outputs, you cannot tell whether a change helped…
- 11 A model can grade, and brings its own biases Using a model to score another model's output is practical and scales, but the judge is a model: it has position…
- 12 The word for it is confabulation NIST's term for what everyone calls hallucination is confabulation: the production of confidently stated but erroneous…
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Read against OWASP Top 10 for Large Language Model Applications, 2025, NIST AI 600-1 — Generative AI Profile (AI RMF), Lewis et al., Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks (arXiv:2005.11401), Hu et al., LoRA: Low-Rank Adaptation of Large Language Models (arXiv:2106.09685) on . Regulations and frameworks change; the date is there so you can tell whether this has kept up.
The OWASP Top 10 for LLM Applications is © the OWASP Foundation and published under a Creative Commons licence; NIST AI 600-1 is a US Government work in the public domain. These cards are independent commentary written in our own words. ytyk.org is not affiliated with or endorsed by the OWASP Foundation or NIST.