If you use LLMs for work that matters, how do you decide when to trust the output?

Reddit r/ArtificialInteligence News
llm-trust critical-use high-stakes-work practical-guide llm-outputs decision-making

Summary

A conceptual guide on deciding when to trust LLM outputs in high-stakes professional contexts like legal, clinical, and financial work, emphasizing the need for critical evaluation skills.

Not "how they work" internally, nobody needs that to use one. I mean the practical decision: an LLM hands you a fluent, confident answer whether it's correct or invented, and in high-stakes work (legal, clinical, financial, research, etc) a wrong one carries a cost. Deciding when to trust, when to verify, and when to intervene is a skill, and I'm not sure it's obvious or widely held. I ended up writing a conceptual guide from my own experience, notes, and study, meant to pass on these LLM fundamentals and build more critical use for people who apply the tool professionally across cross-cutting fields. https://preview.redd.it/s15c7wu5t8ch1.png?width=1415&format=png&auto=webp&s=ec84cca02d83361dfd048d22587faaaa7ed652cc In practice, how do you decide whether you can trust the answer?
Original Article

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