Evals are a core part of any up to date LLM team. If some team was just winging it without robust eval practices they’re not to be trusted.

> Further more, I've worked with a pretty well respected researcher in this space and in our internal experiment we found that LLMs where not good critics

This is an idea that seems so obvious in retrospect, after using LLMs and getting so many flattering responses telling us we’re right and complementing our inputs.

For what it’s worth, I’ve heard from some people who said they were getting better results by intentionally using different LLM models for the eval portion. Feels like having a model in the same family evaluate its own output triggers too many false positives.

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Uehreka 4 days ago | parent [-]

I once asked Claude Code (Opus 4) to review a codebase I’d built, and threw in at the end of my prompt something like “No need to be nice about it.”

Now granted, you could say it was “flattering that instruction”, but it sure didn’t flatter me. It absolutely eviscerated my code, calling out numerous security issues (which were real), all manner of code smells and bad architectural decisions, and ended by saying that the codebase appeared to have been thrown together in a rush with no mind toward future maintenance (which was… half true… maybe more true than I’d like to admit).

All this to say that it is far from obvious that LLMs are intrinsically bad critics.

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colonCapitalDee 4 days ago | parent | next [-]

The problem isn't that LLMs can't be critical, it's that LLMs don't have taste. It's easy to get an LLM to give praise, and it's easy to get an LLM to give criticism, but getting an LLM to praise good things and criticize bad things is currently impossible for non-trival inputs. That's not say that prompting your LLM to generate criticism is useless, it's just that any LLM prompted to generate criticism is going to criticize things are that actually fine, just like how an LLM prompted to generate praise (which is effectively the default behavior) is going to praise things that are deeply not fine.

	▲	bubblyworld 4 days ago \| parent \| next [-]
		Absolutely matches my experience - it can still be super helpful, but AI have an extreme version of an anchoring bias.
	▲	jauhar_ 3 days ago \| parent \| prev [-]
		Another issue is that the behaviour of the LLMs is not very consistent.

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Herring 4 days ago | parent | prev [-]

I have an idea. What if we used a third LLM to evaluate how good the secondary LLM is at critiquing the primary LLM.