I'm absolutely right

I've started saying this to people I don't agree with, for the enhanced collaborative capabilities, learning from the LLMs.

It feels like a greater form of intelligence, IQ without EQ isn't intelligence.

This phrase is a clear indicator LLM is being used in a wrong way. I have a really poor experience with LLMs correcting after being incorrect.

Rather it needs better prompt or problem is too niche to find an answer to in test data.

> The LLM, with its single-token prediction approach, follows up with a suggestion that much more closely follows the user's desires, instead of latching onto it's own previous approach.

Maybe? How would we test that one way or the other? If there’s one thing I’ve learned in the last few years, it’s that reasoning from “well LLMs are based on next-token prediction, therefore ” is a trap. The relationship between the architecture and the emergent properties of the LLM is very complex. Case in point: I think two years ago most of us would have said LLMs would never be able to do what they are able to do now (actually effective coding agents) precisely because they were trained on next token prediction. That turned out to be false, and so I don’t tend to make arguments like that anymore.

> The people behind the agents are fighting with the LLM just as much as we are

On that, we agree. No doubt anthropic has tried to fine-tune some of this stuff out, but perhaps it’s deeply linked in the network weights to other (beneficial) emergent behaviors in ways that are organically messy and can’t be easily untangled without making the model worse.

Probably because it's intentional. There are many theories why, but one might be that by saying "You're absolutely right," they are priming the LLM to agree with you and be more likely to continue with your solution than to try something else that might not be what you want.

has anyone tried ways to not obsessively agree with you? what's worked?