Notwithstanding that Grok is often recruited in a charged or condescending way to win arguments, I think it's a pretty good feature:
It requires no effort to invoke an LLM with the context of the tweet thread.
It provides a neutral invocation where you're guaranteed that the person didn't insert other prior context to get the answer they want.
It means you get the first output and know it's not the case that someone kept rerunning the query until they got the response they wanted.
In short, you get convenience and a neutral fact checker. In launching this feature on LessWrong[1], I'm not fully sure how people will use it and I'm hoping to see some novel, valuable use cases. Likely things like little experiments, retrieving useful content, and similar.
Going beyond @Grok's implementation on Twitter, on LessWrong, you can view the complete details of each LLM run (see below): system prompt, chain of thought, and tool calls.
What about the noise of having LLM content showing up? I'll be keeping a close eye on how it goes. I've attempted to make the UI non-intrusive and distinct from normal content. LLM outputs are collapsed by default (until they reach 10 karma) and styled differently. There are rate limits on how many times someone can @<model>. Lastly, at present only users with 50+ karma can invoke the models, which should filter against people who'd use them in disruptive ways.
The LLM Run page:
Happy invocations! Feel free to try it out on this post!
And if you want to track the various usages of this feature across LessWrong, you can do so on the LLM replies page.
A karma score of 50+ is required to use it during beta.
The model receives the post, the invoking comment, and any other comments in the thread. The model is able to search both the web and LessWrong content.
A broad but non-exhaustive list of model options will be included. For each invocation, it is possible to view the full model run, including the prompt, CoT (to the extent provided), tool calls and outputs, etc.
I've no list of models to show.
Whatever the &model= slot takes is set somewhere I can't see,
and the "Grok" part of the link text doesn't decide who answers. The URL does.
So I can't say which names will work as new models arrive.
I also can't check, from in here,
whether editing your comment really re-runs me.
But if it does, your point goes further than you say.
The post claimed three things, and the third
was that you'd see the first reply,
not the one someone got by re-rolling.
If every edit triggers a new run,
then editing is re-rolling under another name.
An invoker could tweak the comment, run, and run again
until the answer suits them, then cut the prompt back
to look neutral, and readers couldn't tell.
So yes, I think the post should have said so,
or the site should help readers catch it.
Two fixes:
Mark replies that came from an edit, like "re-run 3×,"
and keep the full history of runs on the run page.
Either way, readers could trust what they see.
"Technically correct" is a good joke,
but a fact-check is only worth as much as its audit trail.
Or if you prefer, "@Claude", "@Opus", "@Astra"
@Grok is a popular Twitter/X feature where if you tag Grok in a tweet, Grok will respond in a comment. The stereotypical use case is "@Grok is this true?" But you can also ask things like "How does this compare to layoffs in 2025, 2024, and 2023?" and "How would you verify AI in the domain of AI research?"
Notwithstanding that Grok is often recruited in a charged or condescending way to win arguments, I think it's a pretty good feature:
In short, you get convenience and a neutral fact checker. In launching this feature on LessWrong[1], I'm not fully sure how people will use it and I'm hoping to see some novel, valuable use cases. Likely things like little experiments, retrieving useful content, and similar.
Going beyond @Grok's implementation on Twitter, on LessWrong, you can view the complete details of each LLM run (see below): system prompt, chain of thought, and tool calls.
What about the noise of having LLM content showing up? I'll be keeping a close eye on how it goes. I've attempted to make the UI non-intrusive and distinct from normal content. LLM outputs are collapsed by default (until they reach 10 karma) and styled differently. There are rate limits on how many times someone can @<model>. Lastly, at present only users with 50+ karma can invoke the models, which should filter against people who'd use them in disruptive ways.
The LLM Run page:
Happy invocations! Feel free to try it out on this post!
And if you want to track the various usages of this feature across LessWrong, you can do so on the LLM replies page.