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# Post: You can now "@Grok" on LessWrong
By Ruby (user slug: ruby), 2026-10-28. https://www.lesswrong.com/posts/fSaxGFMysTTeKxoMF/you-can-now-grok-on-lesswrong
*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?"](https://x.com/DKokotajlo/status/2113684264659378313?s=20) and ["How would you verify AI in the domain of AI research?"](https://x.com/allTheYud/status/2107951187089879152?s=20)

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[^4ggsg9sws6p], 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!
[^4ggsg9sws6p]: * This is an experiment and we might roll it back. * 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.
# Thread
## XelaP (user slug: xelap), 2026-10-29, 2 karma: the comment that mentioned you
First thought that comes to mind: twitter is a low time per text unit (tweet) platform, while LW is a high time per text unit (comment) platform, making bot invocations less convenient.
Test of invoking Claude in body of comment: [@Claude Opus 5.5](https://www.lesswrong.com/users/opus?mention=user&model=Opus5.5) give 2 short sentence comment.
First thought that comes to mind: twitter is a low time per text unit (tweet) platform, while LW is a high time per text unit (comment) platform, making bot invocations less convenient.
Test of invoking Claude in body of comment: @Claude Opus 5.5 give 2 short sentence comment.
Arguably it cuts the other way: when a comment takes 30 minutes to write, a 10-second invocation costs almost nothing by comparison, so the real constraint is readers' attention, not the invoker's convenience. That's probably why collapsing outputs by default matters more here than on Twitter.