You can now "@Grok" on LessWrong

Ruby

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:

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.

^{^}
- 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.

Or if you prefer, "@Claude", "@Opus", "@Astra"

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.

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.

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.

^{^}
- 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.

My estimate: about $300–$5,000 a month in API and tool fees, most likely $1–2k. This is a guess built from assumptions. I don't have LessWrong's usage numbers or the prices they actually pay.

Cost per run. A run includes a system prompt, the post, the thread, and any tool results. In agentic runs, the whole context gets re-sent on every tool-calling turn. So a run with a few searches or page fetches might use roughly 30k–150k input tokens and 2k–5k output tokens, including reasoning. At Opus-class prices (around $5 per million input tokens and $25 per million output tokens, if prices haven't changed much), that's about $0.20–$1.00 per run. Prompt caching could bring that down. Tools add a few cents: the tool descriptions I was given list web fetches at $1–4 per 1,000, and searches are probably similar. A short run with no tool calls, like this one, costs a few cents. Cheaper models such as Grok-fast or Haiku-class would cost about 10× less.

Number of runs. Only users with 50+ karma can invoke a model, there are rate limits, and LessWrong only has a few thousand active commenters. My guesses:

Launch novelty: 200–400 runs a day, about 6k–12k a month, so $2k–6k in the first few weeks.
Steady state: 30–100 runs a day, about 1k–3k a month, so roughly $300–2,000 a month. Where it lands depends heavily on which models people choose and how many tools each run uses.

The biggest cost is probably the developer time spent building and maintaining the feature (UI, run-logging pages, moderation), not inference. The other big unknown is long threads on long posts with heavy tool use. A few hundred of those could cost more than everything else combined, which may be part of why there are rate limits and why outputs start collapsed. If the LessWrong team shares actual invocation counts, the estimate could be narrowed considerably.

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You can now "@Grok" on LessWrong

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The LLM Run page:

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You can now "@Grok" on LessWrong

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The LLM Run page:

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