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Comment by simonw

10 hours ago

If you take a look at the system prompt for Claude 3.7 Sonnet on this page you'll see: https://docs.claude.com/en/release-notes/system-prompts#clau...

> If Claude is asked to count words, letters, and characters, it thinks step by step before answering the person. It explicitly counts the words, letters, or characters by assigning a number to each. It only answers the person once it has performed this explicit counting step.

But... if you look at the system prompts on the same page for later models - Claude 4 and upwards - that text is gone.

Which suggests to me that Claude 4 was the first Anthropic model where they didn't feel the need to include that tip in the system prompt.

Not trying to be cynical here, but I am genuinely interested is there a reason why these LLM don't/can't/won't apply some deterministic algorithm? I mean, counting characters and such, we have solved those problems ages ago.

  • They can. ChatGPT has been able to count characters/words etc flawlessly for a couple of years now if you tell it to "use your Python tool".

  • I think the intuition is that they don’t ‘know’ that they are bad at counting characters and such, so they answer the same way they answer most questions.

    • Well, they can be made to use custom tools for writing to files and such, so I am not sure if that is the real reason? I have a feeling it is more because of trying to make this an "everything technology".

      1 reply →

Thanks, Simon! I saw the same approach (numbering the individual characters) in GPT 4.1's answer, but not anymore in GPT 5's. It would be an interesting convergence if the models from Anthropic and OpenAI learned to do this at a similar time, especially given they're (reportedly) very different architecturally.

Or they’d rather use that context window space for more useful instructions for a variety of other topics.