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Today, we'll resume charging for requests our safeguards block before Claude…

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ClaudeDevs
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ClaudeDevs@ClaudeDevs

Today, we'll resume charging for requests our safeguards block before Claude responds. This only applies in categories with low false positive rates: biology, distillation attacks, and frontier LLM development. We've seen some coordinated attacks on our systems in recent weeks, and this is one layer of defense. In recent testing, 99.7% of accounts using Claude Code, Claude​.ai, or Cowork did not hit any of these newly "billable blocks." The classifiers behind the blocks we’re resuming charging for today are tuned to have a <0.1% false positive rate. We know that's not 0%, and we're going to keep improving them so they interrupt your work less often. If you think a request has been blocked incorrectly, please report it with /feedback in Claude Code. https://t.co/uX6JhvN6He

Key takeaways · AI-distilled
  • Anthropic is again charging for requests its safeguards block before Claude responds, but only in three categories it says have low false-positive rates: biology, attacks, and frontier development.
  • Anthropic ties the change to coordinated attacks on its systems in recent weeks and describes billing these blocked requests as one layer of defense.
  • In Anthropic's testing, 99.7% of accounts using Claude Code, Claude.ai or Cowork hit none of these billable blocks, and the classifiers are tuned for a false-positive rate under 0.1%; Anthropic says it will keep working to lower it.
Terms in this piece · Glossary
  • distillation — Training a small, cheap model to imitate a big one's outputs, keeping much of the capability at a fraction of the cost.
  • LLM — A large language model — the neural network behind tools like Claude and ChatGPT, trained on huge amounts of text to predict what comes next.
Why it matters

Claude Code, claude.ai, and Cowork users working in biology, model-distillation-adjacent, or frontier-LLM-development areas should expect occasional billed pre-response blocks and know how to report false positives via /feedback.

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