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Anthropic · Claude2 min read

Some users say Anthropic's Claude AI got worse at thinking, but proof is thin

Some developers say Claude Opus 5.5 reasons worse than before, but a larger check found no decline. Here is what the evidence shows and how to test your own use.

By the Dashline deskSource: 디지털투데이
Some users say Anthropic's Claude AI got worse at thinking, but proof is thin
Photo: Pauli Rautakorpi, CC BY 2.0

Some developers suspect that Anthropic's Claude Opus 5.5 has gotten worse at reasoning. One developer's review of usage logs points to a change starting Nov. 3. Another developer, who checked far more responses, found no sign of weaker performance. So far, nothing is confirmed.

What one developer found

Developer Shane Melaugh analyzed about 1,400 Claude Code usage logs with Google's Gemini 4 Argon. He says the way the AI describes its thinking and works through tasks shifted from Nov. 3. Tokens, mentioned below, are small chunks of text that AI tools use to count words and pieces of words.

  • Thought-summary sentences starting with "I'm" jumped to 61.3 percent, from 20 to 30 percent.
  • "I should" and "I need to" fell to 10.9 percent, from about 50 percent.
  • Median thought tokens before the first task fell about 36 percent, to 54 from 84.
  • Error indicators tied to running and fixing code rose 47 percent.

A coding test showed a gap too. Asked to fix the same audio playback error, the model on the "high" reasoning setting failed after 160 tries. On the "xhigh" setting, it fixed the problem in 5.

Why it is not settled

Anthropic's documentation says the thought text users see is not the AI's actual internal reasoning. It is a summary written by a separate model. That means the wording can change even if the underlying ability does not.

Developer Theo Browne analyzed about 458,000 responses. He saw the same change in writing style, but the timing differed by account. Average thought tokens per response rose to 413 from 369. He found no sign of weaker performance in his setup and suggested Anthropic may be changing the summary method account by account.

Melaugh himself acknowledged that his review was not a rigorous performance evaluation.

What to do

If you use AI for work and notice a sudden dip, it may be real or it may be a style change. Run the same task twice before drawing a conclusion. If results look weak, try a higher reasoning setting, as the coding test suggests it can help.

What is not known yet

It has not been confirmed whether Anthropic reduced the model's performance. The two analyses reach different readings, and they used different methods. Further verification is needed.

The takeaway

Before blaming the AI for a bad stretch, run the same task twice and try a higher reasoning setting.

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