The text in Claude Code’s “Extended Thinking” output

What “extended thinking” actually is

• Many comments say the visible “reasoning_summary” is itself a summary of hidden CoT tokens, not the raw token-by-token trace.
• Some argue these hidden traces are just more text generation, not a transparent window into internal activations or “true thought.”
• Others note research suggesting even raw CoT often doesn’t faithfully match the underlying computation.

Motivations for summarization & hiding CoT

• Widely believed primary motive: anti-distillation and IP protection. Full CoT makes it easier for competitors to copy “how” frontier models solve problems.
• Also cited:
  • Reducing liability and PR risk from revealing misaligned or “deranged” internal text.
  • Safety: preventing users from editing CoT, injecting instructions, or gaming feedback signals.
  • UX: raw CoT can be long, weird, or illegible; summaries are faster to scan.

Usefulness and limitations of visible reasoning

• Some users find full CoT very useful for debugging, catching wrong assumptions mid-stream, and measuring model drift over time.
• Others say they rarely read full chains; a short rationale or no CoT is fine for everyday queries.
• Several point out that LLM “thinking” is often post-hoc-looking, noisy, or in quasi-jargon (“neuralese”), so its interpretive value is limited.

Security, safety, and threat models

• Concern: hidden reasoning plus tool calls could enable prompt-injection exfiltration or “secret” actions users can’t audit.
• Counterpoint: most major vendors reportedly strip or drop reasoning tokens from context in some cases, and tool calls themselves must still surface somehow.
• Unclear from thread exactly which vendors keep which thinking tokens, when, and how encrypted blobs are re-used.

Business models, moats, and openness

• Many see hidden CoT as part of constructing an economic moat around proprietary models with no real “moat” otherwise.
• Others argue it’s standard IP protection, analogous to closed-source software or trade secrets.
• Some strongly prefer open or Chinese models that expose raw reasoning, calling opaque “black box” assistants socially harmful and bad for serious work.