Start free trial

TRUE, BUTLab Not Field

Doubled on benchmarks, unproven beyond

METR says that ruler covers well-specified tasks, and Anthropic redacted most of the rest.

“AI is dramatically accelerating AI research at Anthropic right now, roughly doubling the pace of capabilities progress.”

Ajeya Cotra on Planned Obsolescence, reading METR's assessment and Anthropic's S-1 statement that it may imminently meet its own threshold, 6 November 2026

Recorded 7 November 2026. Our ruling means: literally true, materially misleading.

Read the story →

Receipts pack

The evidence file for this verdict

16 receipts: 6 support the claim, 1 contradict it, 9 add context. 4 figures on the record, 2 traced to a quoted receipt.

The receipts

Each source, the line we quote from it, its date and which way it cuts. Free to read and to cite.

  1. 1Supports the claimplanned-obsolescence.org ↗

    AI is dramatically accelerating AI research right now

    Look up an archived copy ↗

  2. 2Supports the claimplanned-obsolescence.org ↗

    Anthropic stated in their S1 that they “may imminently meet” the threshold of “dramatically accelerated progress due to AI”

    Look up an archived copy ↗

  3. 3Supports the claimplanned-obsolescence.org ↗

    it looks like the “dramatic acceleration” threshold has already been crossed

    Look up an archived copy ↗

  4. 4Contextplanned-obsolescence.org ↗

    I did not work on this project or see the unredacted report.

    Look up an archived copy ↗

  5. 5Supports the claimmetr.org ↗

    Anthropic is likely improving the capabilities of their models on well-specified tasks at around twice the rate they did between March 2024 and October 2025

    Look up an archived copy ↗

  6. 6Contextmetr.org ↗

    we would not be surprised if the true acceleration was closer to 1.3x or 3x the historical rate

    Look up an archived copy ↗

  7. 7Contextmetr.org ↗

    could be explained by overfitting to the benchmark distribution or otherwise be an artifact of the AECI methodology

    Look up an archived copy ↗

  8. 8Contradicts the claimmetr.org ↗

    We have additional uncertainty in how this acceleration translates to broader and less well-specified tasks.

    Look up an archived copy ↗

  9. 9Contextmetr.org ↗

    Anthropic redacted a majority of the evidence we found most informative for these conclusions

    Look up an archived copy ↗

  10. 10Contextmetr.org ↗

    Robustness analyses find acceleration rates between 1.1x and 2.9x.

    Look up an archived copy ↗

  11. 11Supports the claimmetr.org ↗

    We are confident that the acceleration was not due to an acceleration in the scaling of training compute.

    Look up an archived copy ↗

  12. 12Contextmetr.org ↗

    We consider this to be only very loose evidence

    Look up an archived copy ↗

  13. 13Contextmetr.org ↗

    R&D is accelerated primarily via AI assistance rather than fully autonomous contributions

    Look up an archived copy ↗

  14. 14Contexttherundown.ai ↗

    handing out a roadmap for others to go faster.

    Look up an archived copy ↗

  15. 15Supports the claimtherundown.ai ↗

    METR crediting AI for around 80% of the company’s faster progress

    Look up an archived copy ↗

  16. 16Contextanthropic.com ↗

    METR will publish the results of its risk assessments.

    Look up an archived copy ↗

Members' extras

What each receipt proves, and what would change our mind.

  • What each receipt above proves, in our words
  • The figures table, each number traced to the receipt that states it
  • The trick behind the claim, explained, with the guide to spotting it
  • What would change our verdict
  • Our call on the record, with its due date

The verdict, the opening and every receipt above stay free. Membership adds our analysis to the evidence file for every checked story.

First membership: 30 days free, then A$89 a year. One introductory trial per customer. Card required; renews annually until cancelled. Cancel before the trial ends to avoid the first charge.