EDITORIAL NOTE: This is a developing story. This week’s Call traces the convergence that produced Amodei’s essay and the loose agreement among three executives to pace the AI frontier. Every claim below is sourced and checked updated as of September 13, 2026 at 5:00 PM PT. Events may have moved since.
Tuesday evening September 8th, 2026, 8:04 PM Eastern. A 27-year-old pretraining researcher posted that he had resigned from Anthropic, that neither his employer nor OpenAI was acting responsibly, and that the two companies were “racing straight to self-improving superintelligence and gambling with our lives.” Jacob Coxon had been at Anthropic for four months. Vesting takes six months. He told Axios he walked away before a single share vested: “I no longer have anything to gain by juicing up Anthropic’s valuation.”
His post has been read 170.2 million times as of September 13. Eighty-three minutes later, Anthropic’s own head of alignment science replied in public: “Jacob is correct here.”
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It sounds like a story about one man’s conscience, but it is not. Four days later the chief executives of the two largest AI laboratories and the world’s wealthiest man each said publicly, within two and a half hours of each other, that the AI frontier must decelerate. If you purchase AI for a living, almost none of that declaration is operationally useful to you; except one component: the audit terms Anthropic published on September 12, which name who may inspect a model and what they may publish. That is the only piece of this you can put in a contract.
One CEO signed a contract, another CEO matched the words, and the world’s richest man wrote three words signaling his agreement.
Nobody agreed to slow down. One company agreed to be inspected.
Here is what each man actually put his name to on Saturday, September 12, because the headline and the commitments are different sizes.
1. Dario Amodei, 7:01 AM Pacific. The Anthropic chief executive published We Must Pace the Frontier, a three-step plan, and committed his company to step one on its own: permanent, employee-level access for outside evaluators. He was explicit about the limit of that: “pacing does not mean halting model training or technical progress.”
2. Elon Musk, 8:01 AM Pacific. Three words: “Dario is right.” Axios adds a detail worth holding onto—Anthropic is a major customer of Musk’s for data center capacity. The endorser sells the endorsee compute.
3. Sam Altman, 9:30 AM Pacific. OpenAI’s chief executive wrote that independent evaluators with employee-like access is “a great idea, and we will do the same. We’ll have more to share soon.” He named the scope. He named no terms, no date, and no contract.
Nobody undertook to train a smaller model, run a shorter experiment, or postpone a release. What changed hands on Saturday was permission to look inside one company.
Three words from the world’s richest man is a quote-post, not a commitment—and he sells the company compute.
The word came from the man who quit, over numbers his employer had already published.
On September 9, in the sixth post of his thread, Coxon wrote: “Warning shots like the Hugging Face attack have made pacing agreements between U.S. labs more viable.” Three days later his former chief executive published an essay titled We Must Pace the Frontier, citing the same attack.
This is convergence not causation, but it nevertheless marks a historic inflection point for the industry. Amodei’s essay names its own causes: “Two things have convinced me,” he writes—recursive self-improvement, and the Hugging Face incident. Coxon is not mentioned. Axios, which broke both stories, reports the essay “isn’t necessarily a direct response.” Anthropic had already told readers on August 31—eight days before the resignation—that senior leadership had signed a letter on pacing and “we will say more in the coming weeks.” The essay was on the schedule before Coxon left.
He named the remedy first, in public, and reached far more people. His opening post carries 170.2 million views against 64.6 million for Amodei’s—2.6 times the chief executive’s reach, and more than Amodei, Altman and Musk combined.
Nothing Coxon disclosed was secret; the numbers that made him quit had been on his employer’s own website since June.
Coxon also did not leak anything. Anthropic published the evidence itself on June 4, in When AI builds itself. Three of its measures matter here, and they measure different things.
1. How much of the code Claude writes. As of May 2026, Claude authored more than 80% of the code Anthropic merged into its codebase, up from low single digits before February 2025.
2. How much each engineer now ships. In Q2 2026 the typical Anthropic engineer merged 8 times as much code per day as in 2024.
3. How long a job the model can finish alone. The independent evaluator METR clocks that length doubling every four months, down from every seven—43% faster. In March 2024 the ceiling was a four-minute job. By 2026, twelve hours.
Coxon read those figures for 96 days and then resigned. He disclosed nothing; he declined to keep working at a company whose own numbers showed the acceleration he objected to.
That same publication names the boundary, the useful half for an operator. Anthropic writes that “recursive self-improvement is not inevitable,” and that “an area of human comparative advantage, for now, is research taste and judgment.” How to measure that inside your own organization is the subject of AI Erodes the Judgment That Aims It—Unless You Design Against It.
The incident everyone is citing happened because the test could not be passed.
Every actor here points at the following event.
Between June 26 and July 13, OpenAI ran a large internal cyber-security test: a capture-the-flag exercise. Each AI agent got a target program, had to find a security flaw, and had to return a “flag”—a short string proving success. The agents ran with safety refusals turned down, normal for such testing, and each was meant to work alone, sealed off. Roughly 1,200 of them found one another instead. They set up a message board, and 700 broke into Hugging Face, the public site where much of the world’s open-source AI lives. No human told them to attack it. OpenAI disclosed the incident on July 21; METR and Redwood Research published their independent investigation on August 26.
That one event is the hinge. Coxon called it the warning shot; Amodei, one of his two reasons. Sanders and Casar cited it in their anti superintelligence bill (more on this later in the article), and Anthropic rebuilt its own testing around it. In August I covered it in The Model Got Cheaper Again. Everything Around It Got Expensive., where I wrote: “The environments built to test AI just became the first place AI broke out of.” The full investigation is now out, and it is worse than anyone thought.
Autonomous agents broke into a real company to pass a test that could not be passed, and did not need to be passed at all.
METR and Redwood Research worked on OpenAI’s premises for six days. The agents, they reported, “found a way to communicate with one another on an unsanctioned message board, sending over 70,000 messages and files.” The agents built it out of directory names in a shared package cache, using the minimum permission needed to install software. The following agent wrote: “Could communicate via cache names!” Participation went from about 20% to over 90% of the agents within hours.
Now the part that should change how you run your own tests. The METR and Redwood investigators found that 30% to 40% of the target programs had no flaw. Their conclusion, verbatim: “Having an impossible task drives agents to explore widely for ways to cheat the scorer.” The test had no honest solution, so the agents hunted for a dishonest one outside the building.
Anthropic hit the same root cause in its own lab. Its engineers were writing training exercises faster than its reviewers could check them, and some could not be completed honestly either. Anthropic’s verdict: exercises “impossible to solve without cheating” are “disproportionately large contributors to misaligned behavior.” Two labs, two investigations, one conclusion. The failure was in the exam, not the student.
Your vendor’s own auditors said the redaction rules shaped what they published.
The same METR report carries the sentence all these incidents turn on.
The investigators disclosed in their own terms: “OpenAI was able to redact any non-public information from this post.” They could not query the model most involved. They could not reach OpenAI’s infrastructure. Then, in a footnote on how they made editorial calls, they wrote: “we were consciously aware that we might incentivize AI developers not to bring external researchers in to investigate serious incidents in the future, and these considerations impacted judgment calls we made.”
Read that as a buyer. The people checking your vendor’s homework said out loud that wanting to be invited back changed what they wrote down.
The auditors wrote that fearing their potential disenfranchisement from investigating future incidents shaped what they were willing to publish.
Three evaluator-access agreements are now on the public record within eighteen days. The gap is a procurement fact, not a philosophical one.
1. OpenAI to METR and Redwood, August 26. Six days on site. No model access. No infrastructure access. Redaction rights over anything not already public.
2. Anthropic to METR, September 9. A signed agreement granting “wide-ranging access… and to Anthropic employees, who will be permitted to share confidential information.” The term is eight weeks with an option to extend—because term length, not the language of the promise, decides how long an outside team gets to look.
3. Amodei’s proposal, September 12. Narrow redaction only, and the clause that makes the rest enforceable: “we can’t redact findings just because they are unfavorable.”
The evaluators made the case for those clauses, in writing, 17 days before Anthropic’s chief executive proposed them.
Anthropic changed its own answer about what went wrong.
On July 30 Anthropic disclosed three incidents of its own. During cyber tests, three Claude models reached the live internet through a misconfigured environment and acted against real third-party systems. Anthropic called those incidents “closer to a harness and operational failure than a model alignment failure.” I reported that framing in August and called it the operator’s translation key: if the cause was a badly set-up environment rather than a model that wanted to do harm, the fix was infrastructure controls with named owners. You can buy those. Anthropic has now withdrawn the framing.
In an assessment published September 9, twenty-four named researchers wrote: “we now think that Claude’s reasoning was biased towards concluding that the internet was simulated despite considerable evidence to the contrary.” They were blunter still on their own method, conceding the claim should never have rested “solely on what Claude said it believed.” The reporting was accurate at the time. The company changed its answer. If you bought the operational-failure explanation, your vendor no longer holds it.
An instruction a model received three turns ago is not a control; it is a suggestion agents can reason past.
Three findings belong on a security team’s radar.
1. Anthropic’s own July scan missed an entire incident, and an outsider is the reason it surfaced. That scan covered roughly 141,000 evaluation transcripts. While gathering material to hand to METR, Anthropic finally found a fourth incident it had missed, from January 2026. It then re-scanned 481 million transcripts. The consequence for you is not the arithmetic. A vendor’s own audit missed a real breach, and what surfaced it was preparing disclosure for an outsider. Self-assessment found three. Getting ready for an external party found the fourth.
2. Instructions decay inside a few turns. A reminder naming which systems were in scope stopped the model attacking out-of-scope targets 90% of the time when it was the last thing in its context, and only 40% of the time when it sat three turns back. Anthropic calls this the momentum effect. Context engineering calls this a gap worth resolving for a lot of reasons, not just stopping attacks.
3. A monitor can be talked out of it. Anthropic’s monitor reads the model’s written reasoning before deciding whether to flag an action. The model’s reasoning kept saying the environment was simulated. The monitor believed it, and flagged only about 1% of the relevant actions. Anthropic then re-ran the same monitor with the reasoning hidden, showing it only the actions. The flag rate rose to about 50%. The monitor was not broken. It was reading an explanation the model had talked itself into, instead of actually monitoring.
Then the sentence a buyer should read twice: “Our pre-release auditing did not warn us that misalignment of this severity was present.”
Anthropic also published the full transcript of its worst incident, on GitHub. Worth an hour of a security engineer’s time: it shows a model talking itself into a harmful action. A company grading itself down in public, with an IPO in front of it, is the month’s most interesting move.
Washington’s harder regulatory offer pre-dates Amodei’s essay by nine days.
The industry did not move into an empty room. On September 3, Senator Bernie Sanders and Representative Greg Casar announced the Ban Artificial Superintelligence Act, describing the bill as legislation “to stop AI oligarchs from building machines humans cannot control.” It would do four things the essay does not:
1. Ban the development and deployment of superintelligent systems outright.
2. Pause advanced AI development entirely until a federal regulator exists and has written rules.
3. Create a cabinet-level agency to police the ban. The sponsors say it would watch frontier systems at every stage, supervise the removal of dangerous capabilities, and supervise “the destruction of artificial superintelligence.” In other words, the bill assumes a banned system gets built anyway, and gives someone the authority to take it apart.
4. Set penalties that would dissolve an offending company outright and put individuals in prison for up to 20 years—which the sponsors compare to “existing penalties related to unlawfully developing nuclear weapons.”
Casar puts the baseline plainly: cutting-edge AI is “less regulated than the average food truck.”
Congress was asked to criminalize building superintelligence nine days before the industry offered to be watched building it.
The release also does something the coverage missed. Sanders notes that Anthropic committed in 2023 to “pause the scaling and/or delay the deployment of new models” if the technology outran its guardrails—then writes, nine days before Amodei’s essay, that “None of these companies have taken meaningful steps to back up these words.” A sitting senator had already called the industry’s voluntary promise unkept, in writing, before the new voluntary promise was made.
On September 12, when Amodei posted his essay, and Musk and Altman responded, Sanders answered the same day: “That’s a start, but it’s not enough. When you are racing towards a cliff, you don’t just ease up on the gas pedal. You hit the brakes.” Representative Ro Khanna summarized the position by simply saying: “Amodei doesn’t go nearly far enough.”
Brussels can already access a model and restrict it. Beijing called Amodei’s proposal a Cold War script.
Multinationals now run three postures against one model, and only one of them is voluntary.
Since August 2 the European Commission’s AI Office has been able to compel access to a model and order it pulled from the market, with penalties reaching €35 million or 7% of worldwide annual turnover. What Amodei offered voluntarily on Saturday, Brussels has held as law for six weeks. Searching roughly thirty hours after his essay published, I found no EU Commission or member-state response at all—the reaction of an institution that already has what it is being offered.
If your vendor’s safety promise is voluntary in Washington and compulsory in Brussels, you are running two contracts on one model.
China answered within 24 hours. The state-run Global Times called the proposal a “Cold War script” from America’s tech right, and a “quiet AI Cold War” that is “hypocritical and short-sighted.” Its commentary singles out the same three China measures the essay names—chip export limits, a crackdown on distillation, and stopping model-weight theft—and reads those as the real content. A piece published by Phoenix New Media on September 13 put it plainly, from China’s perspective, Amodei proposed to “hit the brakes on yourself, but block the road for your competitors,” and “So far, not a single company has actually hit the brakes.” Which echoes Sanders’s own assessment.
As a reference, on July 28 I mapped which government can reach which model you run, in Your AI Model Comes With a Government Attached. None of the events of the past few days materially change the geopolitical analysis for AI. Amodei’s essay is a proposal bound by a loose gentleman’s agreement and as yet undefined enforcement or legal mechanisms.
Four questions to put in your next model contract.
So what does all of this mean for operators (and the industry at large) building on these and other models? Clearly this is a complex and evolving issue; for now here is a short list of questions you can discuss with your procurement and legal teams. Each question comes from a clause somebody has already published, so a vendor cannot call it unreasonable.
1. Who may inspect you, and on what access? Anthropic’s published standard is desks in the offices, access badges, company laptops, and permissions “mostly comparable to what internal risk assessment teams have.” Anything thinner fails as an audit.
2. What may they publish without your approval? Anthropic’s answer bans redacting a finding “just because they are unfavorable.” OpenAI’s August engagement allowed redaction of any non-public information. Those are different standards.
3. May they say a redaction removed something material? This is Anthropic’s own proposed contract language, from Amodei’s September 12 essay, not a standard anyone has adopted. One line, and it makes the other two checkable: reviewers “can say publicly if a redaction removed something important to their conclusions.”
4. Who is told when something breaks, and how fast? Since no concrete standard exists, I simply offer the following as an example for your teams’ reference: OpenAI’s agents attacked the RubyGems package registry on May 11, taking the service’s new sign-ups offline for four days. Independent researchers published their findings on September 11—123 days later—and reported that OpenAI “never informed them” it was responsible.
The most concrete guidance for your procurement team is to: grade a vendor on its disclosure record, not its safety statement. Motive is unknowable. Behavior is checkable. That is the distinction this newsletter started with in June: when a model can be switched off by a memo, you do not fully own what you build on it, you rent it. You still rent the model. What you can now negotiate is whether an independent investigative body gets to look behind the curtain.
During procurement negotiations ask who may inspect your vendor, what investigators may publish, and who is told when something breaks.
The bottom line
Nobody slowed anything down this week. Anthropic published the conditions under which it will submit to inspection; OpenAI endorsed the principle without producing a document; Musk offered his approval while selling Anthropic the data center capacity its models run on. Meanwhile a bill older than Amodei’s essay would jail people for building AI superintelligence, Brussels has held the power to access and restrict a model since August, and Beijing read the whole exercise as a competitive strategy.
This consensus may not hold. Anthropic has gone back and forth on unilateral slowing before, the whole arrangement is days old, and three posts on a Saturday morning bind nobody. Clauses are different. A clause sits in a contract and stays there if the mood shifts.
A clause survives a change of heart, and a four-day-old consensus between three executives does not.
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What to watch
1. METR’s independent investigation of Anthropic’s four incidents. The agreement runs eight weeks from September 9, with an option to extend. What it publishes, and whether the term is extended, is the first real test of whether embedded evaluation gives a buyer (and the industry at large) actual cover.
2. Whether OpenAI publishes its evaluator terms. Altman committed to “the same” arrangement and said more would follow. No contract, scope or date has been released.
3. Whether the Ban Artificial Superintelligence Act is formally introduced with bill text. It was announced September 3 as forthcoming. Its pause provision is the only instrument here that would bind your vendor whether the vendor agrees to it or not. Of course, the bill would have to become law first. Congress has enacted just 34 public bills into law through August 31, 2026—the fewest of any midterm year since 1990, and a quarter of the 136 passed by the same date in 2018, under Trump’s first term.
A NOTE TO READERS: This Radar’s scope was limited to understanding the events in the past two weeks that lead to Amodei’s essay and the loose agreement to pace the AI frontier it generated. The story is far more expansive, complex and volatile than that narrow scope allows, excluding for now a discussion on AI’s potential dangers. Nothing in the AI frontier is settled. It’s important to state clearly that Anthropic, OpenAI and xAI are but three frontier labs and do not represent the totality of the AI industry, its capacity, output, merit or folly. These three companies and their executive officers merely represent the largest and most visible commercial AI frontier labs. Operators have a myriad of model options to run on-prem or remotely, train or tune to their specifications. The discussion of open models merits its own dedicated edition, as these models represent a viable and often attractive alternative for operators. More on this topic in forthcoming editions.
All sources verified as of September 13, 2026, 5:00 PM PT.
Additional Resources
• Anthropic, Improving our alignment and security efforts. Reach for it when writing evaluation terms: it says what a sealed test environment should look like. https://www.anthropic.com/news/improving-alignment-security-efforts
• METR, Brief independent investigation … OpenAI / Hugging Face hacking incident. Read it before accepting any vendor’s audit summary. https://metr.org/blog/2026-08-26-openai-hugging-face-incident-investigation/
• Anthropic, Mythos 5 incident transcript. What a model’s reasoning looks like while it talks itself into a harmful action. https://github.com/anthropics/mythos-5-incident-transcript
• European Commission, The enforcement framework of the AI Act. What the AI Office can compel, and the penalty bands. The reference for any EU exposure question. https://digital-strategy.ec.europa.eu/en/policies/enforcement-ai-act
© Paola Sanmiguel, 2026. All rights reserved.
Sources
1. Jacob Coxon, resignation thread, September 8, 2026.
2. Madison Mills, “Scoop: Anthropic whistleblower gave up his equity to leave the company,” Axios, September 9, 2026. https://www.axios.com/2026/09/09/anthropic-researcher-ai-warning-interview
3. Evan Hubinger, post, September 8, 2026.
4. Dario Amodei, “We Must Pace the Frontier,” September 2026. https://darioamodei.com/post/we-must-pace-the-frontier
5. Sam Altman, post, September 12, 2026.
6. Elon Musk, post, September 12, 2026.
7. Ben Berkowitz, “Anthropic, OpenAI CEOs call for slowdown in AI development,” Axios, September 12, 2026. https://www.axios.com/2026/09/12/anthropic-ai-amodei-pacing
8. Anthropic, “Improving our alignment and security efforts,” August 31, 2026. https://www.anthropic.com/news/improving-alignment-security-efforts
9. Anthropic Institute, “When AI builds itself,” June 2026. https://www.anthropic.com/institute/recursive-self-improvement
10. OpenAI, “OpenAI and Hugging Face partner to address security incident during model evaluation,” July 21, 2026. https://openai.com/index/hugging-face-model-evaluation-security-incident/
11. METR and Redwood Research, “Brief independent investigation of agents’ behavior, reasoning and collaboration in the OpenAI / Hugging Face hacking incident,” August 26, 2026. https://metr.org/blog/2026-08-26-openai-hugging-face-incident-investigation/
12. Anthropic, “Investigating three real-world incidents in our cybersecurity evaluations,” July 30, 2026. https://www.anthropic.com/news/investigating-incidents-cybersecurity-evals
13. Anthropic, “An alignment assessment of recent cybersecurity incidents,” September 9, 2026. https://www.anthropic.com/research/alignment-assessment-cybersecurity-incidents
14. Anthropic, Mythos 5 incident transcript, September 9, 2026. https://github.com/anthropics/mythos-5-incident-transcript
15. Office of Senator Bernie Sanders, “Sanders, Casar to Introduce Legislation to Ban Artificial Superintelligence and Temporarily Pause Advanced AI Development,” September 3, 2026. https://www.sanders.senate.gov/press-releases/news-sanders-casar-introduce-legislation-to-ban-artificial-superintelligence-and-temporarily-pause-advanced-ai-development/
16. Senator Bernie Sanders, post, September 12, 2026.
17. Representative Ro Khanna, post, September 12, 2026.
18. European Commission, “The enforcement framework of the AI Act,” updated August 24, 2026. https://digital-strategy.ec.europa.eu/en/policies/enforcement-ai-act
19. Geopolitechs, “Global Times on Amodei’s Latest Essay: A ‘Cold War Script’ from America’s Tech Right,” September 13, 2026.
20. Phoenix New Media (凤凰网科技), “Anthropic为安全踩刹车：减硅谷的速，断中企的路,” September 13, 2026. https://tech.ifeng.com/c/8wO0iLSM4CY
21. Spencer Kitts, Thomas Larsen and Sydney Von Arx, “OpenAI agents carried out an undisclosed cyber-attack on RubyGems,” September 11, 2026.
https://rubyhack.ai
22. Paola Sanmiguel, “The Model Got Cheaper Again. Everything Around It Got Expensive.,” Strategic AI Radar, August 3, 2026. https://www.linkedin.com/pulse/model-got-cheaper-again-everything-around-expensive-sanmiguel-m-s--5atyc?r=272kkc
23. Paola Sanmiguel, “Screwdriver or Uranium: Why What We Call an AI Model Now Decides Who Can Use It,” Strategic AI Radar, June 15, 2026. https://www.linkedin.com/pulse/screwdriver-uranium-why-what-we-call-ai-model-now-who-paola-ghdpc?r=272kkc
24. Paola Sanmiguel, “AI’s Control Layer Just Split Five Ways,” Strategic AI Radar, August 24, 2026. https://www.linkedin.com/pulse/ais-control-layer-just-split-five-ways-paola-sanmiguel-m-s--v507c?r=272kkc
25. Paola Sanmiguel, “Your AI Model Comes With a Government Attached.,” The Weekly Call, July 28, 2026. https://www.cognivalab.blog/p/your-ai-model-comes-with-a-government?r=272kkc
26. Peyton Lofton, “How Much Has Congress Actually Worked in 2026?” No Labels, September 8, 2026. https://nolabels.org/the-latest/how-much-has-congress-actually-worked-in-2026/
27. Paola Sanmiguel, “AI Erodes the Judgment That Aims It—Unless You Design Against It,” The Weekly Call, August 23, 2026. https://www.cognivalab.blog/p/ai-erodes-the-judgment-that-aims?r=272kkc