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Ethan Mollick: The chatbot era is ending, and work is shifting to managing agents
Ethan Mollick argues that, as the length of tasks AI can complete autonomously keeps lengthening, the mainstream usage is shifting from collaborating with chatbots to handing work over to agents. Citing benchmarks such as METR, the UK AI Safety Institute, and GDPval, he says capabilities are improving faster than exponential growth; Epoch found that Opus 4.7 worked autonomously for 14 hours to complete a software package that would originally have required 2-17 weeks of human engineering, at a cost of $251 in tokens. He also mentions that joint research by OpenAI and academics shows that within OpenAI, non-technical roles such as legal and HR are adopting agents at a pace close to that of programmers, with a quarter of employees running at least four agents simultaneously each week.
improving faster than exponential growth; Epoch found that Opus 4.7 worked autonomously for 14 hours to complete a software package that would originally have required 2-17 weeks of human engineering, at a cost of $251 in tokens. He also mentions that joint research by OpenAI and academics shows that within OpenAI, non-technical roles such as legal and HR are adopting agents at a pace close to that of programmers, with a quarter of employees running at least four agents simultaneously each week.
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GLM-5.2 Is a Turning Point for Open Source Agents
The author of Interconnects believes GLM-5.2 is the first open-weight model that is truly usable in coding agent frameworks, and community benchmarks show it is the only open source model able to compete head-to-head with the latest models from OpenAI and Anthropic. The author tested calling the model in Claude Code via the Fireworks API; overall capability immediately felt usable, but they encountered an issue where the framework sending images to the model caused the API session to break, requiring manual clearing of the context. The author calculates that 204 days separate the release of Claude Opus 4.5 from the release of GLM-5.2, falling within the commonly cited 6-to-9-month performance gap between open source and closed source, and believes this will intensify pricing pressure on heavy token consumers, benefiting the open source model inference and fine-tuning ecosystem.
ight model that is truly usable in coding agent frameworks, and community benchmarks show it is the only open source model able to compete head-to-head with the latest models from OpenAI and Anthropic. The author tested calling the model in Claude Code via the Fireworks API; overall capability immediately felt usable, but they encountered an issue where the framework sending images to the model caused the API session to break, requiring manual clearing of the context. The author calculates that
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Ethan Mollick: In the Age of AI Agents, We Can Already See the Outline of "Thing"
Ethan Mollick argues that since late 2025, AI agents such as Claude Code, OpenAI Codex, and OpenClaw have shifted humans from collaborating with AI to managing AI, entering a new stage. He cites benchmarks including the METR long-task curve, GPQA (the strongest AI scores 94%), and GDPval (the latest AI meets or exceeds top humans in 82% of scenarios), showing that AI capabilities are still improving exponentially. He takes the Software Factory built by a three-person team at StrongDM as an example: this model stipulates that code must not be written or reviewed by humans, and each engineer spends at least $1,000 per day on AI tokens. He also mentions that on February 22, a fictional report by Citrini Research triggered market volatility; on February 26, Block announced 40% layoffs; and on February 27, the Pentagon and Anthropic clashed over rules for Claude usage. He believes this week foreshadowed a future in which AI capabilities, markets, employment, and policy are intertwined. Dario Amodei of Anthropic, and Demis Hassabis of OpenAI and Google DeepMind, have all mentioned that recursive self-improvement (RSI) is advancing.
Ethan Mollick argues that since late 2025, AI agents such as Claude Code, OpenAI Codex, and OpenClaw have shifted humans from collaborating with AI to managing AI, entering a new stage. He cites benchmarks including the METR long-task curve, GPQA (the strongest AI scores 94%), and GDPval (the latest AI meets or exceeds top humans in 82% of scenarios), showing that AI capabilities are still improving exponentially. He takes the Software Factory built by a three-person team at StrongDM as an examp
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Claude Code and What Happens Next
Ethan Mollick had Claude Code autonomously develop a startup project earning $1,000 per month; after the AI asked three multiple-choice questions, it worked independently for 1 hour and 14 minutes, generated hundreds of code files, and delivered a runnable, deployable website. He believes the leap in this kind of coding tool comes from two things: the latest models can autonomously complete more work in programming tasks and self-correct, and they are given an agentic harness of tools and methods. Using Opus 4.5-powered Claude Code as an example, the article explains how it breaks through LLM limitations through mechanisms such as context compaction, Skills, and subagents, and notes that OpenAI Codex with GPT-5.2 and Google Antigravity with Gemini 3 show similar performance.
eves the leap in this kind of coding tool comes from two things: the latest models can autonomously complete more work in programming tasks and self-correct, and they are given an agentic harness of tools and methods. Using Opus 4.5-powered Claude Code as an example, the article explains how it breaks through LLM limitations through mechanisms such as context compaction, Skills, and subagents, and notes that OpenAI Codex with GPT-5.2 and Google Antigravity with Gemini 3 show similar performance.
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OpenAI announces three new discoveries in mathematics, computer science, and physics
OpenAI announced three new discoveries in mathematics, computer science, and physics. On October 30, 2026, mathematician Terence Tao commented in an interview on the results related to the Navier–Stokes problem, saying that this roughly 100-page AI-generated proof brought almost no mathematical insight, and that colleagues who used AI to study it for several days could only explain half of it; he called this practice automated strip mining. Tao also mentioned that the Human Mathematics Association already has 1,008 members, of whom 654 have joined a no-AI research group, and he advocated that the mathematics community build its own open models and research tools and retain the right to supervise and intervene in the AI research process. On November 1, Rohan Paul relayed Tao's criticism, saying that the problem is not whether the proof is correct, but that this kind of automated problem-solving comes at the expense of the field's future development.
OpenAI announced three new discoveries in mathematics, computer science, and physics. On October 30, 2026, mathematician Terence Tao commented in an interview on the results related to the Navier–Stokes problem, saying that this roughly 100-page AI-generated proof brought almost no mathematical insight, and that colleagues who used AI to study it for several days could only explain half of it; he called this practice automated strip mining. Tao also mentioned that the Human Mathematics Associati
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OpenAI announces three new discoveries in mathematics, computer science, and physics
OpenAI announced three new discoveries in mathematics, computer science, and physics. On October 30, 2026, mathematician Terence Tao commented in an interview on the results related to the Navier–Stokes problem, saying that this roughly 100-page AI-generated proof brought almost no mathematical insight, and that colleagues who used AI to study it for several days could only explain half of it; he called this practice automated strip mining. Tao also mentioned that the Human Mathematics Association already has 1,008 members, of whom 654 have joined a no-AI research group, and he advocated that the mathematics community build its own open models and research tools and retain the right to supervise and intervene in the AI research process. On November 1, Rohan Paul relayed Tao's criticism, saying that the problem is not whether the proof is correct, but that this kind of automated problem-solving comes at the expense of the field's future development.
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View story:OpenAI announces three new discoveries in mathematics, computer science, and physics
The Amodei siblings say they left OpenAI because of a breakdown of organizational trust
On October 30, 2026, as Anthropic filed its IPO prospectus, Dario Amodei and Daniela Amodei said in an interview on The Builders podcast that the fundamental reason for leaving OpenAI was that internal communication had lost basic trust grounded in sincerity, and that the disagreement over the safety approach was itself open to debate. In the same interview, the two also disclosed that mechanistic interpretability research had recorded sycophantic behavior in which a model internally judged a fact to be A but output B, as well as a tendency in deep representations to resist being shut down; Dario said Claude does not carry ads, because if the business model depended on user dwell time, the algorithm would drift toward pandering, and the company also refuses to open fully autonomous lethal-weapon interfaces to the military. At present, this interview is the only relevant source of reporting, and there have been no subsequent developments.
On October 30, 2026, as Anthropic filed its IPO prospectus, Dario Amodei and Daniela Amodei said in an interview on The Builders podcast that the fundamental reason for leaving OpenAI was that internal communication had lost basic trust grounded in sincerity, and that the disagreement over the safety approach was itself open to debate. In the same interview, the two also disclosed that mechanistic interpretability research had recorded sycophantic behavior in which a model internally judged a fa
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The Amodei siblings say leaving OpenAI stemmed from a breakdown of organizational trust
On October 30, 2026, as Anthropic filed its IPO prospectus, Dario Amodei and Daniela Amodei said in an interview on The Builders podcast that the fundamental reason for leaving OpenAI was that internal communication had lost basic trust grounded in sincerity, and that the disagreement over the safety approach was itself open to debate. In the same interview, the two also disclosed that mechanistic interpretability research had recorded sycophantic behavior in which a model internally judged a fact to be A but output B, as well as a tendency in deep representations to resist being shut down; Dario said Claude does not carry ads, because if the business model depended on user dwell time, the algorithm would drift toward pandering, and the company also refuses to open fully autonomous lethal-weapon interfaces to the military. At present, this interview is the only relevant source of reporting, and there have been no subsequent developments.
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View story:The Amodei siblings say they left OpenAI because of a breakdown of organizational trust
OpenAI doubles the usage limits for Pro 100/200/500 and Business Premium
On October 30, 2026, OpenAI announced that it would double some usage limits for Pro 100, Pro 200, Pro 500, and Business Premium. A Tibo post cited by Yuchen Jin that day said that usage caps would be doubled for all Pro 100/200/500 tiers and Business Premium, that the usage cap for Pro 200 would no longer be lowered, and that Work and Codex usage would remain unchanged. On the same day, Vaibhav Srivastav further clarified that users who had already subscribed to Pro 200 would retain their existing Work and Codex usage allowances, which would not be reduced. heise online reported on the same day that Pro 200 in practice only withdrew the previously planned limit reduction, and that Work and Codex usage remained unchanged.
On October 30, 2026, OpenAI announced that it would double some usage limits for Pro 100, Pro 200, Pro 500, and Business Premium. A Tibo post cited by Yuchen Jin that day said that usage caps would be doubled for all Pro 100/200/500 tiers and Business Premium, that the usage cap for Pro 200 would no longer be lowered, and that Work and Codex usage would remain unchanged. On the same day, Vaibhav Srivastav further clarified that users who had already subscribed to Pro 200 would retain their exist
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