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Meta's personal AI agent Muse launched on September 8, surpassing 2.5 million downloads in 13 days, with 642,000 daily active users on the US mobile end, nearly 3 times that of ChatGPT in its early launch period; on September 21, Meta's market value rose by more than $190 billion in a single day. The article benchmarks domestic players across four items—entry point, payments, ecosystem, and execution capability—arguing that Tencent's Xiaowei has the most similar foundation but is constrained by

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Anthropic's Thariq Shihipar introduced the next phase of Claude Code on the Latent Space podcast, including Claude Mods for customizable harnesses, Projects, Claude Tag, and recent releases such as Opus 5.5 and Sonnet 5.5. He calls prompting the core skill for using Claude Code, recommending that users first spend time filling in context and allocate effort by task—for example, high or maximum for code review and security, and low or medium for UI-type tasks. He also discussed agent security, in

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A CNBC and Generation Lab survey of 1,088 Americans aged 18 to 34 found that distrust of nine tech leaders ranged from 65% to 81%, and 45% believed AI would harm their career prospects. Pew data shows that 66% of Americans aged 18 to 29 have already used AI chatbots, but the share of this same group who believe AI will reduce employment rose from 61% in 2024 to 73% in 2026. The author, Chen Yongwei, argues that this wariness stems from narrowing entry points into employment and negative past exp

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InstructGPT paper author and TypeSafe CEO Diogo Almeida detailed his new model Jev on the Latent Space podcast, describing it as a System One large programmatic model oriented toward code consumption, with its core innovation being an unpublished RLCD (reinforcement learning for calibrated decision-making), optimized for "intelligence per dollar" rather than human preference feedback. He criticized RLHF for causing mode collapse, sycophancy, and hallucinations, arguing that safety alignment suit

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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 c

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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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In an article in One Useful Thing, Ethan Mollick argues that AI agents have crossed the threshold of being able to complete real work with economic value. He had Claude Sonnet 4.5, using only the paper text and replication data, read the paper on its own, organize files, convert STATA statistical code to Python, and check each item one by one; it successfully reproduced multiple research results, which he then double-verified with GPT-5 Pro. He believes the improvement in agent capability stems

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