The Econ Index now tracks artifacts—the primary output Claude produces in a session. We analyzed Claude conversations and compared how often each artifact was used for work, coursework, or personal life. Blogging is mostly a work activity; translation falls in between.
AI
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Anthropic advances study of Claude’s economic impact with hourly data
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To keep pace with AI progress, we're advancing how we study Claude's economic impact. Hourly sampling and survey data show us how the cadences of life shape usage, what people produce with Claude, and how perceptions of AI's impact may be changing.
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108 real-world computer-use workflows: 20.6% agent completion
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108 real-world, long-horizon computer-use workflows. Average rollout: 318 tool calls.
— Snorkel AI (@SnorkelAI) 26 juin 2026
Top frontier agent (Claude Opus 4.8 with max thinking + batched tool calls): 20.6% end-to-end completion (54.8% partial progress). Partial progress is real. Reliable end-to-end computer use is… https://t.co/aK42mNsHdx108 real-world, long-horizon computer-use workflows. Average rollout: 318 tool calls. Top frontier agent (Claude Opus 4.8 with max thinking + batched tool calls): 20.6% end-to-end completion (54.8% partial progress). Partial progress is real. Reliable end-to-end computer use is
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Sakana Fugu Technical Report published on arXiv
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Sakana Fugu Technical Report https://arxiv.org/abs/2606.21228
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GLM 5.0 report and IndexShare: only notable aspects
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I was thinking about it, but beyond the original GLM 5.0 technical report, I don't think there's anything interesting to write about (except that it's better; and IndexShare, which is a rel simple concept)
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Not yet tried Cline & Pi, comfortable with Codex due to muscle memory
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No, not yet. There's also Cline & Pi I still have to try. (I am kind of comfortable with codex because of muscle memory.)
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Local open-weight LLMs: 30B MoE sweet spot at 40 tok/sec
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Have been taking different local open-weight LLMs for a test drive in different harnesses (Qwen-Code, Codex, Claude Code). 30B Mixture-of-Expert models are kind of a nice sweet spot and can solve challenging problems. And they get roughly 40 tok/sec on a Mac or DGX Spark, which
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Genie ZeroOps: AI agent monitors production workloads and suggests fixes
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We recently announced Genie ZeroOps, a new AI background agent that monitors your production workloads, investigates issues, and suggests fixes. As organizations deploy more pipelines, models, dashboards, and apps, maintaining production workloads has become a growing
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Heterogeneous disaggregated inference is the future of AI
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Training builds models. Inference builds businesses. At @deeptechweek SF, our Chief Product & Strategy Officer Abhi Ingle shared why heterogeneous, disaggregated inference is the future of AI, and why "more intelligence per joule" is the metric that matters. @LipBuTan1
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Warning: US focus on winning AI race may cause global catastrophes
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“America’s preoccupation with “winning” the AI race with China could well lead to unprecedented catastrophes, even catastrophes on a global scale. Not all games are zero-sum, and if this fact doesn’t start playing a bigger role in American policy discourse, the AI revolution