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China Considers Adding AI Model Weights and Chip Designs to Export List OpenAI’s Work Agents Reach 10 Million Users, Nearly Doubling in July Anthropic's Biggest AI Coding Projects Verified With Test Suites, Not Other Agents Trump Officials Revive Push to Bar Chinese AI Models After Kimi K3 Alibaba Claims Qwen3.8 Is Second Only to Fable 5 Germany's Soofi S AI Model Tops All Open-Source Rivals on German Benchmarks China Considers Adding AI Model Weights and Chip Designs to Export List OpenAI’s Work Agents Reach 10 Million Users, Nearly Doubling in July Anthropic's Biggest AI Coding Projects Verified With Test Suites, Not Other Agents Trump Officials Revive Push to Bar Chinese AI Models After Kimi K3 Alibaba Claims Qwen3.8 Is Second Only to Fable 5 Germany's Soofi S AI Model Tops All Open-Source Rivals on German Benchmarks
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Anthropic's Biggest AI Coding Projects Verified With Test Suites, Not Other Agents

Anthropic's Biggest AI Coding Projects Verified With Test Suites, Not Other Agents

Anthropic shipped dynamic workflows in Claude Code on May 28, letting Claude write a script that coordinates up to 1,000 agents. This walkthrough builds a document audit you can point at a draft, a filing, or a set of marketing claims, with the rubric that decides what counts as proof. Then it runs that audit on this article: 204 agents, 189 claims, nine minutes. It caught two errors two earlier fact-checks missed, and raised fifty false alarms doing it.

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01 Latest Intelligence
Repo Radar: 5 GitHub Projects Worth Your Week
Tools & Workflows

Repo Radar: 5 GitHub Projects Worth Your Week

Repo Radar No. 13: graphify turns any folder of code, papers and screenshots into a queryable knowledge graph. Tencent's CubeSandbox boots a hardware-isolated agent sandbox in under 60ms. Together AI's hallmark stops coding agents shipping the same gradient hero. Microsoft's Flint compiles agent chart specs into Vega-Lite, ECharts or Chart.js. PentAGI runs autonomous security tests inside Docker. Five projects that narrow what an agent may see, run, render or spend.

Marcus Schuler · 11 min read ·
Repo Radar: 5 GitHub Projects Worth Your Week
Tools & Workflows

Repo Radar: 5 GitHub Projects Worth Your Week

This week's Repo Radar tracks five GitHub projects where AI agents move from chat into real production work: OpenMontage turns a coding assistant into a video studio, Google Labs' design.md gives agents a design-system spec, Strix runs autonomous penetration tests, Alibaba's page-agent drives live web interfaces in natural language, and MinerU converts messy PDFs into LLM-ready markdown. Difficulty scores, licenses, and push dates for each, plus why OpenMontage is Repo of the Week.

Marcus Schuler · 11 min read ·
Repo Radar: 5 GitHub Projects Worth Your Week
Tools & Workflows

Repo Radar: 5 GitHub Projects Worth Your Week

Repo Radar's eleventh issue tracks five GitHub projects builders attach to AI agents once a demo becomes a workload: Agent-Reach, a CLI giving agents live access to Twitter, Reddit, and YouTube; Flue, the Astro team's sandbox agent harness; cognee, a graph-based memory layer; hunk, a review-first diff viewer for agent-written code; and mistral.rs, a Rust engine for local inference. Each scored on stars, language, license, push date, and setup difficulty.

Marcus Schuler · 11 min read ·
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Every Tuesday Morning

Claude Fable 5 and GPT-5.6-Sol: How to Orchestrate Claude and Codex to Ship More Reliable Code

OpenAI shipped an official plugin that installs inside Anthropic's Claude Code and hands coding work to Codex. This walkthrough installs it and sets up the /route command, so Fable 5 manages while Codex's GPT-5.6 builds, and traces where AI coding value is moving.

Every Tuesday Morning

When Claude Fable 5 Is Worth Double, and When to Use Opus 4.8

Anthropic reports Claude Fable 5 falls back to Opus 4.8 on a fifth of Terminal-Bench trials, and after the July relaunch one tester measured three of four debugging tasks rerouted. The launch drew a researcher revolt over hidden limits; Andon Labs found an alignment slip. Double the price.

Thinking Machines’ Inkling Takes U.S. Open-Model Lead With 41 Score
Analysis 17 min read

Thinking Machines’ Inkling Takes U.S. Open-Model Lead With 41 Score

Thinking Machines’ Inkling leads U.S. open-weight releases with a 41 index score. Independent tests also found high pricing and a 63% hallucination rate, while the full checkpoint needs two terabytes of GPU memory. The open weights leave companies with a harder deployment decision.

Thinking Machines Lab’s first production model has taken the U.S. open-weight lead with a score of 41 on Artificial Analysis’s Intelligence Index. Inkling uses fewer output tokens than several Chinese rivals, yet testing found high prices and a 63% hallucination rate on one knowledge benchmark. Its weights are free, but the full checkpoint needs at least two terabytes of GPU memory. The test begins after the download: which companies can afford to turn open access into a working system?

Marcus Schuler
Marcus Schuler

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