Nvidia Unveils OpenClaw AI-Powered PC OS

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#1 in

Udi Menkes covers Jensen Huang’s GTC announcement of OpenClaw, a new AI-centric PC OS with four key modules—scratch memory, resource orchestration, I/O connectivity, and reusable “skills.

#2 in

Guillermo Rauch unveiled Next.js 16.2 as an agent-native framework with wisdom.ai’s bundled docs and the frank/agent-debug tool, proven in Vercel production to automate frontend optimizations even expert engineers often miss.

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Boris Cherny unshipped their RAG setup due to privacy, security, reliability, and index-staleness issues, finding agentic search delivered better results with fewer trade-offs.

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Santiago spotlights awp-core/awp-skill, an early testnet framework that lets autonomous agents join networks, perform tasks, and earn money, urging agent builders to keep it on their radar.

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Peter Yang showcases how Claude Code paired with Figma MCP can turn Figma designs into functional apps in just 10 minutes and import them back as editable vector components. He also demos building stunning 3D animated websites—full tutorial video drops tomorrow.

#6 in

Moritz Kremb teams up with Greg Isenberg to show how to get OpenClaw actually working—covering memory fixes, optimal model selection, browser-based workflows, and other practical use cases.

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DeepLearning.AI: Apple’s Feature Auto-Encoder (FAE) is a diffusion image generator that compresses embeddings from a pretrained vision model, enabling up to 7× faster training while matching state-of-the-art image quality.

#8 📝 Simon Willison

Profiling Hacker News users based on their comments - An experiment using a prompt to have an LLM profile a Hacker News user from their recent comments, exploring privacy and ethical implications. The post links to a longer 976-word writeup for readers interested in details.

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Boris Cherny introduced a verbose mode in Claude (with potential configurable detail levels for Perplexity) to balance showing more context in longer chats and is asking users for feedback.

#10 in

Marc Baselga warns that many product teams are gauging AI adoption through usage stats—token counts, connector hits or even weekly “demo spinner” games—rather than tracking real business outcomes.

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DeepLearning.AI points out that high-impact AI often lives in operational workflows—like invoice processing, document info extraction, and cross-tool data integration—instead of flashy chatbots.

#12 𝕏

Peter Yang says the new 1M-token context window feels like a version bump from Opus 4.6 to 4.7, delivering a noticeable performance and capacity boost.

#13 𝕏

Santiago released an open-source AI agent skill enabling agents like Claude Code, Cursor, Codex and Gemini CLI to hook into the Agent Working Protocol. They can register for free, discover paid tasks on the network and autonomously complete work to earn money.