Month: June 2026

The 4 Skill Groups That Unlock Peak Agent Productivity | 这4组Skill才是Agent顶级生产力的真正密钥

June 16, 2026 coffee
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**The real productivity ceiling in the AI agent era isn't your tool — it's your Skill configuration.** After testing dozens of agents, one truth stands out: Skill Creator, Find Skills, Superpowers, jStack, Frontend Design, and Baoyu's content toolkit form the essential stack. Configure these four Skill groups correctly, and any agent becomes a full team. --- **AI Agent 时代真正的生产力天花板，不是你用的工具，而是你配置的 Skill。** 实测数十个 Agent 后，一个真相浮现：Skill Creator、Find Skills、Superpowers、jStack、Frontend Design 与宝玉工具箱，构成了核心生产力矩阵。四组 Skill 配置到位，任何 Agent 都能顶一支团队。

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Yann LeCun — “World Models: Enabling the Next AI Revolution”

June 12, 2026 coffee
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Yann LeCun argues that LLMs cannot achieve human-like intelligence: a four-year-old absorbs as much data through vision as all internet text. His solution—world models built on JEPA, predicting in abstract representation space rather than pixels—enables planning by energy minimization, intrinsic safety, and emergent physical common sense. Now open-sourced via V-JEPA 2, EB-JEPA, and LeJEPA for hands-on experimentation.

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How to Be a Successful FDE | 如何成为一名成功的前端部署工程师（FDE）

June 9, 2026 coffee
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AI, Chinese/中文, Education, Quantum and U, Quantum Mindset Programme

Traditional logic says you must choose: bespoke high-value consulting or infinitely scalable software. Palantir refused the trade-off and invented the Forward Deployed Engineer — an embedded engineer with direct CEO access who ships production code and precipitates every engagement into reusable platform capability. 传统逻辑要你二选一：高单价的定制咨询，或可无限扩展的软件。Palantir 拒绝妥协，造出了"前端部署工程师（FDE）"——能直达客户 CEO、写生产代码，同时把每一次项目沉淀为可复用的平台能力

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Graphify – Open Source Repo Solved Claude Code’s #1 Problem

June 8, 2026 coffee
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AI, Education, Quantum and U, Quantum Mindset Programme

Graphify is an open-source tool that solves Claude Code's biggest limitation — no persistent memory of your codebase. By converting any repository into a queryable knowledge graph through a three-pass pipeline (AST analysis, audio/video transcription, and LLM-driven semantic extraction), it gives Claude a structural map instead of forcing it to grep through files blindly, delivering real-world token savings of 40–60% on large codebases.

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