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文库
- 1 Kimi K3, explained: how forgetting made the biggest open model possible
- 2 从 Spec 驱动转向环境与验证驱动——我对 AI Coding 的一点思考
- 3 Claude 新模型的上下文工程：从堆规则到设计上下文
- 4 【手猫研发提效随笔】七句话搞定一年AB实验下线：CodingAgent的魔法时刻
- 5 本体和语义层，到底差在哪？AI 问数对不上，问题多半出在这
- 6 How we secure Figma’s internal systems with agents
- 7 Scaling Grab's Data Lake: Our journey to Apache Iceberg adoption
- 8 Eval-driven development: Lessons from evaluating GenAI at scale
- 9 Crowdsourced taxonomy verification: A feedback-driven framework for refining knowledge graph relationships via online search interactions
- 10 GenRec: Towards LLM-Native Recommendation at Netflix
- 11 以决策为中心的场景本体设计
- 12 前端 Skill 驱动的团队 AI Coding 实践：从个人提效到整体赋能
- 13 面向监控场景的无订阅异常发现：问题、思路与边界
- 14 Recursive Self Improvement for Coding Agents
- 15 AI Coding的下一站，不是更会写代码，而是更懂团队
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