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- 1 百亿补贴 C 端 AI Coding 实战：端到端 CodingAgent 设计与实践
- 2 Reducing Doom Loops with Final Token Preference Optimization
- 3 Kimi K3, explained: how forgetting made the biggest open model possible
- 4 从 Spec 驱动转向环境与验证驱动——我对 AI Coding 的一点思考
- 5 Claude 新模型的上下文工程：从堆规则到设计上下文
- 6 【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
- 7 本体和语义层，到底差在哪？AI 问数对不上，问题多半出在这
- 8 How we secure Figma’s internal systems with agents
- 9 Scaling Grab's Data Lake: Our journey to Apache Iceberg adoption
- 10 Eval-driven development: Lessons from evaluating GenAI at scale
- 11 Crowdsourced taxonomy verification: A feedback-driven framework for refining knowledge graph relationships via online search interactions
- 12 GenRec: Towards LLM-Native Recommendation at Netflix
- 13 以决策为中心的场景本体设计
- 14 前端 Skill 驱动的团队 AI Coding 实践：从个人提效到整体赋能
- 15 面向监控场景的无订阅异常发现：问题、思路与边界
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