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How DoorDash is pushing experimentation boundaries with interleaving designs
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文库
- 1 3 个月用Harness重构90万行旧项目：实战经验与踩坑总结
- 2 如何把 Skills 变成 Agent 的训练场？小红书 AllSpark 提出 Skill2Env
- 3 淘特端侧模型从微调到应用的全链路实践
- 4 从 vmcore 到上游 commit：一次 systemd 事件循环缺陷的完整猎杀
- 5 基于AST与LLM的遗留代码重构：绞杀者模式自动化实践
- 6 3个月用Harness重写90万行旧代码：踩过的坑都在这
- 7 Inside Minerva: building scalable observability for eBay’s monetization platform
- 8 Meta’s Generative Ads Model (GEM): Scaling the Central Model and Compute Engine for Frontier Ads AI
- 9 大表治理之分表实践：带你手搓一个简单的数据库分表组件
- 10 CASTLE: training natural language search before the first real query
- 11 Reliable GPU compute for large training & inference jobs
- 12 Netflix Stratum Media Processing: Automated Container Right-Sizing
- 13 The Lifecycle of LLM-as-a-Judge: Building, Aligning, and Monitoring at scale
- 14 Running Apache Spark experiments in my sleep (and on a plane)
- 15 Netflix Conductor : The Next Chapter
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