本文基于《现在是2026年，直接用Postgres |老虎数据 — It’s 2026, Just Use Postgres | Tiger Data》整理核心信息，并结合实际工程场景给出可执行建议。
核心摘要
- Think of your database like your home. Your home has a living room, bedroom, bathroom, kitchen, and garage. Each room serves a different purpose. But they’re all under the same roof, connected by hallways and doors. You don’t build a separate restaurant building just because you need to cook. You don’t construct a commercial garage across town just to park your car.
- That’s what Postgres is. One home with many rooms. Search, vectors, time-series, queues—all under one roof.
- But this is exactly what specialized database vendors don’t want you to hear. Their marketing teams have spent years convincing you to “use the right tool for the right job.” It sounds reasonable. It sounds wise. And it sells a lot of databases.
- Let me show you why it’s a trap and why Postgres is the better choice in 99% of cases.
我的判断
这类内容的共同点是：模型能力上限不断提高，但稳定产出仍取决于流程约束。把验收标准、上下文边界、回归测试写清楚，实际收益会明显高于“追最新模型”。
真正有复利的做法不是一次性写出完美提示词，而是形成可复用的协作脚手架：任务拆解模板、失败回喂模板、以及固定的验证清单。
可直接落地的做法
- 先写可判定的完成标准（测试通过、接口契约、输出格式），再让模型实现。
- 每轮迭代只改一个维度（正确性/可读性/性能），避免目标漂移。
- 把失败案例沉淀为检查清单，下次直接复用。
结语
技术文章真正的价值不在“看过”，而在“转化为下一次决策时可复用的方法”。建议把本文结论映射到你当前项目的一项具体动作，并在一周内验证效果。