OzBrain, a shared brain for knowledge between agents and your team
Show HN: OzBrain, a shared brain for knowledge between agents and your team
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// WHY I MADE IT I’ve been enjoying getting back to my technical roots, as I lost my coding skills more than a decade ago, but with AI I can focus on the system and the product in partnershi
- 来源:Hacker News(发现于 2026-08-22)
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- 主题:AI Agent
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中文辅助译文(全文)
我认为以 agent 为先的聊天界面将成为主要的软件形态,繁杂的仪表板/界面将会消失。我不确定最终赢家是谁,但我想让我的知识跟随我一起成长。大量「知识」——也就是研究、分析、推理——将由 agent 作为主要用户完成。我们当前的笔记工具和任务管理系统是为人类设计的……我不在乎我 bug 待办列表上第 17 项是什么。我想要指挥能够为我执行并产出优秀成果的 agent。我打造 OzBrain 是为了实现这些目标: + 为 agent 推理后的知识提供一个集中存放的地方 + 对接入的应用/agent 保持中立 + 捕获并追踪一切,以便我可以审计 + 让团队、协作者或合作伙伴能够共享知识库 + 处理冲突,避免同一篇文章中的多个 agent 互相干扰 + 将知识重构为对 token 更友好的小块,并建立良好的索引 + 关闭知识闭环,让新的思考取代语料库中旧的思考。不要删除,而是降级并保留链接 + 保证用户数据安全 ++ 足够易用,让你无需任何技术知识也能上手
我们当中总有一些人会构建自己的定制方案,但有数以百万计的技术从业者和小企业主将重度使用 agent,并需要一个解决方案。所以我正在尝试打造它。这像不像 gBrain?是的,相似。我觉得这就像 AWS 与 Vercel 的关系。AWS 非常强大、可配置,如果你懂技术并愿意投入时间精细调优系统,它很有用……但如果你只想让 Web 部署/托管简单可靠地工作,你会用 Vercel。
// 为什么我要做这件事 我很享受重新回到我的技术本源——十多年前我已经丢掉了我的编码技能,但现在借助 AI,我可以与 agent 编程工作流协作,专注于系统和产品本身。
我最近为老年人构建了一个语音 AI。为了构建它,我创建了一套 agent 化的工程工作流(欢迎随时吐槽,我一直在寻求改进这套系统:https://ozbrain.com/resources/eng-flow)。我使用编程 agent 的方式是「信任但核实」,我正试图用对抗性的或专用的 agent 来取代人类审核的部分,以获得更好的回答/审核。我有可以将高层任务直接变成已合并 PR 的工作流,运行在 Claude 云会话中。本地我使用 Claude Code,在我想要更紧密的视觉工作循环时(比如 UI 或布局),会用 Cursor。而当我想做 token 节流的负载均衡,或想让另一个大语言模型来思考某件事时,会用 Codex。
在 .md 文件之间传来传去并追踪哪个版本是最新版本,真是烦透了。所以我直接在 Supabase 里搭了一个托管的 .md 存储,我的所有 agent 都已具备 Supabase 访问权限。这让我可以在健身房里用手机就构建出一个稳定、可扩展、安全的语音 AI。
我的所有 agent 都可以访问我们的知识库,能写入、更新和引用它,在我们构建和改进产品以及我们所使用的系统的过程中都能用上。
我询问了 75 位创始人朋友他们如何管理共享知识,其中 26 位自己搭建了定制知识系统……有的用 Obsidian 库加上 7k 文件通过 VPS 同步,有的在自建 MCP 服务器后面放 markdown 仓库,有的用 cron 任务把 Supabase 和 skills 文件拼在一起……每个都是不同的 Frankenstein,他们都必须自己维护。32 位说他们在搬移静态文件时感到痛苦,但又没有任何解决方案。所以我把我的「大脑」重建得更好,并用这个大脑来打造产品。
// 你们能怎么帮忙 希望你们来试用一下。维护闭环还在 alpha 阶段,所以暂时还没有在客户数据上运行。如果你自己搭建过「大脑」,我很想听听你是怎么做的。在它的设计与功能中,你认为最重要的标准是什么?如果你厌倦了在 .md 文件之间来回折腾,欢迎试用 OzBrain 并提供反馈,只需让你的 agent 把内容放进共享的 bug 和功能知识库即可!Cheers!
Bubs.co
译文由上游机器翻译生成,可能有误;判断请以英文原文为准。
英文原文(来源本站未改写)
I think agent-first chat interfaces will be a primary software modality and busy dashboard/UI will go away.I’m not sure who exactly wins it, but I want my knowledge to grow/go with me.A lot of the “knowledge” ie research, analysis, reasoning will be done by agents as the primary user.Our current notes tools & tasks management systems were built for humans… I don’t care what the 17th thing on my bug backlog is.I want to conduct agents that can execute for me and do great work.
What I built OzBrain to do: + Create a central place for agent reasoned knowledge to live + Be agnostic about what apps/agents connect to it + Capture everything and track it so I can audit it + Enable teams, collaborators or partners to share brains + Handle conflicts so many agents in the same article doesn’t blow up + Refactor knowledge into more token friendly chunks and map the index well + Close the knowledge loop so new thinking supersedes old thinking across the corpus.
Don’t erase, depreciate and link + Keep user data safe and secure ++ Be easy enough to use that you don’t have to have any technical knowledge Some among us will always build their own custom solutions, but there are millions of tech professionals and small business owners that will use agents heavily and need a solution.So I’m trying to build that.Isn’t this like gBrain?Yes, similar.I think it’s like AWS vs Vercel.
AWS is very powerful, configurable, and useful if you’re technical and want to invest the time into really fine tuning your system… but if you just want your web deploy/hosting to just work and be easy to deal with you use Vercel. // WHY I MADE IT I’ve been enjoying getting back to my technical roots, as I lost my coding skills more than a decade ago, but with AI I can focus on the system and the product in partnership with agent coding workflows.I recently built a Voice AI for older people.
To build it I created an agentic engineering workflow (feel free to rip that up as I’m always looking to improve systems: https://ozbrain.com/resources/eng-flow ) My approach with coding agents is trust but verify, and I’m trying to replace the parts where a human would review with an adversarial or specialized agent who would give a better answer/review.I have workflows that will go high level task to shipped PR running in Claude cloud sessions.I use Claude Code locally and Cursor when I want a tighter loop on doing visual work like UI or layout.And Codex to either load balance usage for TokenThriffting or when I want a different llm to think thru something.
It was a pain in the ass passing .md files around and keep track of which version was the most recent, so I built a hosted .md storage right in Supabase and any of my agents already have Supabase access.This let me build a solid, scalable, secure voice AI from my phone at the gym.All my agents have access to our knowledge, can write to it, update and refer to it as we build and improve the product and the systems we use.
Out of 75 founder friends I asked about how they manage shared knowledge, 26 built their own custom knowledge systems… Obsidian vaults with 7k files synced through a VPS, markdown repos behind their own MCP servers, cron jobs stitching Supabase to a skills file… each a different Frankenstein they have to maintain. 32 said they felt the pain of moving static files around but didn’t have any solution for it.So I rebuilt my brain better and used it to build it. // HOW YOU CAN HELP Would love to have you try it out.The maintenance loop is still in alpha so not running it on customer data yet.If you built your own brain I’d love to hear how you did it.
What criteria was most important for you in its design & function.If you are tired of shuffling .md files around I’d love to have you try out OzBrain and to give feedback, just ask your agent to put it in the shared bugs & features brain!Cheers!Bubs.co
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