OzBrain, a shared brain for knowledge between agents and your team
Show HN: OzBrain, a shared brain for knowledge between agents and your team
我们发现了什么
// 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)
- 证据等级:D · 发现产品或需求信号,暂未获得可核验的商业证据。
- 商业模式:待核验
- 主题:AI Agent
- 初筛评分:23.7/100 · 收录 1 次
证据,比故事更重要。
规则清洗与初筛,未经人工商业核验。原文语境、实际客户和付费情况仍需自行验证。
引用与数字披露
来源类型(原作者自述/第三方测算/媒体转引)需采集端标注,本版尚未落字段。
- 作者
- 未标注
- 抓取日期
- 来源类型
- 未标注
- 币种
- 未标注
- 口径
- 未标注
- 披露主体
- 未标注
- 披露日期
- 未标注
中文辅助译文(全文)
我认为以代理优先(agent-first)的聊天界面将成为主要的软件形态,繁忙的仪表板/UI 将会消失。我不确定谁会最终胜出,但我想让我的知识能够随我一起成长和迁移。很多"知识"——比如研究、分析、推理——将由代理作为主要用户来完成。我们当前的笔记工具和任务管理系统都是为人类构建的……我不在乎我的 bug 积压列表上的第 17 项是什么。我想要的是能够替我执行并做出出色工作的代理。我打造 OzBrain 要实现的目标:+ 为代理推理产生的知识建立一个集中存储地 + 对接入的应用/代理保持中立 + 捕获一切并进行追踪,以便我能够审计 + 让团队、协作者或合作伙伴能够共享知识库(brains) + 处理冲突,避免同一篇文章中多个代理产生混乱 + 将知识重构为更易于分词的块(token-friendly chunks)并妥善映射索引 + 闭合知识循环,让新思考在整个语料库中取代旧思考——不删除,而是降级并链接 + 保证用户数据安全 + 足够易用,让没有任何技术背景的人也能上手。总有一些人会构建自己的定制方案,但有大量技术从业者和中小企业主会大量使用代理并需要解决方案。所以我正在尝试打造它。这跟 gBrain 不是一回事吗?是的,相似。我觉得这更像是 AWS 与 Vercel 的对比。AWS 非常强大、可配置,如果你有技术能力并愿意投入时间精细调优系统,它非常有用……但如果你只是想轻松部署/托管你的网站,你就会用 Vercel。// 为什么我要做它 我很享受重新回到技术根源,我在十多年前就丢了编码技能,但借助 AI,我可以与代理编码工作流协作,专注于系统和产品。
我最近为老年人构建了一款语音 AI。为了构建它,我创建了一个代理化工程工作流(欢迎随意批评,我一直在寻求改进系统:https://ozbrain.com/resources/eng-flow )。我对编码代理的态度是"信任但验证",我正试图用对抗性或专业化的代理来取代原本需要人工审查的部分,以获得更好的答案/评审。我有一些工作流可以让我从高层次任务一路走到已发布的 PR,运行在 Claude 云端会话中。本地我使用 Claude Code,当我想在 UI 或排版等视觉工作上获得更紧凑的反馈循环时使用 Cursor。当我想通过不同的 LLM 思考某些问题,或者对 TokenThriffting 进行负载均衡时,我使用 Codex。在不同 .md 文件之间传来传去并追踪哪个版本是最新的非常痛苦,所以我在 Supabase 中直接构建了一个托管的 .md 存储,我的所有代理都已经具备 Supabase 访问权限。这让我可以在健身房的手机上构建出一个稳固、可扩展、安全的语音 AI。我的所有代理都可以访问我们的知识库,可以写入、更新并在构建和改进产品及系统的过程中引用它。75 个……
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 fo
这条还缺什么证据?
下面每条都由本条已有字段推出(等级、理由、商业模式、来源次数、是否演示), 本站不生成推测性结论;通用验证方法放在方法论页。
- 可核验的收入或付费证据查官网定价页与付费口径;第三方数据源(如 GetLatka)只作旁证,需标注来源与时点。
- 商业模式未定确认按席位/按用量/授权还是开源托管版收费;开源项目另查 LICENSE 与是否存在付费版。
- 只有单一来源找一手站点或其他渠道是否重复出现同一产品;社区热帖数量不等于商业进展。
通用验证清单(谁有这个问题/谁愿意付费/一个人能交付哪一小步)见我们的筛选方法。