AI Agents3 weeks ago
Node OS — Redemocratizing the internet
Decentralized operating system for building and running AI workflows on a peer-to-peer network.
@Economy_V1 · X
AI workflows for the rest of us. Built on Bitcoin. Building cloudless at
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Decentralized operating system for building and running AI workflows on a peer-to-peer network.
@Economy_V1 · X
AI workflows for the rest of us. Built on Bitcoin. Building cloudless at
AI agent that generates comparable product concepts from ideas, sketches, images, and constraints.
@hedge8og · X
4月23日，我开始用 Codex 搭自己的产品。到现在，满3个月了。 截至7月19日，Codex 页面显示247.1亿个 Token，连续使用54天。标题里的“250亿”是取整，准确数字以截图为准。 这三个月，我把 做上线了，产品介绍视频改了很多版，也借助 Codex 做了不少以前一个人很难完成的工作。 具体一点：我用它整理过 BP、导出过 PDF、做过 PPT 工作稿，也把调研、文档、图片、浏览器操作、网站、视频和邮件这些常见 Skills 跑过一圈。有些后来真的进入了工作，有些试完就放下了。 现在回头看，最大的收获不是“我做过这么多种东西”，而是我越来越能分清：哪些能力能进入真实工作，哪些只是演示起来很厉害。 这些数字确实挺夸张。说实话，我自己看到也会觉得：是不是做了很多事？ 但如果现在让我总结，我不会把它们当成绩。它们只能证明我很投入，蹬得快冒烟了，不能证明产品已经有价值，更不能证明商业已经成立。 我大学辍学，最高学历是高中，之前一直在制造业工作，也不会写代码。写这些不是为了卖惨，更不是想证明学历没用，只是先把我的真实起点说清楚。 2月 OpenClaw 火起来以后，我开始认真试各种 AI 工具，想先解决工作里那些重复、又不得不做的事情。 这期间还有一次，客户马上要我提案，但公司的设计师手上也有急活。我用 ChatGPT 做了产品效果图，最后拿到了订单。 老板后来跟我说：“早知道你可以帮我做这些，那些外包设计早就可以不用买了。” 到了4月，我又用扣子搭了发货模板和记账系统。原来需要手工对比核验的条形码、外箱码，我也开始想办法交给工具处理。 这张订单图只能证明订单记录是真实存在的，不能单靠它证明订单一定是 AI 带来的，更不是 Ohwait 的客户案例。AI 参与了产品效果图制作，之后拿到订单，是我对那次真实工作过程的记录。 那一刻让我兴奋的，其实不是发现了什么创业机会，而是我第一次觉得，模型真的可以成为人的“数字外骨骼”。 回头看这三个月，我现在有5个比较确定的结论。 ### 1. AI最好先从一个真问题开始 发货、记账、核验、临时要效果图，这些都不是什么宏大命题，但它们有一个共同点：问题原本就存在，而且有人正在为它花时间、花钱或者承担压力。 我现在判断一个 AI 工具有没有价值，还是看两件事：它有没有少让我重复
AI agents that search, summarize, and create content from academic papers.
colibris · HN
AI Assistant that verifies its own sources
Automate Salesforce pipeline updates from calls and emails
@divlohia · X
Katalyst - Agent that runs pipeline for teams on Salesforce. @joinkatalyst
Use AI agents to automate startup operations: social, blogging, SEO, revenue, and security.
u/Background-Bed-8866 · Reddit
I built an AI back office that handles startup operations while I focus on shipping I build an AI back office for founders because I was tired of juggling 15 different SaaS tools for blogging, SEO, docs, analytics, customer support, and launches. Today I finally launched on Product Hunt. Happy to answer anything about the architecture, pricing, or why I chose specialized agents instead of one general assistant. try it out: Astrodesk submitted by /u/Background-Bed-8866 to r
Task board for AI agents in VS Code with persistent context across chat sessions.
gb2d_hn · HN
It was with the transience of valuable agent session dialogue in mind that I built https://www.agentkanban.io - A key feature is context capture in the tasks which you create on the board and then progress in agent sessions. Supported agents are currently Claude and Github CoPilot in VS Code. All of your context is captured in the task and can be reloaded into new agent sessions at any point in the future. Tool use is intentionally discarded because it is proprietary in nature and therefore brea
Detects AI agent runaway loops and generates verified fix PRs for GitHub or local apply.
@void_rags · X
Introducing Orqis AI, an AI Watchdog that also fixes Agents. Have a look:
Observability platform for AI agent pipelines that detects failures and explains root causes.
@VaraadDurgaay · X
Solving the prb of observability in ai agents
Affordable memory storage layer for AI agents.
@AudaxicTech · X
Memory for AI agents, most affordable in the industry
An AI agent team plans, designs, and deploys full-stack applications with real databases and APIs.
@islamtaha · X
Shared memory for AI coding agents to store team discoveries and reduce duplicate research.
snakaya · HN
Vibsync – One Shared Memory for Claude Code, Cursor and Codex (MCP)
A directory for publishing and discovering AI agent skills.
kubeden · HN
Generalized – AI agent skills with community proof