AI 智能体3 weeks ago
reachpad: infrastructure for your coding agents
reachpad: 在浏览器中运行和监控编码代理的基础设施
sakuraiben · HN
Reachpad – Run all your coding agents from anywhere from the browser
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reachpad: 在浏览器中运行和监控编码代理的基础设施
sakuraiben · HN
Reachpad – Run all your coding agents from anywhere from the browser
The official Agents Game competition. Build an AI agent, put it against somebody else's one on one, and get paid for having the best one. Every move public, every replay permanent.
@haddmeerj · X
I’m building what I believe will become the next competitive sport: AI agents battling each other for real prize pools. ( )
保持AI代理活跃的基础设施，提供持久执行和状态管理。
iacguy · HN
Show HN: Durable AI agents without the workflow engine
Monitor, govern, and optimize your AI agents at scale.
@AiShivam · X
AgentStacKPro is an OS for AI agents designed to make them production-ready, and it holds incredible potential. You can also check out the project I currently developed
bgHub：为你的项目发现和集成精选的动画网页背景。
@thaipham278 · X
Just shipped bgHub 🚀 A small UI library focused entirely on backgrounds for vibe coding. AI can generate backgrounds, but it often misses the vibe, bgHub is a curated collection of ideas that actually look good. 🆓 Completely free Check it out:
Agent原生的TypeScript框架，在托管GPU上训练和部署定制模型。
@soleil_colza_ · X
在统一终端界面中协调多个 AI 编码代理和项目。
@soracstv · X
I run my AI coding agents with AgentsRoom, a visual command center for multi-agent development. @AgentsRoomDev #VibeCoding #AI
AI 代理的统一上下文层，集成邮箱、Drive、Slack、Notion 和 GitHub。
@marcin_u2 · X
-> here it is! claude finally knows everything gpt knows. and both of them know everything that's happened across your email, drive, slack, notion, github and granola :)
招聘AI同事，在3D办公室中协作完成任务。
@Anwaritoovvy · X
I’m opening the beta for Remotely. Remotely is an AI operating system for companies — a company brain inside a 3D workspace where teams, tasks, dashboards, communication, and AI agents come together. Try it here: I’m looking for feedback from founders
长上下文对话、代理规划和代码部署的独立 AI 工作台
david082321 · V2EX
我做了一个 Kimi K3 的工作台，把成本、部署、评测和使用场景整理到一起 最近看大家聊 Kimi K3 、Claude 、GPT 在 coding 和长上下文任务里的差异，发现很多信息散在不同地方：API 成本、上下文窗口、本地部署、硬件需求、评测表现、适合的使用场景，都要来回翻。 所以我整理了一个偏“导航仪”的 Kimi K3 站点： https://kimi3.org/?utm_source=v2ex&utm_medium=post&utm_campaign=kimi3_org&utm_content=create_topic 它不是单纯的介绍页，更像一个给开发者用的参考工作台。你可以快速看 Kimi K3 适合做什么、部署前要准备什么、和其他模型相比大概强在哪里，以及 API 成本怎么估算。 如果你最近也在比较 Kimi K3 、Claude 、GPT 或 GLM 这类模型，欢迎看看，也欢迎提建议。
设计并部署 AI 代理，跨任何软件自动化任务，无需 API。
@gabebenchimol · X
从社交、链上和链外数据中合成交易信号的AI代理。
@orbitant · X
Elfa just launched Iris. If you're looking for api to connect your agents for synthesises signals across social, on-chain, and off-chain market data etc 1000 credits free monthly API for your vibe coding: