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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 :)
Farcaster自主AI代理，撰写帖子需人工批准，支持链上归属。
@afifarioss · X
AI agent layer for Farcaster. Human approves every cast. 🟦 onchain attribution. Now Solo no team. Phase 2+ needs hands.Repo: Live: Need grants / team / funding. MIT. Fork it or fund it. 🟦
@rdbuilds7 Memory Layer for AI Agents Product - https://t.co/mbRK424Ws4 Guide - https://t.co/W9xosDWLzQ
@Pankaj41521 · X
Memory Layer for AI Agents Product - Guide -
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
注册AI代理、探索研究数据集，在Base上观看实时AI经济。
@CRYPtoKong32 · X
also Join our $MUSKOX Ai Ecosystem built on Base Coin. 🪙 $AGWC Websites:
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:
在多个AI编程环境中部署编排器生成和管理代理。
@EnzoV_sc · X
I’ve built a skill for agent orchestration so I don’t have to explain any session how to manage the next task. Pretty useful Through I can make my orchestrator spawn as many agents as it needs, from all harnesses (Claude Code, Codex, Grok Build etc..)
与能记忆并学习的 AI Veiled Prime 进行持续对话。
@Vematrex · X
5M views. 13K shares. Building Veiled Prime at The most insightful AI we know how to make. Built for people doing real work. One conversation. Real memory. No resets.
用于组织和共享视觉资产的数字资产管理平台，支持 AI 代理集成。
@raster_app · X
为 AI agents 提供请求人工批准的结构化方式，支持安全重试和决策验证。
@GetAgentHail · X
AgentHail — a control layer for AI agents to request approval, execute work, and return verifiable results. Would you sign up or leave?
用于构建网站、编写代码和处理复杂任务的 Agentic AI 助手。
@durdom_evm · X
Chinese team at just dropped ZCode 3.0 and it's quietly reshaping the agentic coding landscape while everyone's waiting on Anthropic's roadmap here's what matters: GLM-5.2 is trading blows with Opus 4.8 on the benchmarks that actually count. 81.0 vs 85.0
