为团队构建真正的 Agent OS：来自 Ankole 的工程实践
此为《Building a Real Agent OS for Teams: Lessons from Ankole》的中文翻译版，倘有歧义请以英文原版为准。1. 从单用户 Harness 到集体认知在独立开发者的笔记本电脑上，Claude Code、Codex 与 OpenCl...
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#enterprise-ai
25 篇笔记
腾讯 2026 AI Agent 企业解决方案及落地实践手册
腾讯、腾讯云与 WorkBuddy 联合发布的 78 页《2026 AI Agent 企业解决方案及落地实践手册》精读：七类提效场景与 WorkBuddy / ClawPro / Agent Runtime / TokenHub 四件套，三阶段跃迁与三代办公，研发运维、SaaS、内容生产、AI 社交陪伴、游戏 NPC、智能客服与生态共建的方案和案例。
What FDE means at OpenAI
What forward deployed engineering means at OpenAI
Building agents: When to fold subagents into your main agent loop
When to consider using fewer subagents and how to migrate the into your main loop.
How Uber connects its AI agents to models and tools
In this blog we will see how Uber puts two gateways around its AI agents, and how every call carries the person who asked.
手脑分离与边界治理：企业级 Agent 平台的总体架构设计
在本地终端环境中，开发者早已习惯使用 Claude Code、Cursor 或各类命令行 Agent 进行自主编码与系统运维。模型推理循环与操作系统的 Shell、文件系统和环境变量运行在同一台宿主机上，通过本地进程树与内存字典直接驱动。这种“脑与手同机”的拓扑，在个人开发机上极...
来自 every 的自我批评，不应该让每个员工一个 Agent
Every 是一家做 AI 应用和内容的公司，最近把自己用了半年的企业 Agent 公开，同时批评自己之前的做法：受 OpenClaw 的影响，Every 为员工每人一个 agent，但在实践过程中，发现了在「维护」层面产生了诸多的问题，导致这种方法不可持续。它的联合创始人兼 C...
构建你的 AI FDE 能力入门篇： 0x01 Palantir 架构中心·中文全解
本系列编译自 Palantir Architecture Center 官方文档，共 7 篇，从整体架构到各核心层逐层拆解 Palantir 的技术体系。建议阅读顺序总览：Palantir 架构中心导读 —— 全局地图，先读这篇 AIP、Foundry 与 Apollo：一体化平...
AI agents meant to replace Meta workers made “large-scale, disruptive actions”
Report shows Meta's challenges replacing people with AI agents.
How to Build a Company Brain That Gets Smarter Every Week
I am going to show you how to turn every correction, decision, and useful workflow your team gives AI into one company brain that makes ever...
Moats in the age of floods
As the labs break revenue records and absorb more capabilities, there's a growing narrative that the great flood of intelligence they bring ...
An open source rival to Claude Managed Agents just launched
TrueFoundry's open source TrueForge challenges Claude Managed Agents with vendor-neutral model choice, claiming 50% lower agent costs and no lock-in.
How to Build a Shared AI Harness for Your Team
I am going to show you how to turn the models, agents, skills, and automations living across your team's tools and workflows into one coordi...
The company brain has a permissions problem
Every company is connecting Slack, email, docs and meetings into one brain that gives everyone access to everything the company knows.Nobody...
所有想做 FDE 的人，都该读懂 Palantir 这套方法
大模型进入企业以后，最难的一步是把一家公司的数据、规则和权力关系，变成 AI 能够理解并安全执行的系统。2026 年 5 月，OpenAI 成立了一家专门负责企业部署的新公司。它准备投入超过 40 亿美元，并计划通过收购 Tomoro，一次带入约 150 名 Forward De...
Cloudflare OS: an open platform for agents, apps, and work
Cloudflare OS is an open-source platform that lets everyone in your company build apps, automate work, and safely access internal systems, shaped around what your organization knows and how it operates.
How Stripe Built Kai on Deep Agents in 1 Week
Learn how Stripe built Kai, a company-wide AI agent on LangChain, LangGraph, and Deep Agents, reaching 5,000 users in roughly 4 weeks.
YC 开源 QM：当每个员工都有 Agent，公司需要怎样的协作系统？
未来一家公司里，可能每个员工都有自己的 Agent。它们能读文件、查数据库、写代码、回复邮件，也能在后台持续运行任务。问题随之而来：这些 Agent 应该看到什么？记住什么？使用谁的账号？哪些能力可以共享？危险动作由谁批准？7 月 31 日，Y Combinator 开源的 QM...
How we built our knowledge base
Authors: @hi_im_isaac_, @learnwdaniel, @gaozenghaonote: the interactive version of full technical blog available: https://www.cerebras.ai/b...
Reshaping the economics of software: Building a future-ready core with Al/works™
Shift from AI experimentation to execution. Discover how Thoughtworks AI/works™ reshapes the economics of software delivery.
Towards org-level agent harnesses
Claude Tag has grown rapidly in Anthropic. I want to share some of the reasons for this and the behavioral shifts I’ve seen with this agent ...
Building Reliable Agentic AI Systems
AI helping pharmaceutical researchers query decades of information buried in PDF reports
Every Company's First AI Strategy Should Be a Skill Library
Watch your best people work long enough and you notice something. They have patterns.A great salesperson approaches an important call with a...
Memory Is Purpose
LLMs compressed the internet into weights. Agents need to compress work into state.LLMs are among the most successful artificial memory syst...
How Anthropic enables self-service data analytics with Claude
Tips and approaches to maximizing Claude’s ability to drive self-serve data insights