大家都在说 AI 能替代人力,但真要用 AI 平替一家公司的全部岗位,从哪下手、怎么编排,相信大多数人其实都没概念。
最近看到 Headcount Zero 这本开源书籍,为我们讲怎么用 AI 智能体搭建一家「零员工」公司,思路挺有意思的。
核心方案是一个创始人加一整张由 AI 智能体组成的组织架构图,通过开源平台 Paperclip 来调度所有智能体协作完成工作。
GitHub:https://t.co/iTRdoxwekb
全书分四个部分:先讲为什么可行,再解释 AI 智能体和聊天机器人的本质区别。
然后手把手教你设计智能体组织架构、搭建治理机制,最后还聊了同时运营多家公司的可能性。
想要尝试一人企业的超级个体的朋友,这本书提供了一份颇为不错的实战指南,可以看下。
AI agents are evolving fast.
We’ve moved beyond simple chatbots and prompt engineering. Modern AI systems now need tools, workflows, and real-world connectivity to operate effectively in production.
That’s where Tools, MCP, and Skills come in.
In tomorrow’s hands-on webinar, we’ll break down how these three layers work together to build scalable, composable AI agents capable of real-world interaction.
You’ll learn how to:
• Build custom tools
• Connect agents using MCP
• Package reusable workflows into Skills
• Design production-ready AI agent systems
📅 Tomorrow - May 13, 2026
⏰ 11:00 AM PST
Featuring Kwasi Ankomah | Lead AI Architect at SambaNova Systems
If you haven’t registered yet, now’s the time: https://t.co/29bG2NzMye
#AI #AIAgents #LLM #GenerativeAI #MCP #AgenticAI #ArtificialIntelligence #AIEngineering #MachineLearning #Python
If you're serious about AI engineering (in 2026), then learn these 13 concepts:
1 How Vector Database Works
→ https://t.co/FVxan8xHH3
2 How RAG Works
→ https://t.co/cGmunPTUlb
3 Design Personal Chat Assistant
→ https://t.co/nNWq3onTnW
4 LLM Concepts - A Deep Dive
→ https://t.co/5lCKxq2g4N
5 How to Design an AI Agent
→ https://t.co/JvnPd9773A
6 What is Reinforcement Learning
→ https://t.co/AVpl9j1oit
7 LLM Evals 101
→ https://t.co/nv3Ol8W53p
8 Context Engineering 101
→ https://t.co/OMkiZhkODL
9 AI Coding Workflow 101
→ https://t.co/paIf9ksIU9
10 Agentic Patterns, Simply Explained
→ https://t.co/8YdBBWvTj1
11 How AI Agents Work
→ https://t.co/tk3zkCjRvg
12 Multi-Agent Architectures, Clearly Explained
→ https://t.co/rS5QQS7Jln
13 How MCP Works
→ https://t.co/wgf8gHnnkn
What else should make this list?
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