How I'd Learn AI Agents From Scratch | Ex-Google, Microsoft Engineer

If you want to master AI agents in 2026 and actually build systems that can reason, plan, and take action on their own- this video is your complete roadmap. I walk you through exactly what you need to learn, in what order, and which free resources will actually get you there- without wasting months chasing hype. The space feels overwhelming right now. Everyone's throwing around words like agents, autonomy, multi-agent systems, tool use, planning, memory- and it all sounds exciting, but also kind of chaotic. You're not too late. But you do need a plan. That's exactly what this video gives you. Chapters: 00:00 – Why You Need a Roadmap for AI Agents 01:08 – Prerequisites: Python, APIs, ML Fundamentals 03:25 – Month 1: Foundations & Architecture 05:17 – Month 2: Agent Frameworks & Memory 06:55 – Month 3: Tools, APIs & Multi-Agent Systems 08:06 – Month 4: Evaluation, Safety & Deployment 08:55 – Month 5-6: Specialization, Advanced Topics & Capstone 10:12 – Final Advice & Resources Free Resources Mentioned: Prerequisites- Google's Python Class: https://developers.google.com/edu/python Python for Everybody (Charles Severance): https://www.py4e.com/ Month 1: Foundations Hugging Face Agents Course: https://huggingface.co/learn/agents-course Month 2: Frameworks & Memory LangGraph Documentation: https://www.langchain.com/langgraph CrewAI Documentation: https://docs.crewai.com/ Month 3-4: Tools, Multi-Agent & Production OpenAI Function Calling Guide: https://platform.openai.com/docs/guides/function-calling LangSmith (Evaluation): https://www.langchain.com/langsmith Month 5-6: Advanced & Capstone Berkeley LLM Agents Course: https://llmagents-learning.org/f24 Drop a comment: Where are you in your AI agents journey? Just starting, already building, or stuck somewhere in the middle?