Introduction to AI Agents
summary
A practical course that shows how to wire LLMs to tools and storage, with working notebooks using LlamaIndex and LangChain demos, OpenAI keys, vector embeddings and a retriever that indexes PDFs. Examples include a RAG on Lyft and Uber 10‑K filings (PDF → embeddings → query engine) and a simple react agent using GPT‑4o plus a web‑scraping tool for movie sentiment. Demos run but reveal limits: reasoning models slow, hallucinatory outputs require ranking and guardrails, and production scale remains rare.
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chapters (14)
- 0:00AI agents introduction
- 1:54AI agent deployment state
- 12:58What defines an AI agent
- 23:30AI agent building blocks
- 37:15AI agent types and uses
- 44:49React agents and reasoning
- 58:24Tools for AI agents
- 1:06:08Agent chains for automation
- 1:15:23Frameworks for AI agents
- 1:23:49AI agent development challenges
- 1:33:18Building agents notebook
- 1:51:58RAG deep dive
- 2:03:16NLP vs AI agents
- 2:07:11AI agent career advice
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