CMU 11-768: AI Agents – Lectures and Slides

Carnegie Mellon 11-768: AI Agents

Guide

All

01-Course Overview - What Is an Agent
01-Course Overview - What Is an Agent
02-Agent Capabilities 1 - Tool Use
02-Agent Capabilities 1 - Tool Use
03-Agent Capabilities 2 - Context Management for Long-Context Agents
03-Agent Capabilities 2 - Context Management for Long-Context Agents
04-Agent Capabilities 3 - Skills and Memory
04-Agent Capabilities 3 - Skills and Memory
05-Agent Capabilities 4 - Planning, Task Decomposition, and Multi-Agent Coordination
05-Agent Capabilities 4 - Planning, Task Decomposition, and Multi-Agent Coordination
06-Domains 1 - Coding Agents
06-Domains 1 - Coding Agents
07-Domains 2 - Computer Use Agents
07-Domains 2 - Computer Use Agents
08-Training 1 - Supervised Fine-Tuning (SFT)
08-Training 1 - Supervised Fine-Tuning (SFT)
09-Training 2 - Reinforcement Learning Basics
09-Training 2 - Reinforcement Learning Basics
10-Domains 3 - Deep Research Agents
10-Domains 3 - Deep Research Agents
11-Training 3 - Advanced RL Algorithms
11-Training 3 - Advanced RL Algorithms
12-Training 4 - RL Systems
12-Training 4 - RL Systems
13-Safety 1 - Agent Safety
13-Safety 1 - Agent Safety
14-Frameworks 1 - OpenHands
14-Frameworks 1 - OpenHands
15-Frameworks 2 - Orchestration and Monitoring
16-Agents and the Future of Work
17-Interaction 1 - Multi-Agent Interaction

Winda

Real incidents of agent harm, threat models like prompt injection and malicious users, defenses through red teaming and safety training, and sandboxing techniques to limit what agents can access and do.

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