Stanford CS329Z Introduction — What Are Agentic Systems?
Browse Stanford's online graduate courses in Agentic AI: https://online.stanford.edu/explore?keywords=agentic%20ai&items_per_page=12&display_mode=grid&filter%5B0%5D=credits_credentials%3A1259&utm_source=youtube&utm_medium=social&utm_content=cs329z-01-what-are-agentic-systemsSelf-paced online Agentic AI course: https://online.stanford.edu/programs/agentic-ai?utm_source=youtube&utm_medium=social&utm_content=cs329z-01-what-are-agentic-systems
Lecture Overview:
Course logistics, a brief history of agents, and the anatomy of an agent: LLM core, reasoning, memory, tools, and environment. Compound AI systems and workflows vs. agents, plus the key challenges of reliability, training, safety, and evaluation.
Speaker: Diyi Yang
Diyi Yang is an assistant professor in the Computer Science Department at Stanford University, also affiliated with the Stanford NLP Group, Stanford HCI Group and Stanford Human Centered AI Institute. Her research focuses on human-centered LLMs and human-AI interaction. She is a recipient of IEEE “AI 10 to Watch” (2020), Microsoft Research Faculty Fellowship (2021), NSF CAREER Award (2022), and a Sloan Research Fellowship (2024).
Chapters:
0:00 Welcome & instructor introductions
1:18 Course overview & logistics
7:40 A short history of AI agents
14:00 ReAct, BabyAGI & AutoGPT: the agent boom
19:06 Q&A: Will model capabilities saturate?
22:05 Anatomy of an LLM agent
28:19 Planning & reasoning: CoT, ReAct, Reflexion
36:52 Q&A: ReAct vs. chain of thought
40:39 Multi-agent debate & orchestration
43:12 Agent memory: episodic, semantic, procedural
46:30 Tool use: Toolformer & Gorilla
53:31 Compound AI systems: workflows vs. agents
58:41 Tool calls & Model Context Protocol (MCP)
1:01:05 Key challenges: reliability, safety & privacy
Course website: https://cs329z.stanford.edu/
Watch the full CS329Z playlist: https://youtube.com/playlist?list=PLPRcF5HR02_U&si=3Z4OYphngcmQ0GIy
Recorded 9/23/2026 in CS329Z: Engineering AI Agents, a graduate course at Stanford University taught by Diyi Yang, Michael Ryan, and John Yang.
#AIAgents #AgenticAI #Stanford Receive SMS online on sms24.me
TubeReader video aggregator is a website that collects and organizes online videos from the YouTube source. Video aggregation is done for different purposes, and TubeReader take different approaches to achieve their purpose.
Our try to collect videos of high quality or interest for visitors to view; the collection may be made by editors or may be based on community votes.
Another method is to base the collection on those videos most viewed, either at the aggregator site or at various popular video hosting sites.
TubeReader site exists to allow users to collect their own sets of videos, for personal use as well as for browsing and viewing by others; TubeReader can develop online communities around video sharing.
Our site allow users to create a personalized video playlist, for personal use as well as for browsing and viewing by others.
@YouTubeReaderBot allows you to subscribe to Youtube channels.
By using @YouTubeReaderBot Bot you agree with YouTube Terms of Service.
Use the @YouTubeReaderBot telegram bot to be the first to be notified when new videos are released on your favorite channels.
Look for new videos or channels and share them with your friends.
You can start using our bot from this video, subscribe now to Stanford CS329Z Introduction — What Are Agentic Systems?
What is YouTube?
YouTube is a free video sharing website that makes it easy to watch online videos. You can even create and upload your own videos to share with others. Originally created in 2005, YouTube is now one of the most popular sites on the Web, with visitors watching around 6 billion hours of video every month.
