DSPy vs. LangGraph: AI Agent Frameworks Explained | Stanford CS329Z Lecture 5 with Michael Ryan
Browse Stanford's online courses in Agentic AI: https://stanford.io/4AIRb2zSelf-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:
Which framework should you use to build AI agents? In this Stanford CS329Z: Engineering AI Agents lecture, DSPy contributor Michael Ryan live-codes agents in DSPy (signatures, modules, and optimizers) and LangGraph (state, nodes, and edges), then compares open-source agent harnesses like mini-SWE-agent, OpenHands, and Pi, shows durable orchestration with Temporal, and shares best practices for observability and evals.
Speaker: Michael Ryan
Michael Ryan is a CS PhD student at Stanford University developing human-centered, open-source AI systems that augment human intelligence and reflect the plurality of human values. His contributions to the DSPy open-source project enable developers to optimize multi-stage AI systems, and his algorithms are used for automatic AI prompt optimization at Meta, Google, Dropbox, Amazon, and other organizations.
Course website: https://cs329z.stanford.edu/
Watch the full CS329Z playlist: https://youtube.com/playlist?list=PLPRcF5HR02_U&si=3Z4OYphngcmQ0GIy
Recorded 10/07/2026 in CS329Z: Engineering AI Agents, a graduate course at Stanford University taught by Diyi Yang, Michael Ryan, and John Yang.
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