Stanford launches CS329Z: Engineering AI Agents, with full materials public
stanfordnlp · x · 2026-10-31
Stanford's new Fall 2026 course CS329Z, taught by Diyi Yang, Michael Ryan, and John Yang, teaches students to engineer agentic systems — from simple LLM pipelines to compound AI systems and autonomous agents.
Topics include LLM foundations and context engineering, RAG, function calling/MCP and tool use, DSPy, LangGraph and agent harnesses, ReAct, agent memory and multi-agent collaboration, prompt optimization, RL and data engineering, agent evals, LLM-as-Judge, safety mechanisms, and coding agents.
The course is heavily hands-on: students build core components (RAG, tool use, agent loops) from scratch before learning frameworks, complete two applied homeworks including building an agent harness from zero, and ship a quarter-long project. Slides, schedule, reading lists, the GitHub repo, and HW1 code are all publicly available.
Related event: Stanford Launches CS329Z Course on Engineering AI Agents(3 posts)→
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