Stanford CS193T Thinking with AI | Autumn 2026 | Core Prompting
For more information about Stanford’s graduate programs, visit:https://stanford.io/cs193t-autumn26
Lecture 1 explained what’s happening inside the model; Lecture 2 is about what you do with it. We cover how to prompt effectively — treating AI like a capable but new hire, using techniques like detailed scope-of-work prompts, the “interview me” pattern, and prompt postmortems you can reuse. We dig into trust and observability (catching confident mistakes, grounding answers in your own data, knowing when to demand evidence over assertions), the mechanics of managing long conversations (context rot, “lost in the middle,” knowing when to start fresh), and resource-mindful habits that are good for your wallet and the planet alike. We close on a thread that will recur all quarter: how to stay the one steering the AI, rather than letting your own skills and independent judgment quietly atrophy.
Speaker: Cynthia Bailey
Cynthia Bailey is a Senior Lecturer in the Computer Science Department at Stanford University. In 2023-2024, she served as an AI Policy Fellow in the United States Senate through the American Association for the Advancement of Science (AAAS). Her scholarship focuses on computer science education, AI/machine learning, and the social impacts of technology. This work includes creating groundbreaking courses such as Equity and Governance for Artificial Intelligence and Race and Gender in Silicon Valley. Her teaching and research awards include the Lloyd W. Dinkelspiel Award for exceptional contributions to undergraduate education at Stanford, the Lasting Impact Award from the International Computing Education Research conference, a "Top 10 Papers of All Time" award at the 50th anniversary of the ACM SIGCSE Technical Symposium, and the Stanford Society of Women Engineers' Professor of the Year. She has consulted for Apple, NASA, law firms, and machine learning startups. She holds a Ph.D. in Computer Science from UC San Diego.
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