Stanford CS230 | Autumn 2025 | Lecture 8: Agents, Prompts, and RAG

ℹ️ EPISODE INFO

Released

November 21, 2025

Duration

1h 49m

Channel

Stanford Online

Watch on YouTube

▶ Open ↗

📝 EPISODE DESCRIPTION

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai November 11, 2025 This lecture covers agents, prompts, and RAG. To learn more about enrolling in this course, visit: https://online.stanford.edu/courses/cs230-deep-learning Please follow along with the course schedule and syllabus: https://cs230.stanford.edu/syllabus/ More lectures will be published regularly. View the playlist: https://www.youtube.com/playlist?list=PLoROMvodv4rNRRGdS0rBbXOUGA0wjdh1X NOTE: There was no class on November 4, 2025 (Lecture 7). The previous lecture is Lecture 6. Andrew Ng Founder of DeepLearning.AI Adjunct Professor, Stanford University’s Computer Science Department Kian Katanforoosh CEO and Founder of Workera Adjunct Lecturer, Stanford University’s Computer Science Department

🎤 SPEAKERS

• Kian Katanforoosh

  host

  Stanford-affiliated instructor and CEO of Workera, known for teaching applied deep learning/LLM topics (e.g., CS230).

🧾 EPISODE SUMMARY

In this episode of Stanford Online, featuring Kian Katanforoosh, Stanford CS230 | Autumn 2025 | Lecture 8: Agents, Prompts, and RAG explores practical methods to augment LLMs: prompting, RAG, agents, evals, multi-agents Base LLMs fail in practice due to domain gaps, staleness, controllability issues, limited context/attention, lack of sources, and task-specific precision requirements.

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