CS 224V

Agentic AI

Fall 2026

About CS 224V

AI agents powered by Large Language Models are already transforming how we work, learn, and solve problems — and we are only at the beginning. As these systems grow more capable, they hold extraordinary promise for accelerating scientific discovery and democratizing access to high-quality medical, legal, and educational services worldwide. This is a project course coupled with rigorous lectures on the principles, methodologies, and cutting-edge research underlying agentic AI. Students undertake a substantial quarter-long project in either foundational methodology research or building novel agents in a domain of their choice.

Topics include:

  • Minimizing hallucination in question-answering and task-oriented agents using Retrieval-Augmented Generation (RAG) and formal task descriptions.

  • Hybrid knowledge reasoning over databases, knowledge bases, and unstructured text.

  • AI-driven knowledge curation and discovery for scientific research.

  • Improving the accuracy and interpretability of decision-making agents through formal methods.

  • Automated techniques for improving the accuracy and efficiency of long-horizon agents.

👩‍🏫 Instructor Monica Lam
(lam at cs)
🧑‍🏫 Head TA Cyrus Zhou
(zikai at cs)
🧑‍🏫 TA Harshit Joshi
(harshitj at cs)
🕒 Time Mon, Wed 3:00-4:20pm
🏫 Location CoDa B80
💳 Credits 3-4 units

Office Hours

Office hours will be posted here in the first week of class.

Project Mentors

Every project is mentored and supervised on a weekly basis. Mentors for this year include:

  • Yucheng Jiang (yuchengj at cs)
  • George Liu (sliu22 at cs)
  • Jiuding Sun (sunjd24 at cs)
  • Cyrus Zhou (zikai at cs)
  • Harshit Joshi (harshitj at cs)

Logistics

Lectures: Monday/Wednesday 3:00-4:20pm in person in CoDa B80. Attendance is mandatory.

Recordings: video recordings of the lecture can be found on Canvas.

Slides: can be found on the Schedule and in the lecture slides folder on Canvas. Posted lecture slides are missing important details to facilitate student participation. Please make sure you watch the lectures.

Homework: can be found on the Schedule and submissions will be on Gradescope.

Contact: Students should ask all course-related questions on Ed, where you will also find announcements. For external inquiries, personal matters, or in emergencies, you can send an email to our staff email cs224v-aut2627-staff@lists.stanford.edu

Academic accommodations: If you need an academic accommodation based on a disability, you should initiate the request with the Office of Accessible Education (OAE). The OAE will evaluate the request, recommend accommodations, and prepare a letter for the teaching staff. Once you receive the letter, send it to the course staff email at cs224v-aut2627-staff@lists.stanford.edu. Students should contact the OAE as soon as possible since timely notice is needed to coordinate accommodations.

Audit Requests: To audit the course, please send an email to course staff email at cs224v-aut2627-staff@lists.stanford.edu, with the subject line "audit cs224v request."

Course Participation: We offer the course on SCPD to serve remote students; it is not to allow students take conflicting courses. In-class attendance and participation are an important part of the course. We allocate 15% of the course grade to class participation, which is important to make the most out of the course.

  1. If you are a local student, 5% of the course grade is allocated to in-class attendance and participation.
  2. We allocate 10% and 15% of the grade to local and remote students, respectively, to (1) your weekend updates, and (2) interaction with your project mentor every week.
  3. Contributions in helping others on Ed will be awarded with bonus points.

Enrollment

CS 224V has limited enrollment so as to provide adequate project and research supervision to students. The class is currently waitlist only (class #2029 on Navigator).

Prerequisites: one of LINGUIST 180/280, CS 124, CS 224N, CS 224S, 224U.

Grading

Grading is according to the following scheme: