TECH 84 — Introduction to Agentic AI: How Intelligent Systems Reason, Act, and Transform Work
Quarter: Fall
Instructor(s): Sufian Aldogom
Date(s): Sep 29—Nov 17
Class Recording Available: Yes
Class Meeting Day: Tuesdays
Class Meeting Time: 7:00—8:30 pm (PT)
Tuition: $590
Refund Deadline: Oct 1
Unit(s): 1
Enrollment Limit: 100
Status: Registration opens Aug 17 8:30 am (PT)
Quarter: Fall
Day: Tuesdays
Duration: 8 weeks
Time: 7:00—8:30 pm (PT)
Date(s): Sep 29—Nov 17
Unit(s): 1
Tuition: $590
Refund Deadline: Oct 1
Instructor(s): Sufian Aldogom
Enrollment Limit: 100
Recording Available: Yes
Status: Registration opens Aug 17 8:30 am (PT)
Generative AI is evolving from a tool that responds to prompts into systems that can pursue goals, make plans, use tools, and act across workflows. This introductory course examines the ideas behind this shift and what it means for the future of professional work. Students explore how AI agents reason and act, how humans can collaborate with them, and where agentic systems may create genuine value or introduce new risks. Through case studies, demonstrations, and structured analysis, participants learn to evaluate agent opportunities and design a responsible human-agent workflow for their field. Optional experiments and technical extensions provide pathways for those who wish to explore agentic AI more deeply.
This course will demonstrate third-party AI tools that are not managed or supported by Stanford. Students can explore these tools on their own if they like, but use is optional. Many tools offer free versions or trials; paid subscriptions, if chosen, typically range from $25–$100 per month. See the syllabus for more details.
SUFIAN ALDOGOM
Senior Manager, Google and Researcher, MIT
Sufian Aldogom is a senior technical program manager at Google and a research affiliate with MIT CSAIL. He serves as a lead instructor with MIT Beaver Works and as a mentor for NASA's Student Airborne Research Program. His work focuses on artificial intelligence, intelligent agents, healthcare innovation, and large-scale technology systems, and he has contributed to AI research, education, and industry initiatives spanning academia and technology. Aldogom received master's degrees in systems engineering, software engineering, and business administration. Textbooks for this course:
There are no required textbooks; however, some fee-based online readings may be assigned.