Course Syllabus for CS 177: Introduction to Product Management with AI

Course Information

CS 177: Introduction to Product Management with AI, Autumn 2026
3–5 units (3 for graduate students, 5 for undergraduates)
CoDa B80
Tu/Th 9:30–11:20am

Contact Information

Teaching Team

Primary Instructor: Christina Wodtke (she/they)
Email: cwodtke@stanford.edu
You may call me “Christina” in writing and when we talk.

Albert Collell
Email:

Course Assistants:

Office Hours

Christina: Wednesdays by appointment (email me to set up a time)
CAs: during studio, or by appointment

Course Overview

Product managers have messy, overloaded, interrupted days, and AI is changing what the job looks like. In this class you’ll learn product management by doing it: your team spends the quarter finding a real problem in PMs’ working lives, proving it’s worth solving, and building and testing an AI-powered product that solves it.

You’ll interview working PMs, pull patterns out of what they tell you, size the market, and pitch the problem you want to bet on. Then you’ll test your value proposition before you build, prototype with AI tools, run experiments on your riskiest assumptions, set metrics and OKRs, and plan how you’d take it to market. Along the way we’ll cover what the job actually is, how product teams work, and the ethical calls PMs make every week.

Course Learning Goals

Through active engagement and completion of course activities, you will be able to:

• Run customer discovery interviews and turn them into problems worth solving
• Size a market and map a competitive landscape
• Define an ideal customer and a value proposition, and test them before you build
• Prioritize with users and scope an MVP
• Find your riskiest assumptions and design cheap experiments to test them
• Prototype with AI tools, and check whether an AI feature works using evals
• Set metrics and OKRs that fit the product
• Price a product and plan its go-to-market
• Work as a team: set norms, have creative conflict, and resolve it fairly
• Give and receive behavioral feedback
• Pitch a product decision and defend it with evidence
• Recognize the ethical tradeoffs in everyday product decisions

Course Materials

Technology: You will need a device that connects to the internet so you can access email and Canvas. All course details and materials will be posted on our Canvas course site. You can borrow equipment and access other learning technology from the Lathrop Learning Hub.

AI tools: You’ll need access to an AI assistant and an AI prototyping tool. We’ll help you sign up in Week 1.

Readings: All readings will be posted on Canvas.

These books are recommended for anyone who wants to be a product manager:

• Inspired, Marty Cagan
• Product Management in Practice, Matt LeMay
• The Mom Test, Rob Fitzpatrick
• Continuous Discovery Habits, Teresa Torres
• The Lean Product Playbook, Dan Olsen
• User Story Mapping, Jeff Patton
• Testing Business Ideas, David Bland
• The Lean Startup, Eric Ries
• Incorruptible, Eric Ries
• Business Model Generation, Alex Osterwalder
• Escaping the Build Trap, Melissa Perri
• Build Better Products, Laura Klein
• Thanks for the Feedback, Douglas Stone and Sheila Heen
• The Fearless Organization, Amy Edmondson
• Radical Focus and The Team That Managed Itself, Christina Wodtke

Affordability of Course Materials

All students should retain receipts for books and other course-related expenses, as these may be qualified educational expenses for tax purposes. If you are an undergraduate receiving financial aid, you may be eligible for additional financial aid for required books and course materials if these expenses exceed the aid amount in your award letter. For more information, review your award letter or visit the Student Budget website.

Coursework and Grading

This is a project-based class with embedded ethics. Most of your work goes into one quarter-long team project; see The Quarter Project page for the full description, timeline, and rubrics.

Each week has three pieces of work:

• A project assignment (team). The week’s reading is part of it.
• A Product Sense Pushup (PSP) (individual): a short analysis of how three real companies handle that week’s topic. Pushups build the muscle; do them every week.
• An ethics assignment (individual): a reading and response, or an in-class discussion.

The project ends with three finals in Week 10: a One-Pager, a working Prototype (shown at the Science Fair), and a Final Pitch.

This course is 3 units for graduate students and 5 for undergraduates. The workload is the same for both: about 15 hours per week: 4 hours of class, 2 hours of studio, and about 9 hours outside of class. Each assignment lists an estimated time so you can plan.

The course schedule at the end of this syllabus lists assignments and due dates. You may take the course for a letter grade or credit/no credit. The table below shows how each type of work counts toward your grade under either option.

Category	% of Grade	Notes
Attendance and participation in class and studio	20%	2 absence “passes,” no questions asked. Only 1 of the 2 can be a studio. Arriving 15 or more minutes late counts as half an absence; leaving more than 30 minutes early without permission counts as a full absence.
Weekly individual assignments (PSPs and ethics)	20%	Your two lowest grades are dropped. You must complete at least 75% of these assignments to pass. Up to 3 can be revised and resubmitted for up to full credit (see Deadlines and Late Submissions).
Quarter project (team)	50%	Weekly project assignments on the check scale, a one-pager draft, and three finals (One-Pager, Prototype, Final Pitch). Everyone on the team gets the same project grade.
Team reviews	10%	Team feedback forms at midpoint and at the end of the quarter. Don’t make your teammates hate you.

Course Structure

This course combines in-person class sessions, required weekly studios with the CAs, and assignments posted on Canvas.

All readings, slides, and assignments will be posted on Canvas, and announcements will be made through Canvas. Submit assignments through the Canvas Assignments tab unless the assignment says otherwise.

Some assignments involve posting on the class WordPress blog (highercommonsense.com). Post questions on Slack, accessible through the Canvas Slack tab, whenever you can.

Class meets Tuesday and Thursday, 9:30–11:20am. Sessions are highly interactive, a mix of lecture and team exercises, so they are not recorded; slides are posted on Canvas. Attendance is mandatory.

Studio meets once a week for two hours with a CA, starting in Week 2. CAs schedule studios any time after Tuesday’s class. From Week 3, the first hour is reporting: every team reports on its week in Lean LaunchPad format (last week we thought… then we did… now we think… next we’ll…). The second hour is team work time, with the teaching team there to help. Historically, teams have a hard time finding time to meet. Studio fixes that.

Homework is due on Canvas at 9:30am (the start of class) on the day listed, unless the assignment says otherwise.

Course Policies

Presence and Participation

Thinking through hard product questions is most productive, and most fun, when you do it out loud with other people. That’s why attendance and participation are a large part of your grade. We also know things happen, so everyone gets 2 “passes.”

• Class: You can use both passes on class sessions. If you miss a class, review the slides. Beyond your passes, you can make up a missed class by reviewing the slides and submitting a 500-word statement on what you learned and how you would have contributed.
• Studio: You can use 1 of your passes on a studio. Beyond that, studio absences affect your grade and can’t be made up. Studio work matters to your team, so your absence affects everyone on it. If you miss a studio, go over its content and activities so you don’t fall behind.
• Arriving 15 or more minutes late to a class or studio counts as half an absence.
• Leaving a class or studio more than 30 minutes early without permission counts as a full absence.
• Even if an absence is excused, any work due at that class or studio is subject to the deadline policy below.
• If you expect ongoing challenges with attending class or submitting work on time, tell us in the course application and follow up with an instructor as soon as possible.

Deadlines and Late Submissions

Deadlines are listed in the course schedule, along with estimated completion times, so you can plan around your other commitments. Despite the best planning, life happens. So:

• An assignment isn’t late until we start grading it. If it hasn’t been submitted by the time we grade, it’s late.
• After that, your grade on the assignment drops one step (e.g., ✓+ to ✓, or A− to B+) for every 12 hours it’s late, starting from when grading begins.
• You may revise and resubmit up to 3 weekly individual assignments (PSPs and ethics) for up to full credit. Resubmissions are due within 1 week after the grade is released, with “resubmit” in the assignment comments.
• Because the quarter moves fast, late resubmissions won’t be accepted, barring extenuating circumstances.

The Honor Code

Class meetings and studios in this course are highly interactive. You’ll hear plenty of great ideas from your peers, and if things go as planned, you might even change your mind based on what others say. However, you are evaluated as an individual and are expected to cite the sources and people you learned from and borrowed from, as a display of academic, intellectual, and creative integrity. Failing to do so violates Stanford’s Honor Code and is a serious offense, even when unintentional. Conduct prohibited by the Honor Code includes all forms of academic dishonesty, among them unpermitted collaboration and representing others’ work as your own. Please review Stanford’s Honor Code, the recommendations from the Office of Community Standards, and the documentation and citation resources from the Hume Center for Writing and Speaking. When in doubt, ask your CA.

AI Policy

This is a class about product management with AI, so AI shows up in two places: in what you build, and in how you work.

In what you build. Your quarter project must use AI to make a PM’s working life easier or better, and AI has to do real work in it, not decorate it. You’ll learn to check that it works by writing evals in Week 8.

In how you work. AI is a tool. Use it where it makes you better, not where it replaces the thinking this class is trying to teach.

You may use AI to:

• Transcribe interviews and usability sessions (with the participant’s permission)
• Build prototypes, including vibe coding
• Second-check your synthesis: after your team has done its own, ask AI what it sees, and compare
• Critique your drafts, scripts, and decks
• Brainstorm, after your team has brainstormed first
• Do the AI exercises we assign in class and studio

You may not use AI to:

• Conduct interviews or tests, or stand in for users. An AI persona saying it would buy your product is not evidence.
• Generate findings. Your insights have to come from what real people said and did.
• Write your reflections for you.

Check everything. AI makes up numbers, sources, and quotes, and does it confidently. If a market size, competitor fact, or statistic came from AI, trace it to a real source before you use it. If you can’t find one, you can’t use it.

Cite it. Note where you used AI and for what. A line at the end of the submission is enough (“AI transcribed our interviews; we used Claude to critique our script”). Using AI without saying so, where it matters, is an Honor Code issue.

We don’t care if it’s AI; we care if it’s any good. AI writes bland, clichéd prose. We’d rather read a reflection with typos than a smooth one that says nothing. We grade the quality of the work.

Extended Absences

Despite our precautions, one or more of us may get sick, need to care for someone who is sick, or need an extended absence for other reasons during the quarter.

• If the instructor needs to be absent, an expert substitute will be arranged.
• If a student needs an extended absence before more than 70% of coursework is completed, there may be options to withdraw from the course or to set a schedule for making up coursework later in the quarter. Students in this situation should talk to the Office of Accessible Education and to their CA or instructor as soon as possible.
• If a student needs an extended absence after at least 70% of coursework is completed at a passing grade or higher, they may request an Incomplete. Incompletes award no credit and can drop students below the minimum required unit load, which could affect academic progress, graduation, NCAA and Veterans certifications, and financial aid.

Course Privacy Statement

As noted in the University’s recording and broadcasting courses policy, students may not audio or video record class meetings without permission from the instructor (and guest speakers, when applicable). If the instructor grants permission, or if the teaching team posts videos, students may keep recordings only for personal use and may not post them online or otherwise distribute them. These policies protect the privacy rights of instructors and students, and the intellectual property and other rights of the university. Students who need lectures recorded as an academic accommodation should contact the Office of Accessible Education.

In-Person Instruction, Fall 2026

All live instruction and participation in this course is in person. Because class time is so interactive, there’s little lecturing and little reason to record sessions. Still, circumstances may keep you from attending: you, your peers, or the teaching team might wake up unwell or need to isolate for everyone’s safety. So we ask that you:

• Skip class or studio if you’re feeling unwell.
• Review the class slides and activity materials posted on Canvas for sessions you miss.
• Complete any assignments posted on Canvas for sessions you miss.
• Come to office hours with your instructor or CA to ask questions and catch up.
• Remember that you can miss up to 2 class sessions without questions or penalty (your 2 passes).
• Know that if you must miss more than 6 days of class or studio for medical reasons, the teaching team will work out an alternative plan for completing coursework.

We want you to learn, and enjoy learning, in this course as much as possible, and we’re committed to meeting you where you are and helping you finish the course successfully. Reach out to us, your Academic Advisor, or both, to talk through concerns and questions so we can work on them together.

Academic Accommodations

Stanford is committed to providing equal educational opportunities for disabled students. Disabled students are a valued and essential part of the Stanford community. We welcome you to our class.

If you experience disability, please register with the Office of Accessible Education (OAE). Professional staff will evaluate your needs, support appropriate and reasonable accommodations, and prepare an Academic Accommodation Letter for faculty. To get started, or to re-initiate services, visit oae.stanford.edu.

If you already have an Academic Accommodation Letter, please share it with us at the earliest opportunity so we can partner with you and OAE to identify any barriers to access and inclusion you might encounter in this course. Email it to the whole teaching team in one group email.

Students who are immunocompromised should register with the OAE as soon as possible.

Student athletes who expect challenges participating in class or submitting assignments on time should speak to an instructor or CA as soon as possible about available alternatives.

Course Schedule

Here is an overview of class topics and due dates. Please complete the team formation form on time so we can finalize rosters and teams. This schedule may change based on student feedback and input. Canvas modules are the source of truth.

Unless noted, work is due at 9:30am on the day listed.

Week	Dates	Topics	Due
1: What PMs do	Tue 9/22 Thu 9/24	What a PM does · intro to interviewing · PM + AI	Thu 9/24: cold interviews · team formation form
2: Discovery	Tue 9/29 Thu 10/1	Teaming and norms · business models · market sizing	Tue 9/29: Week 1 PSP Thu 10/1: ethics (Ethical Jobs)
3: Discovery	Tue 10/6 Thu 10/8	Ideal customer (ICP) · competitive analysis	Tue 10/6: round 2 interviews + patterns · Week 2 PSP Thu 10/8: ethics (Fair Use or Piracy, in class)
4: Discovery	Tue 10/13 Thu 10/15	Synthesis · Sanity Check pitches (Thu)	Tue 10/13: three problems · Week 3 PSP Thu 10/15: Sanity Check pitch · ethics
5: Hypothesize	Tue 10/20 Thu 10/22	Value proposition · opportunity-solution maps · story mapping · participatory roadmaps	Tue 10/20: Week 4 PSP Thu 10/22: ethics (testing on users)
6: Hypothesize	Tue 10/27 Thu 10/29	Prototyping with AI (vibe coding) · assumption mapping and test design	Tue 10/27: value prop + smoke test Thu 10/29: ethics · midpoint team feedback
7: Hypothesize	No class Tue 11/3 (Democracy Day) Thu 11/5	MVP spec · the one-pager	Thu 11/5: test cards + prototype v0 · Week 6 PSP · ethics (Disruptive Innovation)
8: Solution	Tue 11/10 Thu 11/12	Metrics · evals · OKRs	Tue 11/10: one-pager draft · Week 7 PSP Thu 11/12: ethics
9: Solution	Tue 11/17 Thu 11/19	Pricing · go-to-market · final pitch workshop · PM job panel	Tue 11/17: test results, metrics, evals + OKRs · Week 8 PSP Sun 11/22, 11:59pm: usability + GTM
Thanksgiving	11/23–11/27	No classes
10: Finals	Tue 12/1 Thu 12/3	Science Fair (Tue) · Final pitches (Thu)	Tue 12/1: One-Pager, Prototype, Final Pitch deck Thu 12/3: final team feedback form
11: End-quarter		We finalize grades this week.