Syllabus - Product Management course
Google-Reichman Tech SchoolDates: 22.12.26-2.3.27 Lessons: Tuesday at 16:00-20:00 Practice sessions: Thursdays 18:00-20:00
*Schedule and topics are subject to change.
Course Overview
Product management in tech companies is a fascinating profession that balances passion for technology, empathy for customers, business sense, and never ending drive for success through optimization. AI is an inherent part of the PM role. First, an AI-powered PM leverages AI tools to automate research, design, and management. Second, an AI PM is fluent in defining AI PRDs that can produce code, and leverage MCPs to add capabilities. Third, AI PMs perform cycles of Evals and set Guardrails to improve their AI product accuracy and safety.
This course is intensive, up-to-date, and comprehensive. It is not a short intro course, it dives deep into core aspects of PM and AI-PM. There are two weekly sessions, a 4-hour expert lecture-workshop session and a 2 hours hands-on practice session via Zoom. Practice is essential for learning, lecture alone is not enough.
The course is designed for professionals with 3+ years of experience, as PMs or as members of product teams (Dev, Data, Design-UX-UI, QA, CS, Research). The course covers the fundamentals of product management, all with AI integrated into the work processes: the PM role in B2C and B2B, product discovery, product metrics and optimization strategies, Product strategy and Growth, AI Metrics and Unit Economics, AI PRDs, AI Prototyping and Testing, AI Evals, Guardrails, Product operations, and Product delivery.
Unit 1: The PM Role - Frameworks and Metrics
- Lecturers: Prof. Oren Zuckerman and Ron Shahnovsky
- Topics covered: The PM role in B2C and B2B companies, the essential PM frameworks. Business metrics and product metrics, Optimization and Funnels, engagement and retention conversion strategies.
- Industry case studies* by: Gong, Monday (*subject to change)
Unit 2: Product Discovery, Design, and Prototyping
- Lecturer: Prof. Oren Zuckerman
- Topics covered: User research with and without AI, Customer interviews with real and synthetic users, Continuous Discovery, Need identification, Need validation, value creation not feature creation, problem definition and problem-solution fit, AI prototyping, user testing for value validation.
- Industry case studies* by: Simply, Appsflyer, Waze (*subject to change)
Unit 3: Job search, Job interviews, Individual strengths and weaknesses
- Lecturer: Industry mentors
- Topics covered: The PM job market, how to search, how to interview, product sense, the AI perspective, breadth and depth, prioritization, know your strengths and weaknesses.
Unit 4: Product Data, Data lifecycle, Feature Dashboard
- Lecturer: Asaf Barzilay
- Product data: Product data lifecycle, feature dashboards, custom metrics, from data to insights, reporting to product teams, reporting to management, leading impact based on data.
Unit 5: AI PM Fundamentals, AI PRDs, Evals and Guardrails
- Lecturer: Shmulik Davar, AI Consultant
- AI automations for PMs: AI PRD and Code Mapping.
- AI accuracy and safety: Evals and Guardrails.
Unit 6: Product Strategy and Growth
- Lecturer: Dudu Noy, Simply
- Topics covered: Top of the funnel acquisition, Product-led growth strategies, Roadmaps and Prioritization
Unit 7: Product Operations and Product Delivery
- Lecturer: Ron Shahnovsky, Principal Product Manager and Team Lead at Microsoft.
- Topics covered: Optimizing day-to-day work using dedicated platforms, AI PM internal automation and agents, Collaborating seamlessly with engineering teams and other partners for efficient product delivery.
Practice Sessions
Throughout the course, students will have a 2 hours hands-on practice session every Tuesday at 18:00-20:00, by Itamar Gilon. Practice sessions include training with relevant tools and working on assignments.
