About the Course:
In 2026, a Product Manager’s job isn't just to write requirements; it’s to manage uncertainty. This workshop explores the "AI PM" toolkit: moving beyond RAG hype to build production-grade AI features. We cover how to design Synthetic Evals to catch model hallucinations, how to manage
Token Economics for profitability, and how to transition from fixed roadmaps to outcome-based Agentic Workflows. If you are a PM or Lead Developer, this session provides the blueprint for building AI products that are reliable, ethical, and profitable.
Course Objectives:
By the end of this workshop, participants will be able to:
- Define the difference between "Traditional" and "Probabilistic" product management.
- Build a basic AI Evaluation Pipeline (Evals) to measure model reliability.
- Calculate the ROI of AI by balancing GPU/Token costs against user value.
Who is the Target Audience?
- Product Managers, Senior Developers, Technical Founders, and Business Analysts.
Basic Knowledge:
- Basic familiarity with business metrics and user-centered design
- No prior machine learning experience required
Curriculum
Total Duration: 1 Hour 30 Minutes
Ability to write a PRD for an AI Feature (including failure modes)
Understanding of RAG vs. Fine-tuning trade-offs for product market fit
Strategies for "Human-in-the-Loop" UX to handle AI hallucinations gracefully