
Overview of GenAI technology and its evolution.
Introduction to the section: Core Concepts: LLMs, Prompt Engineering, RAG, and APIs
Explanation of LLMs, their capabilities, and applications.
Best practices for creating effective prompts for AI systems.
Overview of RAG, how it enhances AI outputs, and why it matters for TPMs.
Introduction to AI platforms and tools commonly used for integrating GenAI in projects.
Introduction to the section: GenAI Opportunities.
How to identify where GenAI can add value within your product or program.
Strategies to connect AI opportunities with organizational objectives.
Steps to define AI-driven features, prioritize them, and break them down for implementation.
Key roles in AI projects (e.g., ML Engineers, Data Scientists, Analysts) and their collaboration.
Best practices for TPMs to communicate AI progress, blockers, and milestones.
Introduction to the section: Execution from Pilot to Scale.
How to set up, run, and measure the success of a GenAI pilot project.
Techniques for assessing the outcomes of AI pilots, including KPIs.
Strategies for scaling GenAI projects from successful pilots to full deployment.
Challenges around fairness, transparency, and accountability in AI.
Understanding how to set policies and ensure AI compliance.
Identifying and mitigating risks, including bias, privacy, and misuse.
Ethical guidelines are the backbone of GenAI governance, ensuring AI systems are responsible, fair, and aligned with societal values. This condensed cheat sheet highlights key areas to focus on when developing and supporting AI use cases.
Generative AI (GenAI) is transforming how products are built, decisions are made, and organizations scale. As a Technical Program Manager (TPM), you are in a unique position to lead this transformation. This course is designed to help TPMs understand, apply, and manage GenAI across programs—from strategy to execution.
In this course, you’ll learn the fundamentals of GenAI, including large language models (LLMs), prompt engineering, RAG (retrieval-augmented generation), and how GenAI APIs integrate into modern workflows. You’ll gain clarity on how to identify AI opportunities, align them with business goals, and define scalable solutions that deliver measurable impact.
Through real-world frameworks, stakeholder communication strategies, and a hands-on case study, you’ll develop the confidence to lead cross-functional teams on GenAI projects. The course also explores essential topics like AI ethics, governance, and risk mitigation—empowering you to make responsible decisions while accelerating delivery.
Whether you’re already involved in AI projects or just starting, this course provides the knowledge, vocabulary, and strategic thinking you need to stay relevant and drive innovation in today’s fast-changing tech landscape.
By the end of the course, you’ll walk away with a comprehensive toolkit to lead GenAI initiatives, communicate value to stakeholders, and create lasting business impact. No coding or data science background is required—just a passion for program management and a desire to lead the future of work.