What you'll learn:
- Use AI prompts to run discovery interviews, synthesize user research, and turn raw notes into structured PRDs
- Plan and simulate sprints with AI model capacity, flag scope risks, and produce trade-off options before the sprint begins
- Draft multi-audience release notes from a list of closed tickets in one prompt customer changelog, exec summary, and CS briefing
- Reconstruct an incident timeline, identify root cause, and generate a full stakeholder communication package
- Apply the CLEAR framework with AI to write transparent stakeholder communications for incidents, AI features, and UAT outcomes
- Use AI as a go/no-go criteria generator and deployment checklist tool to replace subjective release decisions with objective gates
This course contains the use of artificial intelligence.
What you will learn:
This is a practical, workflow-first course for product managers who want to use AI as a daily co-pilot - not as a novelty tool, but as a reliable system that reduces the administrative load of PM work at every stage of the product lifecycle.
Across 9 modules and more than 30 lessons, you will cover every phase of product development - from discovery and requirements through development, testing, deployment, and maintenance - and learn exactly how to apply agentic AI at each stage. Nearly every lesson includes ready-to-use prompt templates you can copy, adapt, and run immediately in ChatGPT or Claude.
What is inside each lesson:
Every lesson in this course is built around a practical learning stack:
Audio podcast lesson: Narrated lesson you can consume on the go - commuting, walking, or between meetings
Infographic: Visual summary of the key frameworks, tables, and concepts from the lesson
Mind map: Structured visual overview of how the lesson fits into the broader module and course
Lesson notes database: Annotated reference notes for each lesson - searchable, scannable, ready to revisit
Slide deck: Presentation-ready slides for each lesson - useful for sharing frameworks with your team
Quiz (Q&A document): A comprehensive question bank covering all modules so you can test and reinforce your learning
Who this course is for:
Product managers who spend too much time writing, organizing, and documenting instead of thinking
PMs new to AI tools who want a structured, practical starting point
Experienced PMs who have experimented with ChatGPT but want a systematic workflow approach
Scrum Masters, product owners, and project leads who run ceremonies and manage stakeholder communications
No engineering background required. All prompts are written in plain language and explained with context.
What you will be able to do after this course:
Run an AI-assisted discovery session and convert raw interview notes into structured requirements in under 30 minutes
Generate a full backlog with acceptance criteria, story splits, and a definition of done from a feature brief
Use AI to plan sprints, simulate scope trade-offs, and manage capacity without spreadsheets
Generate multi-audience release notes from a list of closed tickets - in one prompt
Reconstruct an incident timeline, identify root cause, and draft a stakeholder communication package within an hour of resolution
Facilitate retrospectives that produce tracked, completed action items instead of forgotten sticky notes
Build and maintain a cross-sprint pattern library so recurring problems become visible before they become normalized
Module overview:
1. Discovery and research
2. Requirements and documentation
3. Roadmapping and prioritization
4. Stakeholder communication
5. Design and UX collaboration
6. Development and coding support
7. Testing
8. Deployment
9. Maintenance and retrospectives
A note on tools:
The course is tool-agnostic at the prompt level - the frameworks and prompt templates work in ChatGPT, Claude, Gemini, or any capable LLM. Where a specific tool is recommended, it is because it is the best fit for a specific task (Claude for log-heavy incident summaries, ChatGPT for structured communications), and the rationale is always explained.
