AI for Product Managers: From Research to a Shipped AI Spec
This course runs for 5h 52m. It is taught by Satyam Kumar, Shubham Keshav, published by Udemy, and was released on 2026-09-20. The course taught in en-US, includes exercise files, and uses Claude, Perplexity, NotebookLM, Lovable, v0, n8n.
Course Overview
This course teaches product managers how to use AI tools such as Claude, Perplexity, NotebookLM, Lovable, v0, and n8n to research, specify, prototype, and evaluate AI features. It is a hands-on, tool-first course focused on building a real AI product concept from start to finish, including drafting PRDs, conducting market research, building prototypes, prioritizing backlogs, writing AI feature specs, and creating evaluation rubrics.
Key Takeaways
Draft and refine a product requirements document (PRD) with AI assistance.
Conduct cited market research and competitive analysis using AI tools.
Synthesize documents and interview transcripts to generate insights.
Create working, clickable prototypes without coding.
Use AI to analyze product data and prioritize backlogs with frameworks like RICE.
Write comprehensive AI feature specifications covering grounding, cost, failure modes, and human-in-the-loop design.
Build evaluation rubrics and golden datasets to measure AI feature quality.
Design and implement human-in-the-loop agent workflows.
Present AI product concepts effectively to leadership.
Prerequisites
Some product management experience, familiarity with PRDs, backlogs, and roadmaps.
No coding, math, or machine learning background required.
Access to free accounts for AI tools used in the course.
A Google account for certain course activities.
Time commitment of approximately 12 hours for capstone projects.
Target Learners
Product managers, product owners, and business analysts with some experience.
PMs tasked with AI initiatives seeking practical, defensible approaches.
Senior PMs needing to cost and defend AI features to leadership.
Associate or aspiring PMs wanting real work samples rather than certificates.
Final Project
The course includes a core capstone project where learners research, specify, prototype, and present an AI product concept. An advanced capstone involves preparing a one-page summary and a five-minute presentation to leadership.