Product Management
Intermediate
AI Product Roadmap Strategy
Define clear AI product value propositions, ROI metrics, and feasibility milestones.
Course Overview
Evaluate feasibility versus impact for AI features, construct product roadmaps that accommodate model uncertainty, and align engineering capabilities with business goals.
What You Will Learn
Structure AI product roadmaps that balance feasibility, risk, and impact
Define non-deterministic success criteria for probabilistic AI features
Evaluate build vs. buy decisions for LLMs, fine-tuning, and hosted APIs
Conduct ROI calculations considering API costs, latency, and human-in-the-loop review
Communicate AI capability limits and model uncertainty effectively to executives
Tools & Technologies Used
Product Roadmapping Tools
Miro
Excel/Notion
API Cost Calculators
Structured Curriculum
2 Modules · 4 Lessons · 140 Minutes Total
Module 1
Module 1: AI Feasibility & Value Proposition
2 lessons
Module 1: AI Feasibility & Value Proposition
Screen AI ideas for feasibility, unit economics, and user impact.
-
The AI Feature Feasibility Framework
Categorize product ideas into simple prompts, complex RAG, or autonomous agents.
-
Unit Economics & API Cost Modeling
Calculate monthly API token consumption, latency trade-offs, and gross margin impact.
Module 2
Module 2: Roadmapping Under Uncertainty & Execution
2 lessons
Module 2: Roadmapping Under Uncertainty & Execution
Structure milestones that adapt as AI capabilities evolve.
-
Probabilistic Roadmap Milestones
Set objective key results (OKRs) for AI accuracy instead of rigid feature output dates.
-
Managing Executive Expectations
Draft clear documentation explaining model accuracy ceilings, edge cases, and safety bounds.
Practical Project & Capstone Outcome
🚀 Capstone Project
Enterprise AI Product Roadmap & Business Case
Construct a comprehensive 12-month AI feature roadmap complete with feasibility scoring, API cost projections, risk mitigation plans, and executive presentation slides.
Prerequisites
- Basic product management experience
- Familiarity with AI product terminology
Intended Audience
- Technical Product Managers building LLM-powered features
- Product Leaders establishing AI product strategies
Instructor Information
K
Karan Malhotra
Course Author & Industry Expert
Karan Malhotra is a Vice President of Product Management who has led AI product transformations for global SaaS companies.
Frequently Asked Questions
Is technical coding required for this product course?
No. The focus is on strategic product management, unit economics, and feature feasibility estimation.