AI Product Management Roadmap — Step-by-step Learning Path
Building AI and LLM-powered products: evaluating model capabilities, designing around uncertainty, and shipping responsibly
The AI Product Management roadmap
- AI Product Management Fundamentals — beginner
- The AI Product Landscape — beginner
- Types of AI Products — beginner
- Foundation Models vs Fine-Tuned Models vs Custom Models — beginner
- Build on Top vs Build the Model — beginner
- The AI Vendor and Tooling Landscape — beginner
- AI Product Case Studies — beginner
- Machine Learning Basics for PMs — beginner
- Machine Learning Fundamentals for PMs — beginner
- Training, Inference and Fine-Tuning Explained — beginner
- Understanding Model Performance Metrics — beginner
- Bias and Fairness in ML Systems — beginner
- Working with Data Scientists and ML Engineers — beginner
- Understanding LLMs and Generative AI — beginner
- How Large Language Models Work (Product-Level) — beginner
- Context Windows and Their Product Implications — beginner
- Hallucination and Its Product Consequences — beginner
- Multimodal Models and Their Use Cases — beginner
- Open-Source vs Closed Models — beginner
- Evaluating Model Capability and Limitations — beginner
- Evaluating What a Model Can Actually Do — beginner
- Building an Eval Set — beginner
- Benchmarking Models for Your Use Case — beginner
- Understanding Model Limitations — beginner
- Red-Teaming AI Features — beginner
- Continuous Evaluation After Launch — beginner
- Prompt Design and Iteration for Product — beginner
- Prompt Design Fundamentals for Product — beginner
- Prompt Iteration and Versioning — beginner
- System Prompts vs User Prompts — beginner
- Testing Prompts Systematically — beginner
- When Prompting Isn't Enough — beginner
- Data Strategy for AI Products — beginner
- Data Strategy for AI Products — beginner
- Data Labeling and Annotation — beginner
- Data Flywheels — beginner
- Privacy and Data Rights for AI Training — beginner
- Synthetic Data and Its Limits — beginner
- Designing UX for AI Uncertainty — beginner
- Designing for AI Uncertainty — beginner
- Confidence Indicators and Explainability — beginner
- Human-in-the-Loop Design Patterns — beginner
- Designing Conversational AI Interfaces — beginner
- Failure State Design for AI Features — beginner
- Evaluation Metrics and AI Quality — beginner
- Choosing Metrics for AI Features — beginner
- Human Evaluation vs Automated Evaluation — beginner
- A/B Testing AI Features — beginner
- Measuring User Trust in AI Output — beginner
- Monitoring Model Drift in Production — beginner
- Building an AI Quality Dashboard — beginner
- Responsible AI and Ethics — beginner
- Responsible AI Principles — beginner
- AI Regulation and Compliance Landscape — beginner
- Transparency and Disclosure Requirements — beginner
- Managing Bias in Product Decisions — beginner
- Building an AI Governance Process — beginner
- Roadmapping AI Features — beginner
- Roadmapping AI Features Under Uncertainty — beginner
- Prioritizing AI Use Cases — beginner
- Sequencing AI Feature Rollouts — beginner
- Planning Around Model Provider Roadmaps — beginner
- Communicating AI Roadmap Uncertainty to Stakeholders — beginner
- Cost, Latency and Model Selection Trade-offs — beginner
- Model Selection Trade-offs — beginner
- Understanding Token-Based Pricing — beginner
- Latency Budgets for AI Features — beginner
- Caching and Cost Optimization Strategies — beginner
- Building the Business Case for AI Infrastructure Spend — beginner
- Agents, RAG and Tool Use — beginner
- Retrieval-Augmented Generation (RAG) Fundamentals — beginner
- Designing RAG-Based Product Features — beginner
- AI Agents and Tool Use — beginner
- Designing Multi-Step Agent Workflows — beginner
- Guardrails for Autonomous AI Actions — beginner
- Evaluating Agent Reliability — beginner
- Go-to-Market for AI Products — beginner
- Positioning an AI Product — beginner
- Pricing AI Features and Products — beginner
- Managing Customer Expectations for AI Features — beginner
- Launching AI Features Incrementally — beginner
- Competitive Positioning in a Fast-Moving AI Market — beginner
- Working with ML and AI Engineering Teams — beginner
- Working with ML Engineers and Researchers — beginner
- Understanding the ML Development Lifecycle — beginner
- Scoping AI Feasibility with Technical Teams — beginner
- Managing AI Research-to-Product Handoffs — beginner
- Aligning AI and Product Roadmaps — beginner
- Experimentation and Iteration for AI Features — beginner
- Experimentation Frameworks for AI Features — beginner
- Rapid Prototyping AI Features — beginner
- User Research for AI Products — beginner
- Iterating on AI Features Post-Launch — beginner
- Sunsetting AI Features That Don't Work — beginner
- Career and Capstone — advanced