Your AI PM Journey
From first steps to advanced implementation, navigate the world of AI with confidence.
The AI PM Journey Map
Your path to becoming an effective AI product manager, tailored to your experience level and needs.
Understand the Landscape
Know the different AI implementation types and their best use cases.
Before diving into AI implementation, understand the spectrum of AI product types - from simple tools to autonomous agents. Each has distinct characteristics that determine when and how to use them.
Identify the Right Approach
Select the optimal AI implementation for your specific use case.
Not every problem requires the same AI approach. Learn our proven decision methodology to determine which implementation type aligns with your user needs, technical capabilities, and business goals.
Decision MethodologyMaster the FOBW Framework
Design for low "Fear of Being Wrong" to maximize adoption.
The key metric determining AI success isn't technical accuracy—it's how users perceive the risk of using your AI. Learn to create experiences where users feel safe experimenting with and adopting AI solutions.
FOBW FrameworkImplement Strategically
Execute your AI strategy with proven implementation techniques.
Follow our step-by-step roadmap for successful AI implementation, covering data requirements, integration strategies, testing approaches, and scaling best practices.
Implementation RoadmapLearn from Real Examples
See how leading companies have successfully implemented AI.
Examine detailed case studies showing how different organizations have navigated the challenges of AI implementation, with specific tactics, measured results, and lessons learned.
Case StudiesAI Experience Spectrum
Start with simple solutions and evolve only when necessary. Each level represents increasing complexity and different product experiences.
Evolution Framework
AI Product Evolution
Start simple and evolve only when necessary
| Experience Type | When to Use | Control How much human oversight and direction is required | Complexity Technical effort and expertise required to implement | Adoption Ease of integration into existing workflows | Impact Level of organizational influence and transformation potential |
|---|---|---|---|---|---|
Tools | Single-purpose AI actions (summarize, translate, extract) | High | Low | High | Low |
Workflows Complexity 2/5 | Connected AI actions with predefined paths | Medium | Medium | Medium | Medium |
Agents Complexity 3/5 | Dynamic workflows with autonomous decision-making | Low | High | Medium | High |
Copilots Complexity 4/5 | AI assistance requiring human iteration and guidance | High | High | Medium | Medium |
Infrastructure Complexity 5/5 | Foundation models customized for specific business needs | Low | High | Low | High |
The Evolution Principle:
Start with the simplest approach (Tools) and only evolve to more complex implementations when your specific use case demands it. This helps avoid overengineering and ensures sustainable AI adoption.
The most sustainable approach is to begin with the simplest solution (Tools) and only evolve to more complex implementations when your specific use case demands it.
Tools
Focused AI solutions that augment specific tasks with intelligence.
Workflows
AI-powered process automation that can handle multi-step tasks.
Agents
Autonomous AI systems that can execute complete tasks with minimal oversight.
Copilots
AI assistants that enable iterative collaboration on complex workflows, providing conversational feedback until tasks are completed to satisfaction.
Infrastructure
Foundational AI services that power other applications and systems.
Why Product Design Matters More Than AI Accuracy
Discover the "Fear of Being Wrong" (FOBW) – the key metric revealing how user experience, not just algorithms, drives AI success.
Successful AI isn't just about technical brilliance. It's about creating experiences where users feel safe to engage, experiment, and trust the AI. That's where FOBW comes in.
The FOBW Insight
Low FOBW products minimize the perceived risk and effort while maximizing value, encouraging adoption.
Learn how to measure FOBW and apply practical design strategies (like reversibility, transparency, and human-in-the-loop) to build AI products people actually use and love.
Essential PM Resources
Practical tools and guides to help you succeed with AI product management.
Gen AI 101
Comprehensive introduction to generative AI fundamentals for product managers.
Learn Generative AIFrameworks Library
Proven frameworks for AI product success, including BTD and AI Lifecycle models.
Explore FrameworksCase Studies
In-depth analyses of successful AI implementations at Spotify, Netflix, and more.
View Case Studies