The Ultimate AI PM Learning Roadmap

An extended edition with dozens of AI PM resources: definitions, courses, guides, reports, tools, and step-by-step tutorials

Paweł Huryn

May 28, 2025

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Hey, welcome to the free edition of The Product Compass newsletter.

Every week, I share actionable tips, templates, resources, and insights for PMs.

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Updated: Jul 22, 2025

In this issue I cover everything you need to know as an AI Product Manager.

It aggregates resources, templates, and step-by-step guides for AI PMs and AI builders.

If I had to learn AI Product Management again, I would start here:

1. Basic Concepts

Start with understanding what an AI Product Manager is.

Next, for most PMs, it makes no sense to dive deep into statistics, Python, or loss functions. Instead, you can find the most important concepts here: Introduction to AI Product Management: Neural Networks, Transformers, and LLMs.

[Optional] If you want to dive deeper, I recommend you check out an interactive LLM visualization:

[Optional] Finally, as an AI PM you will most likely work with LLMs, as they are the most cost-effective. But just in case, here are 8 other terms you might come across, explained by Generative AI:

LLM (Large Language Models): Great for natural language understanding and generation (think ChatGPT).
LCM (Latent Concept Models): Powerful in capturing nuanced concepts hidden in data.
LAM (Language Action Models): Designed to not just understand, but also take action based on language input.
MoE (Mixture of Experts): Smartly combines expertise from multiple specialized models for superior performance.
VLM (Vision-Language Models): Handles text AND images, bridging visuals and language seamlessly.
SLM (Small Language Models): Ideal for efficiency and speed, especially in resource-constrained environments.
MLM (Masked Language Models): Masters context, great at predicting masked or missing content in text.
SAM (Segment Anything Models): Perfect for precise image segmentation and detailed visual understanding.

8 AI Models You Should Know — Source: Generative AI

Before we proceed, I’d like to recommend the AI Product Management Certification:

I participated in this 6-week cohort in Spring 2024. I loved networking and rolling up my sleeves.

The next session starts on Sep 15, 2025. I secured a $500 discount for our community if you use this link to sign up:

Get a $500 discount

2. Prompt Engineering

AI Product Management, Prompt Engineering Guides

52% of U.S. adults use LLMs. But very few know how to write good prompts.

I recommend starting with resources curated specifically for PMs:

[Optional] Other generic, free resources:

Guides:
An Awesome Analysis: System Prompt Analysis for Claude 4
Tools:
- Anthropic Prompt Generator: Improve or generate any prompt
- Anthropic Prompt Library: Ready-to-use prompts
Free, Interactive Course: Prompt Engineering By Anthropic

Use those platforms to experiment with training and validation data sets and parameters such as epochs. No coding:

OpenAI Platform (start here, my favorite)
Hugging Face AutoTrain
LLaMA-Factory (open source, lets you train and fine-tune open-source LLMs)

You can practice fine tuning by following this practical, step-by-step guide: A Practical Guide to Fine-Tuning for Product Managers

4. RAG (Retrieval-Augmented Generation)

AI PM, RAG (Retrieval-Augmented Generation)

RAG, by definition, requires a data source plus an LLM. And there are dozens of possible architectures.

So, rather than studying artificial names, I recommend the following resources to learn RAG in practice:

How to Build a RAG Chatbot Without Coding: A simple exercise step-by-step
See the point ‘Three Essential Agentic RAG Architectures’ from AI Agent Architectures, where I also comment on how to generalize that knowledge
An interactive RAG simulator: https://rag.productcompass.pm/

5. AI Agents & Agentic Workflows

AI agents are the topic you can learn best by doing. I see too many BS advice by people who have never built anything.

My favorite tool, by far, is n8n, that allows you to:

Create complex agentic workflows and multi-agent systems with a drag-and-drop interface.
Easily integrate with dozens of systems (Google, Intercom, Jira, SQL, Notion, etc.).
Create and orchestrate AI agents that can use tools and connect to any MCP server.

You can start with those guides:

[Optional] And here are my favorite, free generic guides and reports:

Google Agent Companion: focuses on building production-ready AI agents
Anthropic Building Effective Agents
IBM Agentic Process Automation

Refer a friend

6. AI Prototyping & AI Building

I listed many tools, but in practice, Lovable, Supabase, GitHub, and Netlify are 80% of what you need. You can add Stripe. No coding.

Here are four practical tutorials:

[Optional] If you want to build and monetize your products, e.g., for your AI PM portfolio:

When building, focus on the value, not hype. Customers couldn’t care less about whether your product uses or has been built with AI.

7. Foundational Models

My favorite models (July 22, 2025):

GPT 4.1 for AI Agents
Claude Opus 4 for coding
Gemini 2.5 Pro for everything else

8. AI Evaluation Systems

You might have the most advanced architecture. But the real question is this: Does your product actually work?

Evals are the most critical element. And it's a task also for PMs.

A free, detailed guide: Mastering AI Evals: A Complete Guide for PMs
Error analysis: AI Evals: How to Find The Right AI Product Metrics
A massive, free FAQ: https://hamel.dev/blog/posts/evals-faq/

9. Other Resources

A few other AI PM resources that I found particularly useful over the last months:

AI PRD: A free PRD template by Miqdad Jaffer (OpenAI)
Anthropic MCP Servers: The official collection by Anthropic

Optional resources:

Awesome Generative AI Guide (GitHub): Updates, news, and materials
ChatLLM: Use all LLMs with just one $10/month subscription (I’m not affiliated)
MCP.so: The largest collection of MCP servers
microsoft/markitdown: For converting docs to Markdown (if your LLM needs to process documents)

Plus, our practical, step-by-step guides available in the archive, AI Product Management:

AI Product Manager Learning Plan — All guides are available in the archive: AI Product Management:

Thanks for Reading The Product Compass Newsletter

Hope that helps!

It’s great to explore, learn, and grow together.

Have a great rest of the week ahead,

Paweł

The Product Compass