If I had to learn AI PM again, I would start here:
1. Basic Concepts
For most PMs, it makes no sense to dive deep into statistics, Python, or loss functions.
You can find all practical concepts, like LLMs and Encoders, here: productcompass.pm/p/int…
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2. Prompt Engineering
Best, free resources:
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3. Fine-Tuning
Use those platforms to experiment with training and validation data sets and parameters such as epochs. No coding:
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4. RAG (Retrieval-Augmented Generation)
I recommend these resources:
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5. AI Agents & Agentic Workflows
Start with:
n8n you can host for free. Experiment with agents, MCP, and tools.
A practical guide to AI agent architectures (free part): productcompass.pm/p/ai-…
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6. AI Prototyping & 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.
When building, focus on the value, not hype. A free AI PRD template: productcompass.pm/p/ai-…
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7. Foundational Models
My favorite models:
Claude for coding
ChatGPT for research
Gemini for writing
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8. AI Evals
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 detailed guide to AI evals. No paywall: productcompass.pm/p/ai-…
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Hope that helps!
What did I forget?
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P.S. If you want to dive deeper, I recommend two AI cohorts. In the past, I particularly loved networking and rolling up my sleeves.
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I. AI Product Management Certification by instructors like Miqdad Jaffer (Product Lead @ OpenAI)
I participated in the cohort in 2024. The next cohort starts on July 13.
A special $500 discount for my community: bit.ly/aipmcohort
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II. AI Evals For Engineers & PMs by Hamel Husain and Shreya Shankar
They share experiences from 35+ AI implementations (GitHub, Airbnb, Google) and 25+ years of experience.
The next cohort starts on May 19. I'll be participating too.
A special $600+ discount for my community: bit.ly/aievals35