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

If I had to learn AI Product Management 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: (link at the end of the thread)

2. Prompt Engineering

Best, free resources:

• GPT-4.1 Prompting Guide
• Anthropic prompt engineering
• Prompt engineering by Google
• Anthropic prompt generator
• Anthropic prompt library

(links at the end of the thread) 

3. Fine-Tuning

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

• OpenAI Platform
• Hugging Face AutoTrain

(links at the end of the thread)

4. RAG (Retrieval-Augmented Generation)

I recommend these resources:

• Rag architectures (free)
• How to build a RAG chatbot without coding (trial)

(links at the end of the thread)

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)

(links at the end of the thread)

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 at the end of the thread. 

7. Foundational Models

My favorite models: 

• Claude for coding
• ChatGPT for research
• Gemini for writing 

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: at the end of the thread

Hope that helps!

All links: https://bit.ly/m/aipmroadmap

What did I forget? 

P.S. In the links above, you will also find two AI cohorts I recommend. I participated in one, and I'll participating in another one in a few days.

In the links, I shared $1100+ discounts for both.

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