C10. LLM Practitioner PM (AI PM Learning Program)
A complete path: lessons, projects, certification, support, and your digital PM portfolio
Hey, Paweł here. I’m excited to share the first module of our AI PM Learning Program: C10. LLM Practitioner PM.
This is where you’ll build your foundation in LLMs, from prompts to RAG to fine-tuning to basic evals.
I’ve made a few updates before publishing:
Added basic AI evals (so you’ll observe and test your LLMs from the start).
Moved advanced n8n workflows and systems to the AI Agents track.
Note 10/5/2025: I decided to split each module into:
Foundations: Demonstrated knowledge and took the exam
Practitioner: Demonstrated a real experience by building AI products
Here:
C10. LLM Foundations Certified PM
C11. LLM Practitioner Certified PM
This issue will be updated. More information:
C10. LLM Practitioner PM: The Exact Set of Lessons to Take
Here’s the exact set of lessons included in C10:
Lesson 1: Introduction to AI Product Management
Scope: Neural networks, transformers, LLMs, decoders, encoders, tokenization, reinforcement learning, loss function, self-attention, model weights.
Lesson 2: Prompt Engineering: 14 Prompting Techniques Every PM Should Know
Scope: Prompt engineering
Lesson 3: Step-by-Step: Three Essential APIs to Interact With LLMs
Scope: Completion API, Responses API, OpenAI Platform, streaming
Tools: Lovable and Supabase or Replit and SQL
Lesson 4: A Guide to Context Engineering for PMs (none of the points is agent-specific, all can be applied to LLMs, too) +
Scope: Prompt engineering, RAG architectures, short-term memory, long-term memory, how LLMs call and receive tool results
Lesson 5: How to Build a RAG Chatbot Without Coding
Scope: Vector stores, embeddings, chunking, RAG, LLM workflows
Tools: Lovable, Pinecone, Supabase, OpenAI Platform, n8n
Lesson 6: The Ultimate Guide to Fine-Tuning for PMs
Scope: RL vs. Fine-Tuning, SFT, DPO, ORPO, KTO
Tools: OpenAI or Hugging Face
Lesson 7: The Ultimate Guide to AI Observability and Evaluation Platforms
Scope: Observability, Rule-based evals, LLM-based evals
Suggested tool: PromptLayer
How to earn the LLM Practitioner PM certificate
To earn the LLM Practitioner PM certificate, you’ll complete hands-on projects and a knowledge test.
Projects
Implement an LLM chatbot (Lesson 3):
Add observability (Lesson 7),
Add one role-based and one LLM-as-judge eval (Lesson 7).
Fine-tune a model (Lesson 6) - can be combined with the previous project.
Build a standard RAG chatbot (Lesson 5).
Submit each project: pawel@productcompass.pm with “C10” in the subject.
Knowledge test
20 single-choice questions
80% required to pass
1 attempt per week (a larger pool of questions)
Questions?
In case of any questions or doubts, you get full support on our Slack:
#c10-llm-practitioner-pm
Link to join our community: Your Premium PM Resources
I’m also available during weekly office hours.
More about certificates
After completing each track (e.g., C10), you will receive a digital, sharable certificate.
I’m also working on extending accredia.io, so that each certificate can be accompanied by a set of digital asset - your digital PM portfolio. That way, you can demonstrate things you actually implemented beyond taking a quiz.
Currently, a public student’s profile looks like this: https://www.accredia.io/users/pawel-huryn
More resources & Why learn with me
Extra resources
Beyond the lessons, here are some additional resources to explore:
AI Product Manager Glossary - understand key terms
TensorFlow Playground - play with neural networks
Anthropic Prompt Engineering - my go-to resource
Interactive RAG Simulator - study common RAG architectures visually
Why learn with me?
Of course, resources alone aren’t enough - you need support. So why learn with me?
I bring 11+ years of PM experience, including running a successful B2B startup.
But what matters most is practice: rolling up your sleeves is the only way to truly retain knowledge. I’m the only PM author here who spends most of my time actually researching and building with AI - and connecting the two worlds: Product & AI.
I also work closely with Miqdad Jaffer (Product Lead, OpenAI) as an AI Labs Build Leader, and I help AI PM Certification students (#1 AI PM Cohort on Maven) crush their Capstone Projects with demos, live Q&A, and async support.
⚠️ Starting September 1, the subscription will increase to $15/month or $120/year. You can still upgrade now and lock in today’s price for life.
(30-day money-back guarantee. Many members expense it through their company’s learning budget.)
P.S. Stay tuned, C20. AI Agents Practitioner PM is next 🙌
@pawel Thanks a lot for organizing c10 - Looking forward to c20,c30 and c40.