If This 81 Minute Video Doesn't Make You an AI PM, I'll Delete My Channel

Yes, I know what I just said. But Ankit's episode was too good! You’ll learn: - How to become an AI PM without any tech experience - 2 main categories of AI PMs and how to break into each - How to build great AI products your users love - All concepts like Evals, RAG, MCP, etc - Creating AI PM portfolio - And so much more 🎥 Timestamps: Two Types of PMs in the World Right Now – 00:00 How Much AI PMs Make in the US & India – 01:49 Why Jobs Aren’t Marketed as “AI PM” Roles – 04:19 Live Slide Share Session Begins (AI PDLC) – 05:35 What People Get Wrong About AI PM Jobs – 08:51 Why AI Product Management Is Here to Stay – 11:00 Product Development Lifecycle Explained – 12:35 Ad 1: AI Evaluations – 14:47 Ad 2: Maven Courses – 15:46 Understanding PM Canals (Idea Sources) – 16:34 How AI Will Transform the Traditional Product Cycle – 18:55 The Two Branches of AI: Predictive vs Generative – 23:10 Diving Deeper into Generative AI – 27:17 Ad 3: AI PM Certification – 28:47 How to Build Your Own AI Use Case Database – 29:34 Why You Shouldn’t Use AI for Everything – 34:10 Understanding Problem Space vs Solution Space – 36:51 Most Common Mistake People Make Entering AI PM – 40:49 The Building Blocks of AI – 47:01 Contextualization (Prompts, Fine-Tuning, RAG) – 50:24 The Limitations of AI — Why You Still Need Evals – 56:18 Case Study: AI-First Job Search Website – 58:49 Prompt Engineering Breakdown for the Case Study – 01:02:09 Understanding and Leveraging AI Agents – 01:03:40 Introducing the MCP Framework – 01:08:07 How to Build Your AI PM Portfolio – 01:11:37 Your Next 7 Steps to Becoming an AI PM – 01:16:04 Closing Thoughts and Final Notes – 01:18:41 ---- Podcast transcript: https://www.news.aakashg.com/p/ankit-shukla-podcast 💼 Check out our sponsors: 1. The AI Evals Course for PMs & Engineers :Get $800 off with this link - https://maven.com/parlance-labs/evals?promoCode=ag-product-growth 2. Maven: Get $100 off my curation of their top courses - http://maven.com/x/aakash 3. Product Faculty: Get $500 off the AI PM certification with code AAKASH25 - https://maven.com/product-faculty/ai-product-management-certification?promoCode=AAKASH25 👀 Where to Find Ankit: HelloPM: https://hellopm.co/?ref=aakg X: https://x.com/AnkythShukla LinkedIn: https://in.linkedin.com/in/ankythshukla YouTube: https://www.youtube.com/@hellopm 👨‍💻 Where to find Aakash: Twitter: https://www.twitter.com/aakashg0 LinkedIn: https://www.linkedin.com/in/aagupta/ Instagram: https://www.instagram.com/aakashg0/ 🔑 Key Takeaways: 01. Stop Shipping Blind. Your AI product isn't truly valuable until you validate it. Go beyond just building; understand user needs deeply with personas, journey maps, and jobs-to-be-done. 02. MOM Test = Your Secret Weapon. The "MOM Test" is about asking questions that even your most supportive friend can't lie about. Don't ask if users "would" use your AI. Ask about their past behaviors and real problems. This helps you define success metrics and avoid building a fancy toy nobody needs. 03. Evaluate Everything, Relentlessly. AI Evals are not just a technical task for engineers, but the most critical tool for Product Managers to build high-quality, trustworthy AI products. Use them to understand, refine, and continuously improve your AI. 04. Passion Won't Land the Job. Proof Will. "I'm passionate"...great I guess, but recruiters want to see what you've done. Your portfolio is your direct line to showing you can actually do the job. 05. Build Your AI Portfolio. Now. Don't wait for experience. Create product teardowns of AI tools, develop case studies, or launch small side projects. This is your living, breathing proof of thinking and skill. 06. Forget the Resume. Add Value. The ultimate job hack? Identify a problem at a target company and propose a solution, or even build a prototype before you apply. This showcases initiative and concrete skills. 07. You’re At Fault (Brutal, I Know). Nailing Prompt Engineering is a direct path to better AI outputs. If your AI misbehaves, it's often your fault for unclear instructions. Refine your prompts for smarter, more reliable AI. 08. Generic Resumes In The Bin! Forget sending generic resumes into the void. There are three distinct approaches: just a resume, adding a portfolio and cover letter, or the ultimate "Value Add" where you solve a company's problem before applying. #ai #aiproducts #aiprompt #aipm #productmanagement #productmanager 🧠 About Product Growth: After 16 years in PM, rising to VP of product, Aakash is going deep with the world's best experts to teach you product, growth, and AI. The world's largest podcast focused solely on product + growth, with over 177K listeners. 🔔 Subscribe and like the video to support our content! And turn on the bell for notifications.

Aakash GuptahostAnkit Shuklaguest

Jul 27, 20251h 20mWatch on YouTube ↗

WHAT IT’S REALLY ABOUT

Roadmap to become an AI product manager in 2025 fast

AI PM roles often aren’t labeled “AI PM,” but AI responsibilities (LLMs, RAG, evals, AI tooling) are increasingly embedded in standard PM job descriptions and pay meaningfully more.
They distinguish AI-enabled PMs (using AI tools for productivity) from applied/core AI PMs, arguing most opportunities and value creation are in applied AI products built atop existing infra/models.
The AI Product Development Lifecycle mirrors traditional PM work (problem discovery → validation → prioritization → roadmap → PRD → delivery → GTM → feedback), but AI compresses cycle time via rapid prototyping and automation tools.
Successful AI PMs connect problem space to solution space by selecting the right AI approach (predictive vs generative), contextualization method (prompting vs RAG vs fine-tuning), and designing robust evaluation/iteration loops.
The most actionable path into AI PM is proof-of-work: analyze 20+ relevant job descriptions, reverse-engineer leading AI products, publish learnings, build small user-driven side projects/agents, and target smaller funded companies with tailored proposals.

IDEAS WORTH REMEMBERING

5 ideas

Most “AI PM” jobs are hidden inside regular PM postings.

They claim searching for the title alone undercounts opportunities; instead, scan responsibilities for LLM/RAG/evals/tooling language and treat “AI PM” as a capability set applied to many PM roles.

Applied AI PM is the biggest career surface area, not core model/infra PM.

Core AI PM (models/infra) often requires ML/DS depth, but most business value accrues in applications that contextualize foundation models (e.g., Notion AI, Stripe docs assistant, Atlassian Intelligence).

AI doesn’t replace PM fundamentals; it raises the bar on craftsmanship.

They emphasize user empathy, problem-solving, and stakeholder management as durable moats; using AI to auto-generate artifacts (like PRDs) without adding judgment/context can erode critical thinking and perceived value.

Don’t force generative AI; predictive AI still solves many high-ROI problems.

Ranking, recommendations, categorization, and anomaly detection remain powerful and often cheaper/more reliable than GenAI; good AI PMs choose the simplest effective technique rather than defaulting to LLMs.

Contextualization is the key design lever for useful GenAI products.

They outline a progression: prompt engineering for contained context, RAG for large/fast-changing knowledge bases, and fine-tuning for specialized behavior when you have enough examples and can afford retraining costs.

WORDS WORTH SAVING

5 quotes

There are two types of PMs in the world right now, one who is using AI to get better bonuses and hike their salaries, and the other who is stuck in the old way of doing things.

— Aakash Gupta

I think every PM job is an AI PM job because even if you are not developing AI product on your own, still you have to use a lot of AI tools in order to make yourself more productive.

— Ankit Shukla

Unless you are working as a product owner or a program manager or a project manager, if you are working in those role, that's okay. Otherwise, every PM is going to either become an AI PM or you are going to get obsolete.

— Ankit Shukla

My mental model is that before you ask what is going to change, you should ask what is not going to change, and can I make it my strength?

— Ankit Shukla

Understand that motivation is perishable. Your motivation, your inspiration is perishable.

— Ankit Shukla

AI PM compensation (US and India)AI-enabled vs applied vs core AI PM rolesAI-powered product development lifecycle (AI PDLC)Problem space vs solution space mappingPredictive AI use cases (ranking, recommendations, anomaly detection, categorization)Generative AI, contextualization (prompting, RAG, fine-tuning)LLM evaluation loops, AI agents, and MCP integrations

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