Diego Granados

I'm a Product Manager with experience working cross-functionally with business roles (e.g. Marketing, Finance, Sales), technical roles (e.g. Backend and front-end engineers, data scientists) as well as designers and UX researchers to bring products to life that make our users' problems and pain-points go away!

I have experience working with Web and Mobile products, AI and Machine Learning - There's something really fascinating about using data to try and predict the future. I'm a big believer that every model should be thoroughly thought from an AI Ethics point of view.

As a product manager I have to wear different hats every day and I excel at working cross-functionally. My experience and feedback has taught me that I bring value to the teams I work with because:

- I empathize with users and speak: geek, data whisperer, designer, marketer and salesperson. At some point I also tried to learn Shriiwook (I've always wanted to understand Chewbacca like Han did). Understanding means fewer mistakes, and mistakes can be very costly.

- I'm passionate about understanding customers, too many people use "customer obsession" as buzzwords in their resume.

- I leave the BIG ideas to the Elon Musks of the world. A good Strategy, Vision and Execution drives products forward - I do these three.

- I'm an engineer at heart and a musician at soul - I like to combine logic with creativity

- I'm the calm one. I'm the one that plans.

I'm passionate about helping others and I created a YouTube channel to help others learn about Product Management: https://www.youtube.com/c/PMDiegoGranados/

Don't hesitate to reach out if you want to talk about AI/ML, technology, business, consumer electronics/technology or need help on your journey to become a Product Manager!

Specialties: Product Management, Consumer electronics, Consumer Technology, Cross-functional work, Agile development, Product design, data driven decisions, AI, Machine Learning.

Product Manager AI&ML

One of the challenges that GenAI brought to Product Management was that it placed PMs (even experienced ones) into doing AI work without necessarily having the background or expertise in Machine Learning.

Do you need a degree in Data Science or Computer Science to be an AI PM? Absolutely not - However, I am convinced that learning the fundamentals of machine learning will help you be better prepared for the AI (or GenAI) world of Product Management. Things like...
- Learning how ML models (incl. GenAI) learn and predict
- How the data science lifecycle differs from deterministic software development
- How to convince an exec that sometimes predicting with 80% accuracy is fine, while in other cases a 93% can be catastrophic (even though it may sound better)
- How to help your users TRUST and UNDERSTAND the output of your AI models

Earlier this year, the amazing Marily Nika, Ph.D and I spent hundreds of hours collaborating (without ever actually meeting in person!) on our book "The AI Product Playbook".  What started as a simple exchange of ideas about content evolved into realizing that our experience as AI Product Managers at places like Meta and Google has been very different from traditional PM.

AI PM is probabilistic, centered on data, and ambiguous in ways that traditional PM skills and frameworks can't prepare you for. 

This project, "The AI Product Playbook", was born from the idea that we wanted to help others discover and understand the roles of different AI Product Managers in the industry. And to those just getting into AI, give them a compass on how to understand and navigate this world of data and statistics, without having to do an advanced degree in data science.

If you're a product manager, builder, or technologist trying to navigate the new world of AI-driven products, this book is for you.

In fact, all our students for our AI Product Management Evals course (new!) will get a free copy.

Here's a fun fact: I never expected that one day someone would ask me to sign a book we wrote 😋, so here's a photo of me nervously signing our book. Thank you, Jack Xuan for inviting me to chat about our book at Amazon HQ!

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💎 I have a few AI Product Management freebies and more details about our book and Evals course for you - check my comment below!

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Talks about #networking, #interviewtips, #productmanager, and #productmanagement

Product Manager AI&ML @ Google | 🚀 Interested in AI Product Management? Check my profile!

In 2025, Product Managers went from “can GenAI do that?” to “… but is it ready to be shipped?” - knowing how to do AI Evals is one of the core skills of AI PMs 👇


One of the biggest challenges of GrnAI features is to know whether you’ve thoroughly tested your feature - if users can break it, they will….

For example, Taco Bell implemented an AI chatbot to take orders in their drive through. A user wanted to bypass the AI and talk with a real person, so he ordered 18,000 cups of water (true story). People in the store immediately disconnected the AI Chatbot to prevent the order from happening.

Another, perhaps more critical disaster, was when an AI coding assistant from tech firm Replit went rogue and wiped out the production database of startup SaaStr.

Even MIT is urging Product teams to do more evals: “The GenAI App Step You’re Skimping On: Evaluations

If your organization’s generative AI app didn’t pan out, maybe it’s because your team lacked a strong evaluation process.“

If users can break your product, they will. Having strong evals may not prevent every single corner case, but will likely save your feature from appearing in the headlines of “when AI Fails”

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AI Product Managers MUST learn how to do great evals - so I partnered with Marily Nika, Ph.D , George Zoto  and Mark Cramer  to create an amazing live course that centers on GenAI Evals for Product Managers!

We start December 4th, check my comment below for all the details you need! (And a discount, too!)

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