Python or Lovable? The Role of Modern AI Tooling in Product Management

I was recently talking product management with my son, Marcelo.

He is what I would call a classically trained technical Product Manager in the making. He is pursuing a BS in Computer Science and Information Science, with coursework in Human-Computer Interaction, foundations in C, C++, Java, JavaScript, HTML, and CSS, strong data visualization skills, and hands-on experience with modern LLM platforms like ChatGPT, Gemini, and Claude. He has also completed certifications in prompt engineering and AI product management.

One gap in his formal CS background is Python.

As we talked through his summer learning plans, a question came up:

Should he invest time in learning Python, or should he double down on modern low-code and no-code tools like Lovable, v0, and Replit, and go deeper into applying the latest advances in AI?

We landed on this: for an aspiring Product Manager in AI-driven products, leverage today comes less from writing code and more from understanding what is possible, how systems fit together, and how to prototype quickly, alongside strong customer advocacy, sound judgment, and clarity, quality, and taste in requirements.

Great product managers bring this together through deep user empathy, strong prioritization, and the ability to clearly communicate and influence cross-functional teams.

That means deepening AI product thinking, staying fluent in modern tooling, and learning how to work with engineers rather than trying to out-engineer them.

Demis Hassabis said recently:

"If I was to talk to a class of undergrads right now, I would be telling them to get really, unbelievably proficient with these tools. I think that can be better than a traditional internship would have been, in the sense that you are leapfrogging yourself to be useful in a profession."

I know Marcelo is committed to doing both: excelling at a summer internship while continually developing his skills with the latest generation of AI tools.

So I am curious.

If you were advising a current undergraduate with a passion for Product Management, how would you prioritize learning today?

This article reflects my personal perspectives on product management and AI. It does not represent the official position of my employer or any affiliated organization.