Why I’m Building a Course on AI Strategy for Product Leaders
A few months ago, Gagan Biyani (co-founder of Maven) reached out and nudged me to consider creating a course. I wasn’t looking to launch anything at the time, but the idea lingered. It kept resurfacing in conversations with other product leaders, in my mentoring sessions, and during internal strategy reviews.
And here’s what I’ve come to realize:
Most product leaders today are flying blind when it comes to AI.
Not because they lack intelligence or initiative. But because the AI landscape, especially with ML and GenAI, is moving too fast, and product orgs haven’t caught up. There’s a growing gap between what teams could do with AI, and what they are doing.
The Problem: We’re Drowning in AI Hype, But Starving for Strategy
Over the past year, I’ve worked with ML teams and execs across Meta, Booking.com, Flipkart, Goldman Sachs, and several startups. Some consistent themes keep emerging:
ML products often feel fragmented.
GenAI experiments get spun up without real alignment to user problems.
Tech debt builds fast. Strategy… not so much.
In short, product leaders are overwhelmed, under-supported, and missing the strategic frameworks needed to build AI products that actually move the needle.
And I get it. I’ve been there.
At Flipkart, I was one of very few ML PMs in the company, building during crunch-time. At Booking.com, I’ve helped lead one of the most scaled AI transformations in travel tech, spanning classical ML, ranking systems, and GenAI platforms. At Meta, I’ve built ML products at a scale so vast that the resources at my disposal seemed infinite. I’ve seen what works, and what falls apart.
The Vision: A Course for Impact-Driven Product Leadership in AI
So here’s what I’m building:
A high-intensity course for product leaders who want to go beyond the buzzwords and actually drive business impact with AI.
We’ll cover things like:
Identifying high-leverage ML/GenAI opportunities in your org
Designing product strategy for intelligent systems, not just interfaces
Structuring AI bets across Horizon 1, 2, and 3
Balancing GenAI and classical ML for practical business value
And yes, the hard stuff too: fallback design, ML evaluation, experimentation, and compliance
It’s built for people leading product at startups, scale-ups, and large tech companies, who want to push their thinking forward and build with confidence.
Help Me Shape It
I’m still refining the curriculum, and I’d love your input.
If you're a PM, product lead, or product-minded founder working on AI, take 2 minutes to share your thoughts in this short survey:
👉 https://maven.com/forms/341112
If you leave your email, I’ll also send early access invites + priority seats before we open public enrollment.
Let’s build the next generation of AI-native product leaders together.
– Pranav