Sign In
Register

Request to partner

Register now

Call to action
Your text goes here. Insert your content, thoughts, or information in this space.
Button

Back to speakers

Subir
Paul
Group Product Manager
Zalando
Subir Paul is a Group Product Manager at Zalando, where he leads consumer experiences and experimentation. With over a decade of experience across Zalando, AB InBev, and Flipkart, he specialises in product strategy, commercial growth, and building products at the intersection of AI and business impact. A regular contributor to the product community through courses and writing, Subir is passionate about helping product managers thrive in an AI-native world by focusing on user insight and commercial judgment.
Button
21 October 2026 13:40 - 14:10
Fireside chat | If AI removes the busywork, what is product management really for?
If AI removes the busywork, what is product management really for? As AI takes over more of the day-to-day work of product management, the role of the product manager is being redefined. The biggest challenge is no longer getting things done—it's knowing what to build, why it matters, and how to create business value. In this fireside chat, explore how the role is shifting from execution to judgment, influence and strategy, and discover the skills product leaders need to thrive in an AI-first world. You'll learn how to: - Focus your time where human judgment creates the most value. - Develop the commercial and strategic skills AI can't replace. - Redefine the role of product management for the next generation.
21 October 2026 09:10 - 09:40
Fireside chat | How AI is transforming product discovery at scale
AI changes the economics of product discovery by reducing the cost of exploring questions, analysing evidence, and testing ideas. This empowers product teams to investigate more possibilities before committing to solutions, leading to better-informed decisions while still requiring human judgment and critical thinking. Key takeaways include: - Explore more before committing by making expensive discovery work accessible to challenge assumptions early. - Accelerate learning rather than delivery by using rapid prototyping to identify ideas worth investing in. - Understand where AI helps since analysis accelerates, but validation remains essential because plausible outputs are not always trustworthy evidence. - Keep discovery a human and collective discipline where customer contact and critical debate turn information into insight.