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Jordan
Nolff
VP, Growth & Product
Productboard
Jordan Nolff is VP, Growth & Product at Productboard, where he leads Growth, AI product, product marketing, and analytics. His mandate is to make it exceptionally easy for teams worldwide to discover, trial, buy, and succeed with Productboard—while transforming the company into an AI-first platform for product managers. He is the driving force behind Spark, Productboard’s AI for PMs—designed to generate briefs in seconds, surface insights across customer feedback, and accelerate initiative planning. Under Jordan’s leadership, Spark evolved from concept to public beta through a deliberate AI-first rebuild of core workflows, focusing on evaluation rigor, product quality, and scalable team structures to support expanding AI surface area. Before stepping into his current role, Jordan served as GM, Head of Growth at Productboard, where he rebuilt the Growth function and aligned acquisition, activation, monetization, and analytics around a cohesive operating model.
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15 April 2026 11:00 - 11:30
The spec is dead: Long live the spec
You've seen the social media headlines and thought: is product management dead? Engineers are shipping faster than ever. Coding agents are turning requirements into pull requests overnight. If you can build anything instantly, do you need a PM? The answer is yes, but the job looks different now. The scarcest resource in an AI-driven engineering org isn't execution speed. It's judgment: knowing what to build, what to cut, and what "right" actually looks like for your customer. That judgment has always lived in the spec. And in a world where coding agents build exactly what they're given, the spec has never mattered more. In this session, Jordan Nolff, VP of Growth & Product at Productboard, will make the case that AI agents don't make the spec obsolete. They finally give PMs the synthesis engine to write specs that were never possible before. Key takeaways: - How top PMs are using agents to eliminate the "context tax" (i.e., the hours spent gathering information before making a single decision) - Why the quality of your context layer determines whether AI gives you speed or just faster mistakes - Concrete steps you can take to start building a context layer that makes your specs - and your agents - dramatically more effective