Author of Escaping the Build Trap, founder of Produx Labs and Product Institute.
This is what separates teams that accelerate with AI from those that get stuck. You don't find perfect data lying around. You create it using the deep product intuition you already have. /end Check out the whole episode with @vlaurenlee here:
They're taking everything they know about commerce, customer behavior, and product strategy, and using that knowledge to systematically generate the training data they need. It transforms the data bottleneck from a passive waiting game into an active engineering challenge. /3
This week on the podcast, @vlaurenlee from @Shopify shared how her team is using AI to solve AI problems, instead of waiting years for interaction data. "You're basically imparting all of your product intuition into an LLM to then shape yet another LLM." /2
Most teams make the mistake of waiting for data to magically appear before building their AI product. They get stuck in the classic chicken-and-egg problem: you need data to build good AI, but you need users to generate that data. So they wait. And wait. And wait some more. /1
Product teams need to think like investors—understand the real cost, focus on ROI, and balance risk to drive outcomes. Fabrice des Mazery, former CPO at TheFork, shares how shifting to an investment mindset leads to smarter decisions and impact. Listen:
Scaling product teams is hard. Delivering consistent outcomes while keeping things simple is even harder. Mark Rosenberg, VP of Product at @Workday shares how revamping ProdOps reduced complexity, aligned teams, and delivered better outcomes at scale. 🎧
Compliance can become an opportunity for innovation. This week on Product Thinking, @tomerlondon, CPO at @GustoHQ, shares how embedding lawyers in product teams ensures compliance is part of the process. 🎙️Listen now: