What if the “mall” of the future is an answer engine? We sit down with Bryan House, CEO of Elastic Path, to unpack a bold reinvention: turning a 25-year-old commerce platform into an AI-first engine built for complex B2B and highly configurable experiences. From T-Mobile-grade reliability during iPhone launches to Serena & Lily’s 1,500-option couches, Bryan explains why the hardest problems in commerce aren’t about pretty storefronts—they’re about data, orchestration, and performance under pressure.
The centerpiece is a daring BHAG: bring replatforming down from six to twelve months and millions of dollars to six weeks under $100k. Bryan shares how a single, measurable goal aligns product, engineering, and go-to-market teams around the bottlenecks that matter—data migration, integrations, and storefront acceleration—and how internal AI adoption (showcases, shared wins, and performance metrics) builds real muscle, not just hype. We dig into the leadership moves behind the shift: promoting operators with “hustle DNA,” prioritizing experimentation over pedigree, and running lean without sacrificing ambition or profitability.
Looking ahead, Bryan makes the case that LLMs and answer engines will reshape product discovery—and that the winners will be brands with deep, structured catalogs ready to feed models precise, contextual product data. Elastic Path’s strategy: become the best product repository for AI while doubling down on the post-sale core—orders, fulfillment, returns, and customer care—where durable advantages live. If LLMs recommend, commerce platforms must deliver. Join us to explore intelligent commerce, the future of replatforming, and how to build teams that can move fast without breaking the business.
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