A prototype built with Claude Code still has to survive your ERP | Ryan Smith, Pivotree

Every AI conversation in distribution right now assumes the data underneath is ready to be acted on. Most of the time, it isn't. Matt Johnson hosts this one solo, with Floyd Blaikie out of the studio, joined by Ryan Smith, an account executive at Pivotree, fresh off the Applied AI for Distributors event in Chicago run by Distribution Strategy Group. ㅤ Ryan took the data side. Before you buy the next AI tool, you finish step zero and step one: knowing where you're actually headed, then cleaning and governing the data those tools depend on. He and Matt get into why last year's shiny purchases went sideways, why distributors keep walking up to the table saying they're behind, and what happens now that customers show up with prototypes they built themselves. It's a distribution and manufacturing conversation, but retail and B2B operators will recognize the pattern. ㅤ 👤 Guest Bio Ryan Smith is an account executive at Pivotree, where he works with distributors and manufacturers on their AI and data transformation. He joined the company recently and spends his time helping companies figure out where they actually stand before they buy the next tool. He took the data side of this episode, arguing the foundation has to come before the technology. ㅤ 📌 What We Cover • Why most of last year's AI tool buyers hit a wall, and how much of it traced back to data that was never cleaned or governed • Step zero, step one, step two: mapping where a distributor actually is before recommending anything • Distributors building their own tools in-house, with AI engineers vibe coding bespoke solutions • The security and governance risk when two departments build the same agent and spend the budget twice • Customers arriving with ready-made prototypes built in Claude Code, then handing off the integration • Why a working prototype is not a multi-tenant, secure, production-ready system • The generational shift from tribal knowledge walking out the door to buyers who expect the Amazon experience • AI fatigue, the 50/50 reliability problem, and why the human element still decides the outcome