Every engineering leader putting AI into production is making a set of decisions that will outlast any single model release. How much to build internally vs. buy, how much control to trade for convenience, who owns the model, the data or the token cost curve as the AI market shifts. Each of these decisions shapes team structure, vendor dependencies, and how quickly an organization can adapt.
Drawing on his work helping teams at companies like Uber and Shopify deploy AI at scale, Benny will walk through the tradeoffs behind these calls, including where a general-purpose model makes sense vs. when customizing open models wins, and how to build an architecture and a team that keeps evolving instead of locking into one choice. Attendees will leave with a framework to reason through these decisions for their own organization, weighing flexibility against operational load and how to lead a team through the daily decision-making of AI.
