Token optimization got you here. It won't get you to what's next. AI is a load-bearing infrastructure and the teams pulling ahead aren't the ones squeezing costs, they're the ones redefining what value looks like. Walk through the shift from token-level thinking to outcome-driven AI investment: how to measure it, operationalize it, and make the case internally.

Security practices have evolved to match the pace of AI-assisted development and automated deployments. Learn about real-time threat detection, automated security testing that keeps up with rapid release cycles, and how enterprise security teams are leveraging AI to identify vulnerabilities faster than developers can introduce them.

AI is becoming the primary author of code — and that changes everything downstream. This session explores what DevSecOps looks like when your developers are orchestrating agents instead of writing every line themselves: new quality gates, new security considerations, new questions about ownership and accountability, and what it means to ship with confidence when the code came from a model.

Any enterprise with enough history has the same problem: teams picked their own tools for years, and no one reconciled them. This session tackles that mess, aligning independent business units on shared standards, and getting past the inevitable "that's how we've always done it."

AI has shifted where teams spend their time — but it hasn't eliminated friction, it's moved it. This session explores the new bottlenecks in AI-augmented workflows: where productivity gains stall, how organizations measure developer experience beyond velocity, and what platform engineering looks like when AI is doing more of the work.