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How leaders are rebuilding data, pipelines, & architecture around LLMs.
Enterprise AI in 2026 has a production problem. The agentic systems that impressed in pilots are failing in the field - not because the models aren't capable, but because the infrastructure running them wasn't built for the complexity of real-world workflows. Multi-step tasks stall. State disappears mid-execution. A single API failure takes down an entire pipeline.
But engineering teams are finding their way through. A new class of infrastructure patterns is emerging-built around automatic failure recovery, persistent workflow state, & guardrails that keep agents on track when external systems behave unpredictably.
At this event, we're bringing together the practitioners who have crossed that threshold to share what the playbook actually looks like: how they structured their agent workflows, where they drew the architectural lines, & what it took to go from a fragile pilot to a system their business depends on.
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