Most organizations experimenting with agentic AI aren’t blocked by models, frameworks, or orchestration. They’re blocked by something far more basic: the everyday realities of how enterprises actually work.
Agents look brilliant in controlled demos, but the moment you try to plug them into real systems (legacy data, governance, identity, compliance, and unclear ownership) they collapse into the same pile of abandoned POCs as everything else.

My talk cuts through the hype and gets straight to the uncomfortable truth:

- why agentic systems end up as flashy prototypes instead of production tools,
- how Excel-based “data estates” quietly choke autonomy before it even starts,
- why most so-called “AI use cases” are still rule-based automation wearing an AI sticker, and
- how to build the minimal delivery backbone needed for any intelligent agent to run safely in a real enterprise.

This isn’t yet another vision talk, but the reality check most teams never get: the engineering and organizational work required to move agents from the lab into the world where the constraints are real and the stakes are even higher.

Care about getting agentic systems running rather than demoing? This session gives you the hard truths and the practical steps to finally make that possible.