The market is flooded with high-level visions of autonomous AI agents taking over enterprise workflows. However, the reality of running agentic systems in production is a complex engineering challenge. 

 

Success does not depend on the underlying model’s theoretical reasoning capabilities. It depends on the operational infrastructure supporting it.

 

How do you move past the agent hype to examine the practical mechanics of agentic performance, security, and economics?

 

Join our next episode of AI Talk with Martin Miller, who hosts a panel discussion where we’ll explore:

• Overcoming the real-time data gap that causes agentic workflows to fail
• Effective governance of autonomous workflows across enterprise systems
• Quantifying the long-term operational and engineering costs of scaling home-grown agentic frameworks

Join us as we analyse the structural requirements for building accurate, reliable agents and evaluate the hidden total cost of ownership behind self-built enterprise AI platform