Engineering leaders modernizing operational platforms are often presented with a false binary: choose the control and reliability of established enterprise platforms or embrace AI-native tools optimized for speed, automation, and intelligent experiences.

The more important architectural question is how to combine the strengths of both.

In this session, we’ll examine real-world evaluation frameworks used by enterprise teams modernizing legacy environments. Through practical examples and technical demonstrations, we’ll explore where deterministic execution should remain the foundation, where probabilistic AI and autonomous agents create meaningful value, and the tradeoffs that determine whether a platform remains adaptable or becomes the next generation of technical debt.

Key takeaways:
      Deterministic + Probabilistic Architecture: Where traditional business logic should remain in control and where AI-driven reasoning creates value.

     The Right Level of Autonomy: How to choose between deterministic workflows, AI-assisted automation, and autonomous agents.

     The Cost of Extensibility: How to evaluate low-code, APIs, custom development, and AI-assisted developer tools as requirements evolve.