This two-day deep-dive workshop is for developers, architects, and technical leaders who want to understand how enterprise AI systems are actually designed, delivered, and scaled in production.

You’ll learn how real-world solutions emerge from the combination of data platforms, agents, integration layers and governance—and why most teams fail by treating AI as an isolated application instead of a connected system.

We’ll walk through the full lifecycle of enterprise AI delivery:

• selecting use cases that deliver real ROI (and avoiding “UAT purgatory”)
• designing architectures across data, agents, integration, and experience layers
• choosing between pro-code, low-code, and data-platform approaches
• applying retrieval, knowledge, and semantic patterns effectively
• embedding governance, evaluation, and safety from day one

Through architecture deep dives and live demos of emerging capabilities, you’ll gain a clear understanding of what to use, when, and why.

A key theme throughout the workshop is the shift in the developer role itself. Modern AI engineers are no longer just writing code—they are orchestrating intelligence across copilots, agents, data platforms, and enterprise systems.

By the end, you’ll leave with practical frameworks, architectures, and an opinionated view of how to build AI systems that are scalable, governed, and production-ready.