Synthesizing Contextual Agentic Assistants

In this demo, I will be showing an implementation for just-in-time assembly of agentic assistants that is designed for dynamic real-world situations and IoT. The goal is to get contextual agreement by default between the agentic assistant and the user relative to the physical environment (manufacturing station, healthcare clinic room, home office, hotel room, etc.). These environments are dynamic, fragmented, and data/controls for a single physical object tend to exist across multiple systems, so I end up modeling each object then assembling the right agent from these individual object maps and the overall relationships between objects in the physical environment.

The focus will be on the resulting assembly manifests that can be executed using any agentic framework with many different orchestration architectures, the condensed physical-digital graph, and the other elements that is passed in through the system prompt to create the contextual agreement by default. Generating the manifest is a longer talk, so the core of what will be shown is the visualizer to make it understandable and the visualizer code for how the system prompt is constructed (surprisingly simple).