We’ve all seen what happens when you give an LLM a single repo: it’s usually quite successful.
But what happens when you give it a distributed system with 200 microservices? It gets lost in the "muddy middle".
The bottleneck in AI-driven development isn't code generation; it’s architectural context.

This talk introduces the Application Architecture Hub - a living, AI-maintained knowledge base designed specifically for agent consumption.

We will explore how to move away from static, stale documentation and toward a system of automated "facets" (APIs, Domain Models, Events, and more) that allow AI agents to troubleshoot, design, and assess impact across your entire ecosystem.
We'll explore how this can benefit workflows beyond coding, across the organization.

Attendees will leave with a blueprint for building an ingestion pipeline that keeps their AI agents (and their humans) in sync with the "truth" of the codebase.

Should about 30min talk, can be more.
Assumes basic understanding of LLMs and coding agents, and development background.