Observability closes the feedback loop — but it is often introduced only after something has already broken in production. It can shine in that situation, but what if the same telemetry could also help us build better software before it is released? And what if it could give an AI coding agent enough context to test, diagnose and improve its own work?

In this live-demo session, we will give developers and AI agents X-ray vision into a running website built on the popular Umbraco CMS and .NET Aspire with OpenTelemetry to bring logs, distributed traces and metrics together in one local observability environment. There we will build new features, diagnose real problems and verify that our fixes actually work.

We will also explore how coding agents can use observability data through Model Context Protocol to move beyond simply generating code. By inspecting the behaviour of the running application, an agent can help identify failures, suggest changes and validate the result.

Along the way, we will consider what telemetry is genuinely useful, how to avoid collecting personal form data, and how to give AI tools controlled, read-only access to production systems. These practical examples will give you a concrete approach for making observability part of the development process—not merely something you add after deployment.