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How I productionized my multi-agent AI support copilot in Teams and Azure

DEV Community: azure·Eelco Los·5 months ago
#XMYX2x78
#dev#teams#system#triage#azure
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TL;DR

Built a .NET A2A demo to validate the triage pattern before deploying the Python system. If the shape only works in one stack, it is not a portable pattern.

Teams is the ingest channel for this deployment, not a hard requirement. The bot posts to a channel-agnostic /ingress endpoint; any other ingest can do the same.

Teams timeout budgets forced a full async reply architecture.

Adaptive card size limits forced progressive disclosure: compact badge up front, everything else behind toggles.

RSC permissions only activate on manifest install, not Entra consent alone. Getting that order wrong costs you a 403 and a bug you cannot reproduce.

Containerization was table stakes. The real work was auth, telemetry, storage, and making every platform permission explicit.

Part 2 covered the runtime failures and the hardening work that followed. This post is about the next step: productionization.

Once the system was capable of producing credible triage results repeatedly, the question changed again.…

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