Separate reusable support instructions from MCP-style capabilities, add deterministic routing and permission gates, and test the resulting copilot against failures a polished demo usually hides.
A support copilot separates runbooks from tools by loading procedures selectively and validating requests in code, not prompts. This prevents prompt injection and escalation: AI proposes, code authorizes, keeping operational control explicit and auditable in production.
An AI support demo can look finished after it answers one question and calls one API.
The production tension appears later: the model has instructions, tools, customer messages, and credentials in the same context—but nobody can clearly say which part authorizes what.
That is not just an AI problem. It is a systems-design problem hiding behind natural language.
A reliable support copilot needs at least two separate layers:
Runbooks explain how to investigate a particular class of problem.
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