AI and Copilot
Information architecture is the work that decides whether Copilot succeeds
Generative AI answers are only as good as the content behind them. The preparation that determines quality happens before any licence is assigned.
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Article ยท AI and Copilot
The most important design decision in an AI agent is the boundary: what it must not attempt, and what happens when it reaches the edge.
Agent design attracts attention to what the agent can do. The decisions that determine whether it is safe to deploy are about what it must not do, and what it does when it does not know.
An agent that says it does not have information about that, and here is who does, is more useful than one that produces a plausible answer from adjacent content. Designing good refusals, specific and with an onward route, is worth as much design attention as designing good answers.
Tell people what the agent covers before they ask. A short scope statement at the start of the conversation prevents the most common disappointment, which is asking something entirely outside the design and concluding the technology does not work.
Every refusal, escalation and low-confidence answer is information about where the design or the content falls short. Reviewing that log weekly is the single most effective way to improve an agent after launch, considerably more effective than adjusting prompts on instinct.
Written by
Nadia leads Avanteria work on Copilot, agents and retrieval. She spends most of her time on the part of generative AI that decides whether it succeeds: the content it is grounded on, the permissions it inherits, the review points around it, and whether people still use it three months after launch.
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