AI Agents
Designing a Useful Copilot Studio Agent
Why the strongest agent projects begin with a narrow job, approved knowledge, clear actions and rigorous evaluation.
Why this matters
Technology projects create value when they are tied to a clear user need, reliable information, appropriate controls and an operating model that continues after launch. This guide is written as a practical starting point for a discovery conversation.
Use the questions below to expose assumptions early and to decide whether the opportunity is ready for a prototype, needs foundational work, or should be deprioritised.
Practical checklist
- Define one user and one job to be done
- Ground the agent in approved information
- Limit actions and make confirmation explicit
- Create realistic evaluation questions
- Use analytics to improve content and journeys
Keep the first release narrow enough to evaluate with real users, but complete enough to test the end-to-end workflow.
What to do next
Document the current process, name the owner, define the desired outcome and gather representative examples. That evidence gives business and technical teams a much better starting point than a product demonstration alone.
Discuss your use case