From Concept to Copilot: Defining the Right Intake Criteria

AI copilots are reshaping how we interact with digital systems, but their success is not accidental—it starts with well-defined intake criteria. Without a structured approach to defining the agent’s functional and technical scope, we risk building copilots that lack usability, accuracy, or security.

At the heart of a copilot’s effectiveness are its functional requirements—what should it do, and how should it handle various user interactions? A clear purpose statement ensures that every decision made in development aligns with a tangible user need. Take customer service AI as an example: defining a “happy flow” where a user asks a question and receives a relevant, concise response minimizes frustration and increases adoption.

However, not all user journeys are predictable. An AI agent must also handle “error flows”, guiding users to solutions when unexpected inputs arise. In financial services, for instance, a copilot assisting with tax queries should gracefully handle edge cases like ambiguous VAT rules, offering clarifications or escalating complex cases to human experts.

Beyond interaction design, data quality and security determine a copilot’s reliability. A well-trained model needs structured, compliant knowledge sources—be it internal databases or external references. Imagine deploying a legal research assistant that references outdated or conflicting case laws; trust in the system would erode instantly.

Finally, testing and iteration refine the copilot before deployment. In AI-driven automation, test scenarios should reflect real production data, ensuring the system performs under realistic conditions. A rule of thumb? A development dataset should be at least 20% of the projected production volume, ensuring robustness before full-scale rollout.

A copilot agent is only as good as its foundations. Defining clear intake criteria, understanding real-world application needs, and ensuring technical and security readiness—these are the pillars of a successful AI assistant.

Here you can find a checklist with my most important intake criteria. Checklist-Intake criteria for a Copilot Agent

My focus is on structuring, automating and managing business processes using Agile and DevOps best practices. This creates working environments where business continuity, transparency and human capital come first. Reach out to me on LinkedIn or check out my github or blog for more tips and tricks.

The ideas and underlying essence are original and generated by a human author. The organization, grammar, and presentation may have been enhanced by the use of AI.