Custom AI agent development: scope a pilot that answers a real question

Describe the work before choosing the architecture

Write down what triggers the task, which information it uses and what a finished result looks like. Include the person who currently performs the work. Their judgment helps reveal exceptions that a high-level process diagram can miss.

An illustrative pilot might prepare a support response from approved documentation and route an unresolved question to a person. Another might gather account context and draft a next step. Both could use an AI agent, but they need different data, permissions and evaluation criteria.

Choose a useful boundary

Limit the first release by workflow, audience or knowledge scope. A bounded pilot can still include hard cases; the boundary should make the result interpretable rather than artificially easy. Specify which requests should be completed and which should be declined or handed off.

Decide what the pilot will not establish. A working demonstration on prepared examples does not prove that the system can support every user or integrate with every production system. Document those limits so the expansion decision is based on evidence.

Create the evaluation set early

Collect representative tasks before tuning the assistant around them. Include straightforward requests, missing information, corrections and ambiguous instructions. Keep some cases aside to check whether an improvement works beyond the examples used during development.

Microsoft’s agent evaluation checklist recommends testing functional behavior and assessing responses against acceptance criteria. For a business pilot, define those criteria in terms the workflow owner can review, including when asking a clarifying question is the correct result.

Reference: Microsoft: Agent evaluation checklist

Include the real integration constraints

List required data sources, permissions and dependencies. Identify whether the pilot uses a test environment or production access, and what must change before launch. A shortcut can be reasonable during exploration if it is recorded and not mistaken for completed production work.

Consider how failures appear to the user. If a tool is unavailable, can the task be paused, safely retried or handed off? Recovery behavior is part of a useful pilot, because it tells the business how much operational support the system needs.

• Name the owner of each data source.
• Define the actions the agent may perform.
• Decide how outputs and actions will be checked.
• Record what changes are required before production use.

Review quality, time and operating effort together

A pilot can produce accurate answers while requiring too much staff correction or taking too long for the intended workflow. Measure the full task, including review and recovery. Keep response quality, latency and operating effort separate so the tradeoffs remain visible.

Avoid declaring success from interaction counts alone. Ask whether the system completed the intended task, whether the owner accepted the result and how often a person needed to intervene. Compare against the current process using equivalent work where possible.

End with an explicit next decision

The pilot review should support a choice: expand the scope, improve a specific weakness, change the approach or stop. Document the evidence and the unresolved issues. A smaller validated use case is a better foundation for planning than a broad demo whose reliability is unknown.

XT SCALE builds custom AI systems around business workflows, knowledge and integrations. A useful starting brief includes the task, representative examples, the systems involved and the person who can judge the outcome. That is enough to begin a concrete technical discussion.

Common questions

Does a pilot need every production integration?

Not necessarily. It does need a clear record of which connections are real, which are limited and what remains before production use.

How should we choose the first workflow?

Prefer a recurring task with accessible source information, a clear owner and an outcome that can be reviewed. Avoid choosing solely because a demonstration looks impressive.