1
Start with one workflow whose inputs and expected outputs are measurable. Connect only the data sources and tools required for that process, then build the flow with explicit steps and permissions rather than giving an agent unrestricted access. Test with representative and adversarial inputs before publishing. Log tool calls and failures so the team can distinguish model errors from integration problems. Require human approval before irreversible actions such as sending external communications, changing financial records, deleting data, or making decisions that affect customers or employees.
2
For a first evaluation, keep the scope small enough that you can compare the AI-assisted result with a known baseline. Record the configuration, model or workflow choices that produced the result so successful tests can be reproduced. If the product connects to external systems or private data, grant the minimum permissions required and review the provider's current security and data-handling documentation before expanding access.