Pick one decision boundary
“Operate the company” is too broad for a first environment. “Resolve a shortage before a promised delivery date, within substitution policy” gives us a concrete scope.
Use fictional records for the initial design. A source-backed version needs an approved dataset, operational expertise and the permissions required for its intended use.
Specify the starting state
The environment needs orders, stock, product compatibility, supplier commitments and policies. Capture what is known when the episode starts, excluding information that only becomes available after the historical resolution.
A small state model can be more useful than a detailed interface if it accurately represents the decision under test.
Give actions explicit consequences
A stock lookup returns availability. An approval request changes authorization state. An allocation reserves inventory if the requested quantities and permissions are valid.
Define how invalid actions fail. The environment should not silently accept an impossible allocation just because the agent wrote persuasive text.
Verify outcomes and alternatives
Check the accepted plan, the reservation and the relevant policy constraints. Ensure the grader accepts alternative valid solutions, including an appropriate escalation when the task cannot be completed with current permissions.
Include negative cases: insufficient inventory, missing approval, unsupported delivery dates and unrelated record edits. Keep the grader outside the agent’s writable surface.
Document what the demonstration proves
A deterministic demonstration explains the workflow. It does not establish coverage of a whole industry, accurate stochastic dynamics or production performance. Those require additional evidence and validation.