Question

An AI coding assistant generates a Python function that uses Netmiko's send_config_set() to add a set of ACL entries to an IOS XE device. Before merging the code into your automation library, your team lead asks you to evaluate whether the AI's recommendation is safe to run repeatedly as part of a scheduled remediation job. The AI claims the function is 'fully idempotent.' Which validation approach BEST verifies this specific claim before production use?

Accepted Answer

Run the function twice in a CML sandbox against a device with a partial pre-existing ACL, then diff the running-config after each run to confirm the second execution produces no additional changes

Answer

Review the function's docstring and variable naming to confirm it matches your team's style guide, since consistent naming implies idempotent behavior

Answer

Ask the same LLM to rate its own confidence in the generated code on a scale of 1 to 10 and accept it if the score exceeds 8

Answer

Execute the function once against production during a maintenance window and confirm no syslog errors are generated