Our Core Processes are documented for human employees and rely heavily on common sense and judgment calls. How do we translate these human-centric SOPs into structured instructions an AI agent can execute reliably?

Question

Tyler Smith · Accepted Answer

Human standard operating procedures are loaded with implicit assumptions. Phrases like review the invoice for accuracy or notify the account manager if something looks off work fine for experienced employees, but an AI agent will stall or make wild assumptions when handed ambiguous guidance.

To convert human SOPs into system-dependent machine instructions, rewrite the process using strict conditional logic:

- Define absolute boundaries: Instead of telling the system to check for discrepancies, specify the exact mathematical threshold. Instruct the model that if an incoming invoice exceeds the purchase order by more than five percent or one hundred dollars, route the file immediately to the accounts payable manager with the specific delta highlighted.
- Establish deterministic input formats: An AI agent requires defined source documents. Specify the exact fields it must locate, such as vendor name, line item description, unit count, and net total. If any required field is missing or illegible, instruct the agent to stop and trigger a human review exception.
- Provide two-shot examples: In your prompt documentation, include one perfect example of an acceptable output and one clear example of an unacceptable output that triggered an escalation. Models operate significantly better with concrete target references than with abstract descriptions.

Once you translate tribal judgment into structured logic, your documented Core Processes become durable operational assets. This not only allows AI agents to run tasks without human handholding, it also makes your company far more valuable to a future buyer looking for turnkey systems.