Automation can handle a repeated step while leaving exceptional cases unresolved. If the process continues without acknowledging those cases, a small uncertainty can turn into a confident but unsuitable result.
Define the boundary alongside the ordinary path. Which inputs are understood, which outcomes can be checked, and when should the process pause? A handoff should include enough context for a person to decide what happens next.
Review the cases that required attention. They may suggest a clearer instruction or a narrower scope, rather than a need to automate everything. Useful progress includes knowing where the tool’s responsibility ends.
- Define the understood inputs.
- Make uncertainty a visible handoff.
- Review exceptions before expanding the scope.
An example to consider.
A document classifier could flag uncertain items for review. Naming that stopping point makes the automation’s responsibility easier to explain.
Put it in perspective.
Separate the possibility from the commitment. A small trial can answer a question while leaving room to change direction after you learn more.
Follow a related question
Record the purpose of an important dependency.
Dependencies with a reasonInspect the source and measurement method.
An outlier is a question firstKeep learning
Related background to continue exploring this subject.
Google: an introduction to language models NIST: AI risk management framework
