Question: A team is building an email spam filter. They want inference latency to stay under 50 milliseconds, and among all models that satisfy that limit, they want the highest possible precision. Explain why precision is the optimizing metric and latency is the satisficing metric.

Sample answer: Latency is a satisficing metric because the model only needs to stay within an acceptable limit; once it is under 50 milliseconds, the requirement is met. Precision is the optimizing metric because there is no fixed cutoff that merely counts as acceptable. Instead, the team wants to improve precision as much as possible while still meeting the latency constraint. That makes precision the quantity being optimized and latency the constraint being satisfied.

Key points:

• Latency has a pass/fail threshold
• Precision is improved continuously rather than checked against a minimum cutoff
• The goal is to maximize precision while keeping latency under the limit
• This makes precision the optimizing metric and latency the satisficing metric

Rubric: Full credit requires explaining that latency must only meet the time limit, precision is the quantity to maximize, and the optimization is done subject to the latency constraint. Partial credit for identifying the roles without clearly describing the threshold-versus-maximization difference.