HardProduct

Logistics firm wants an AI agent for automated shipment rerouting

1Give yourself 5 minutes

2Answer out loud, not in your head

3Then compare with the answer below

Reference answer

Eval framework: (a) a held-out scenario set of historical disruption events (hurricane, port strike, fuel spike) with shipping-cost and SLA outcomes; (b) a synthetic scenario generator for long-tail events; (c) a daily regression suite against live traffic; (d) human spot-checks on the highest-stakes decisions. The eval must measure "would-have-rerouted-to" rather than just "did-route." Multi-objective tradeoff: cost vs. SLA — define a non-dominated frontier; flag any reroute that violates the 99% SLA regardless of cost savings. Iterate the eval alongside the agent monthly.

Then expect these follow-ups

"What if the cost savings cause SLA dips in 0.5% of cases that your eval missed?

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