A port is three coupled scheduling problems in a single prompt: where ships dock, which cranes work them, and where containers land in the yard. The strong answer decomposes them, names where they couple, and refuses to solve the whole thing as one giant optimizer.
Updated Aug 2026 · Grounded in real Forward Deployed Engineer interview loops and written to a senior-engineer editorial bar.
A port is three coupled scheduling problems in a single prompt: where ships dock, which cranes work them, and where containers land in the yard. The strong answer decomposes them, names where they couple, and refuses to solve the whole thing as one giant optimizer.
This is a Palantir-style decomposition probe: the interviewer wants to see you carve a gnarly physical-world operation into an ontology and a set of decisions, not draw boxes labeled microservices. The trap is reaching straight for a monolithic mixed-integer program over the whole terminal, which is intractable at the tick rate operations actually run and brittle when a ship arrives late. The discriminating move is to separate the three coupled decisions (berth allocation, quay-crane assignment, yard slotting), schedule on different horizons (berths days out, cranes per-ship, yard moves live), and name the coupling explicitly: yard placement now determines crane travel and truck congestion later. The strongest candidates also say the objective is contested (terminal throughput vs vessel turnaround vs yard density) and ask whose number wins. Saying 'I'd use a routing algorithm' without naming the entities and the re-plan trigger is shallow.
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