How do you scope and run a successful AI proof-of-concept or pilot with a customer?
Most AI pilots fail on scoping rather than the model: fuzzy success criteria, the wrong use case, or data that was never ready. For customer-facing and applied AI roles, running a pilot well is the job itself. Here is the playbook.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Most AI pilots fail on scoping rather than the model: fuzzy success criteria, the wrong use case, or data that was never ready. For customer-facing and applied AI roles, running a pilot well is the job itself. Here is the playbook.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
