Why do agents fail on long-horizon tasks, and how do you keep reliability up over many steps?
Per-step accuracy looks fine, yet a 50-step task fails. The signal is grasping compounding error and the techniques (decomposition, verification, checkpointing) that keep long-horizon agents from collapsing.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Per-step accuracy looks fine, yet a 50-step task fails. The signal is grasping compounding error and the techniques (decomposition, verification, checkpointing) that keep long-horizon agents from collapsing.
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.
