How do you keep secrets and credentials out of LLM prompts, logs, and training data?
LLM apps bleed secrets in three quiet places: the prompt, the logs, and the next training set. Each demands a different control. Here is how to close all three.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
LLM apps bleed secrets in three quiet places: the prompt, the logs, and the next training set. Each demands a different control. Here is how to close all three.
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.
