Write a JSON parser from scratch. Now make it handle the partial JSON an LLM streams mid-generation.
The classic recursive-descent exercise with an applied-AI twist: the JSON your model streams stays truncated mid-token for the whole generation. What matters is a clean strict parser plus a small repair layer, not a second parser. The code follows.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
The classic recursive-descent exercise with an applied-AI twist: the JSON your model streams stays truncated mid-token for the whole generation. What matters is a clean strict parser plus a small repair layer, not a second parser. The code follows.
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.
