Your tokenizer shreds domain terms into meaningless subwords. How do you fix it?
When a drug name or a Hindi word splits into nine subword tokens, you pay in cost, context, and accuracy. Adding tokens is easy and adding them well is not. Here is the tradeoff.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
When a drug name or a Hindi word splits into nine subword tokens, you pay in cost, context, and accuracy. Adding tokens is easy and adding them well is not. Here is the tradeoff.
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.
