How do you do continued pretraining to adapt an LLM to a new domain without forgetting general ability?
Continued pretraining adds domain knowledge that fine-tuning cannot, yet done carelessly it wrecks general ability. The signal is the replay ratio, learning-rate rewarming, and how you measure forgetting.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Continued pretraining adds domain knowledge that fine-tuning cannot, yet done carelessly it wrecks general ability. The signal is the replay ratio, learning-rate rewarming, and how you measure forgetting.
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.
