What is semantic chunking, and how does it compare to fixed-size chunking?
Fixed-size chunking cuts a coherent idea mid-thought; semantic chunking splits on meaning. The signal is naming the methods (structure-aware, embedding-similarity, LLM-based) and the tradeoffs that decide which one to ship.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Fixed-size chunking cuts a coherent idea mid-thought; semantic chunking splits on meaning. The signal is naming the methods (structure-aware, embedding-similarity, LLM-based) and the tradeoffs that decide which one to ship.
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.
