The first RAG system I shipped chunked every document at 512 tokens with a 50 token overlap, because that was the example in the tutorial I was reading at three in the morning. It worked well enough to ship. It worked poorly enough that two weeks later a customer support engineer pinged me with a screenshot of the assistant confidently citing a policy document, except the cited paragraph was the second half of one policy glued to the first half of an unrelated one. The model had retrieved a chunk that crossed a section boundary, and the chunk read like a single coherent rule that did not exist anywhere in the source. Fixing that one bug took longer than building the original retriever. That was a few years ago. The pattern has not changed. Teams still ship RAG systems where the LLM is sophisticated, the embedding model is fine, the vector store is overkill for the data volume, and the chunker is a one-line call to a default splitter that tears documents apart at arbitrary character offsets.…