The page says chunking has degraded retrieval quality in the internal knowledge-base bot. What that actually means is explained by the trace: on call sees a plausible response, a successful vector query, and citations that point to the right handbook but the wrong passage. Nothing is down. The retrieval unit is wrong.

TL;DR: chunking decides what a match can possibly be about. A chunk that mixes two topics matches both weakly; a chunk that splits an answer across a boundary may match neither half well enough. For a B2B SaaS knowledge base, start with structure-aware boundaries such as headings and complete procedures, retain stable source metadata, and measure whether the retrieved chunk actually contains the answer and enough context to cite it. Token count is a capacity constraint, not the design objective.

That distinction changes the alert.…