context

Small chunks match precisely but starve the LLM of context; big chunks have context but match badly. Parent-child retrieval refuses to pick. The signal is decoupling what you match on from what you feed the model.

A chunk embedded in isolation forgets which document, section, and entity it came from, so it retrieves poorly. Contextual retrieval writes that context back in before indexing. The signal is fixing retrieval at index time, not query time.

Toxicity detection looks like vanilla text classification and is anything but: context flips labels, adversaries evolve weekly, and naive models flag dialects as hate. The signal is naming those failure modes and designing the human-in-the-loop system around them.