Index listing of all 8 items tagged with #retrieval.
Retrieval finds candidate material; context assembly decides what the model receives. Why finding the right document does not guarantee the right answer.
Reusing answers across differently worded questions, and the failure that makes it dangerous: two questions can look alike and need opposite answers.
An embedding turns text into a list of numbers, so that related text lands close together. What the numbers, dimensions and similarity scores mean.
Confidence in generative systems is earned through retrieval verification, not model scale.
Stored information becomes operational knowledge only when naming, scope, and links stay consistent.
Strong answers usually begin with grounded context, not confident phrasing.
A weekly pass format for keeping note structures coherent, linked, and retrieval-ready.
A compact resource pack for checking whether an AI system retrieves the right evidence before it answers.