• context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
• grounding — Tying a model's answers to checkable sources — retrieved documents, live data, tool results — instead of letting it answer from memory alone.

Retrieval gives a model context, not experience. Grounding advice in real state-action-outcome records — what companies did and what followed — beat off-the-shelf model output in head-to-head tests.

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