Adaptive retrieval
Adaptive retrieval is when the system decides on the fly whether to look something up, and how hard, instead of always searching or never searching.
Easy questions can be answered from memory. Hard, fresh, or high-stakes ones should trigger search. If your page only exists in the live web, you need the engine to choose retrieval. If you are a household name, memory might be enough — and harder to correct.
GEO implication: do not assume every prompt browses. Sample both modes.
Examples
- ChatGPT answers “what is photosynthesis” from memory, then searches for “Acme outage today.”
- A legal prompt always browses because the lab configured it that way.
Related terms
ChatGPT Search is OpenAI’s live web retrieval inside ChatGPT. It is a different beast from “what GPT remembers about you.”
The date after which the model’s weights don’t include the web. Anything newer needs browsing or RAG.
RAG means the model looks up documents at answer time instead of relying only on what it memorized in training.
FAQ
Can I force retrieval? +
Not as a third party. You can make pages worth fetching and keep facts dated so a browsing run prefers you.
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