AI search security: keep retrieved content in the role of evidence
Map trust boundaries, limit tool authority, protect credentials, and evaluate how the full application handles outside content.
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AI & Search / 3 FIELD GUIDES
Answers with a traceable source.
Explore the boundary between search results and generated answers. This collection covers evidence selection, citation checks, uncertainty, and the controls needed when a model reads outside content.
A useful reading route
Start with the AI search overview for the product decisions. Move to grounding for the evidence structure, then review security before adding tools, private data, or consequential actions.
Keep the evidence in view
Each guide separates its example workflow from documented source behavior. Follow the editorial source in the article for the relevant reference, and preserve the stated limitations when adapting an example to your own project.
AI search engines: from discovery to evidence-backed answers
Separate discovery, retrieval, and generation. Design an AI search experience that makes its evidence and limitations visible.
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Connect search to an LLM without losing the source
Build evidence packets, select relevant passages, validate citations, and test what happens when the sources cannot answer.
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