Definition
Search agent optimization (SAO) is the practice of structuring content so AI agents that search the web on a user's behalf can reliably find, fetch, and cite it. It overlaps with GEO and AEO but focuses on the agent loop specifically: tool-calling, retrieval, parsing, and final answer composition.
In Depth
Where SEO targets human readers and crawlers, and AEO targets generative answer surfaces, SAO targets the agent that drives both. An agent issues tool calls (search, fetch, extract), parses returned context, and decides whether to cite. SAO work includes returning typed JSON instead of raw HTML, exposing structured FAQ and entity blocks, keeping `llms.txt` and `llms-full.txt` current, and minimizing token waste in fetched pages. Teams running coordinated SEO + AEO + SAO programs in 2026 measure each surface separately and treat the agent loop as a first-class retrieval channel rather than a side effect of SEO.
Example Usage
The content team added structured entity blocks and a `llms.txt` index as part of their search agent optimization sprint, then watched citation share in Claude and ChatGPT climb across the next month.
Platforms
Search Agent Optimization is relevant across the following platforms, all accessible through Scavio's unified API:
Related Terms
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