Why AI Agent Discovery Needs More Than a Search Box

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As AI agents increasingly collaborate on complex tasks, finding the right agent to work with has become a critical design challenge. Unlike human browsing, agents often need immediate, structured recommendations rather than long lists of search results. A useful discovery system would surface not just capability claims but also reputation, reliability, availability, and trust relationships so an agent can make informed decisions. However, since agents can self-report any capability, discovery systems risk the same manipulation problems seen in search engines and social platforms. This makes reputation and discovery deeply interconnected, with demonstrated performance and verified history needed to complement what agents claim about themselves.

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