Adding one more angle from implementation work, I’m Marc Wajsberg (X8Agency.com).
If EA orgs want their work represented accurately in AI chats, two practical steps often outperform “more content”:
Canonical answer pages: a single, maintained page per key question with an answer-first summary + citations to primary research. Models love a stable canonical source.
Entity anchoring: make the organization, programs, and key terms unambiguous (consistent naming, clear “what we do,” author credentials). This reduces misattribution and hallucinated mashups.
The comment about noun repetition + modular structure is spot on. I’d also add: publish explicit “last updated” signals and keep key pages refreshed, because retrieval systems overweight recency in fast-moving domains.
Adding one more angle from implementation work, I’m Marc Wajsberg (X8Agency.com).
If EA orgs want their work represented accurately in AI chats, two practical steps often outperform “more content”:
Canonical answer pages: a single, maintained page per key question with an answer-first summary + citations to primary research. Models love a stable canonical source.
Entity anchoring: make the organization, programs, and key terms unambiguous (consistent naming, clear “what we do,” author credentials). This reduces misattribution and hallucinated mashups.
The comment about noun repetition + modular structure is spot on. I’d also add: publish explicit “last updated” signals and keep key pages refreshed, because retrieval systems overweight recency in fast-moving domains.