V1.0

Principles

Specification · Version updated 2026-09-25 · Page first published 2026-09-19

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Version: VGO V1.0 published methodology (release notes)

  1. Human First. Begin with real people and real needs, not platforms.
  2. Intent First. Identify meaningful intent and problem spaces before selecting optimization targets.
  3. Effectiveness First. Grow more Effective Visibility rather than maximizing raw exposure.
  4. Visibility is not value. Ranking, mentions, citations, and traffic are intermediate signals, not automatic proof of value.
  5. Effective SEO over ranking alone. Search visibility should help the right audience discover and understand an entity in valuable contexts.
  6. Effective AEO over answer appearances alone. Direct answers should be relevant, accurate and supported by checkable sources; presence alone is not user choice.
  7. Effective GEO over mentions alone. Generative visibility should support correct understanding, credible citation, meaningful comparison, and recommendation in relevant problem spaces.
  8. Owned assets and external signals reinforce each other. First-party assets preserve knowledge and learning; credible third-party sources provide distribution, corroboration, authority, and diversity.
  9. Evidence before assertion. Important claims should be supportable by first-party evidence or credible independent sources.
  10. Optimize for humans and machines. Machine readability must not degrade usefulness to people.
  11. Measure longitudinally without assuming causation. Observe change over time, but do not turn correlation into unsupported causal claims.
  12. Integrity constrains growth. Visibility gained by degrading truth, provenance, or trust fails VGO.
  13. Assets can accumulate; visibility changes. Organizations can retain content, knowledge, data, evidence, and learning even while rankings and AI outputs continue to change.
  14. Action requires an owner and a check. Recommendations should name the affected asset or source, responsible party, evidence, publication condition and verification method.
  15. Automate with reviewability. Automate repeatable observation and support for decisions and execution where appropriate; retain provenance, overrides and review for consequential changes.
  16. Maintain fact ownership and portability. Organizations should control, update and migrate core facts, evidence and learning across providers; credible third parties remain important corroborating sources.
  17. Learning is an output. Keep unsuccessful as well as successful actions and comparable observations to improve the next cycle.
  18. Open to new surfaces, conservative with new concepts. New terminology should solve demonstrated problems rather than expand the system unnecessarily.