The short definition
Generative Engine Optimization is a measured effort to improve how a brand and its evidence appear in AI-generated answers. It starts with the same fundamentals that make a page useful in search, then adds explicit source, entity, and answer-level measurement work.
What reliable GEO work includes
- Search eligibility: crawlable HTML, correct status codes, canonicals, internal links, language signals, and index checks.
- Useful evidence: clear claims, original value, current facts, direct sources, and visible limitations.
- Entity consistency: the same verified company name, address, contacts, and service descriptions across legitimate public profiles.
- Corroboration: genuine reviews, relevant editorial coverage, partner references, and accurate directory profiles.
- Measurement: repeated prompts under documented conditions, with sources, mentions, citations, recommendations, failures, and non-triggers logged separately.
What platform documentation actually says
Google says normal Search requirements apply to AI Overviews and AI Mode. No special AI text file or special schema is required. OpenAI separates OAI-SearchBot, GPTBot, and ChatGPT-User by role. Those official controls are a stronger foundation than an agency's theory about hidden weights.
Read the current official guidance from Google Search Central and OpenAI's crawler documentation.
How to establish a baseline
Choose a small fixed prompt set, specify language, account state, location condition, surface, and model or mode, then spread repeated attempts across scheduled time windows. Retain each response and code visible sources, mentions, citations, and recommendations separately. A failed request is not a brand absence, and a Google search with no AI Overview block is a non-trigger rather than a negative answer.
What to avoid
- Guaranteed citations, rankings, recommendation slots, or timelines.
- Calling one model response cross-engine share of voice.
- Presenting schema, FAQ markup, llms.txt, or Wikidata as a universal citation lever.
- Treating vendor-study correlations as causal platform rules.
- Publishing a success story before the underlying panel and evidence exist.
Where to go next
Use the bilingual glossary for terminology, the GEO versus SEO guide for the evidence boundary, and the example-program page to understand how a responsible engagement can be structured. The GEO readiness tool checks technical preparation and includes a clearly labelled experimental single-model observation. It is not a substitute for a controlled panel.