01 How a generative engine builds an answer
Ask ChatGPT search, Perplexity, or Google AI Overviews a commercial question and three systems fire in sequence. Retrieval pulls candidate pages from a live web index. A selection layer decides which of those sources are trustworthy enough to quote and cite. Then the model writes, blending what the chosen sources say with its prior sense of your brand from training data. That prior matters more than most buyers expect: models answer plenty of questions without searching at all, and those answers favor brands the training corpus described often and consistently.
The sequence is the entire playbook. If retrieval never surfaces a page about you, you cannot be cited. If the pages it finds say little or contradict each other, you get a vague sentence or nothing. If the model barely knows you, even good retrieval gets diluted by a competitor it knows better. Generative engine optimization is the discipline of working all three stages at once, which is why single-tactic vendors disappoint.
02 What GEO work actually changes
A serious GEO program changes four concrete things. It changes which pages about your brand exist, by earning coverage in publications the retrieval systems already index and trust. It changes what those pages say, by putting specific, consistent claims into the world: your category, your differentiators, your proof. It changes how quotable your own site is, through answer-shaped sections and schema.org markup that make extraction and attribution easy. And it changes the model prior slowly, as accumulated mentions flow into the corpora future models train on.
Notice what is missing from that list: prompt tricks, hidden text, secret keywords, anything that claims to steer a model directly. As of mid-2026 no reliable lever of that kind exists, and the engine providers actively close whatever loopholes appear. Vendors selling one are guessing with your budget. The durable path runs through evidence, and evidence can be built on schedule.
03 Why press coverage is the highest-leverage input
Every stage of the answer pipeline privileges independent sources. Retrieval systems index news heavily and recrawl it often. Citation layers prefer publications with editorial standards over self-published claims, because a third party vouching for you is worth more than you vouching for yourself. Training corpora over-represent journalism relative to marketing copy. One earned story in a respected outlet therefore does triple duty across retrieval, citation, and training, which is why press placements with backlinks are the spine of our retainers rather than a line item at the bottom. The full trust mechanism is mapped on backlinks for AI trust.
Your own content still matters, but it plays a supporting role. It is the destination that converts, and it is the source machines quote for the facts only you can state, like pricing and product specifics. Which page types earn quotes, and how to build them, is covered on our AI citations page.
04 Running generative engine optimization as a program
We run generative engine optimization as a monthly retainer with a fixed measurement loop, not a one-time audit, because every input in this discipline compounds and none of them spikes. Each month brings new press placements, entity corrections, one or two pages rebuilt for quotability, and a re-run of your prompt panel across ChatGPT, Claude, Perplexity, Gemini, AI Overviews, and Microsoft Copilot. The report records who got named, who got cited, and how descriptions of your brand changed. When a month moves nothing, the report says so, because some months will not, and pretending otherwise would poison the data you steer by.
Results build the way reputations build: unevenly, then convincingly. For the full service picture, start with our AI SEO services page, or compare tiers on pricing. Foundation programs begin at $3,500 per month, carrying a minimum of five placements, with no setup fees.