What an AEO agency does in your first 100 days

The first 100 days start with a calendar and a short list of the questions buyers actually ask.

An AEO agency optimizes for "direct answers in search engines and AI assistants," as a February 2026 Moosend roundup of 13 such agencies defined it, and the first 100 days put that to work.

Most buyers walk in expecting traffic. I understand why. Traffic is the number everyone learned to read. A fair agency can tell you up front what you will see at day 14, day 45 and day 100. Builders of AEO tracking tools put the content feedback loop at 3 to 6 months, buried under seasonality and competitor moves.

So before you sign, ask any agency which questions it will be judged on. Not visits. Answers.

The tools will not do that judging for you. In an r/aeo thread where agency operators compared notes on AI search work, the original poster put it in two sentences: "The tools report what happened. The judgment and the deliverable stay manual." I keep coming back to that line. It describes the whole engagement.

What follows is that engagement week by week, from the first audit to day 100, and what you sign off on at each turn.

What happens in days 1 to 14 of an AEO agency engagement?

Days 1 to 14 are measurement: an audit benchmarked against our 26,577 real AI-visibility audits, a list of agreed target questions, and a baseline across four AI engines.

The first two weeks run in this order:

1. Audit the site against the same criteria every other scored domain was measured on.
2. Draft the buyer questions your customers actually put to AI engines, and agree them with you.
3. Ask each question in ChatGPT, Perplexity, Google AI Overviews and Gemini, and record who gets named.
4. Mark every question where you are missing, and every one where a competitor is named instead.

The benchmark matters. Our scoring covers 11,000+ domains across 15 sectors and 28 categories, so a site is not graded against an abstract checklist. It is compared with the sites it actually competes with. I've always thought a number in context says more than a number alone. A gap you can see next to a rival's name is hard to argue with.

The question list is the part I'd ask you to slow down on. A practitioner in an r/aeo thread about which actions drive most AEO results suggested running your top 3 buyer questions through ChatGPT, Gemini and Perplexity as a first diagnostic, then keeping a sheet of 10 to 15 buyer prompts checked weekly. That cadence is sane. The common assumption is that the baseline is a formality, a box ticked before the real work. It is the real work. Every article written later points back to one of those questions, which is why you sign off on the list before anything is drafted.

Then there is the report itself. In a separate r/aeo thread, an agency-side poster described spending half a day turning tool screenshots into a client deck, and warned that most visibility reporting averages early informational answers and decision-stage answers into one number, so the drop at the decision stage never shows up. The lesson is the same: a baseline is only useful when it is specific. I'd split it by intent. The questions a buyer asks while learning sit apart from the ones asked while choosing.

In practice, nothing ships in these two weeks. That is deliberate. The audit tells you what is broken, and the baseline tells you where you are invisible, and those are different problems.

If some of the vocabulary is new, the AEO knowledge base guides cover the terms in plain language. Read them once and the reports stop sounding like code.

By day 14 you have a list, a baseline and a short stack of gaps. Somebody still has to choose which gap gets closed first.

What goes live on your site in days 15 to 45?

Days 15 to 45 put the first answer-first articles on your site and fix schema. In our pilot, every product claim checked line by line against the code was correct.

The technical layer goes first, and it is smaller than people expect. One practitioner in an r/aeo thread on high-leverage AEO work put crawl and rendering fixes, answer-first copy and schema at "maybe a day of work per site." The same thread advised placing the answer in the first two sentences of a page. Contrary to how a lot of retainers are sold, schema is not where the weeks go. The weeks go into the articles.

So what does a first article look like when it goes live? Our October 2026 pilot with a live-chat software company is the clearest example I have. We connected two of the product's repositories and indexed 1,368 text files, leaving out 367 backup and retired template files on purpose. The articles were then written from what the product actually does, not from what someone remembered it doing.

That choice caught something. The product's admin page described two-factor sign-in as using an authenticator app. The real sign-in screen sends a one-time code by text and email. An article written from documentation would have repeated the admin wording, and an AI engine would have repeated the article. The pilot's article described what users actually see. When the same two questions were written again with web research removed, the second round carried zero web sources and zero first-person opinions, and nothing about the product had to be taken on faith.

Accuracy is the edge here. Volume is not.

That fits an argument Graphite CEO Ethan Smith made in 2025 on Lenny Rachitsky's podcast: AI-generated content did not work for AEO, and help-center content could be a company's highest-ROI investment. I'd take both points seriously. An answer engine is a patient reader with no way to call you and check. Hand it one wrong detail and it carries that detail forward, answer after answer.

Your part in this window is approval. You see each draft before it goes live, and you correct anything only your team would know: a price that changed last month, a feature that was renamed, a claim legal will not allow. This is the logic behind research-driven content built on evidence. The evidence comes first. The prose follows it.

By day 45 the first pages are live and the schema is clean. The question stops being what to publish and becomes what the engines did with it.

What happens in days 46 to 100?

Days 46 to 100 run a loop: steady publishing, scheduled checks of every agreed question, and each missed question turned into the next article, until you are named in AI answers.

The loop has three moves, and they repeat on a fixed schedule:

1. Publish the next article from the approved question list.
2. Recheck every target question in ChatGPT, Perplexity, Google AI Overviews and Gemini.
3. Turn each question where you are still missing into the brief for the next article.

Here is how a miss looks on paper. Say the baseline showed you absent when a buyer asks an engine which companies specialize in answer engine optimization. That question does not go into a report and die there. It becomes a brief, then a draft you approve, then a page. Then it gets checked again.

Conventional wisdom says this is the stretch where traffic should climb. Gartner disagrees. Gartner's September 1, 2026 analysis, "AEO Is Creating New Blind Spots in Customer Demand," argues that as AI-mediated journeys absorb more of the discovery process, traditional measurement captures a smaller share of how demand forms. Joseph Enever, a Senior Director Analyst at Gartner, put it plainly: "Declining organic traffic may reflect a measurement failure, not a performance failure." Gartner recommends tracking Share of Answer and Citation Presence alongside traffic and revenue, not in place of them.

So keep your own copy of the question list and recheck a few answers yourself between reports. A buyer can read your name in a Gemini answer and never click. The visit never shows up. The influence still happened.

There is a second tension, and it lives inside the tools. In an r/aeo thread about AI agents in AEO software, Sofian, who builds the AEO Copilot tool, wrote: "The intelligence is there. The verification isn't." Another commenter in the same thread added that "the hard part isn't finding opportunities anymore, it's choosing what to ignore." I agree with both of them. A tool will surface gaps all day long, and most of them will not matter to your buyers. The loop holds because every miss is checked against a short list you already agreed to, not against everything a crawler can find.

Some practitioners describe two routes into an AI answer. Being cited from the pages a model reads can move in days or weeks. Being known to the model from its training moves in months or years, one model release at a time. This window lives almost entirely on the first route.

And this is where our AEO agency guarantee sits. If you are not named in AI answers across the agreed target questions within 100 days, we keep working free until you are. More on how the engines choose their sources is in our AEO FAQ answers, for anyone who wants the mechanics.

By day 100 the list is either answered or it is not. What you should actually see by then is narrower than most people expect, and more useful.

What should you expect from an AEO agency after day 100?

By day 100 you should be named in AI answers to the questions you agreed on. Leads come after that, as accurate pages keep getting quoted.

I'd hold any agency to that order. Gartner's analysis argues for a dual-track model: keep traffic, conversions and revenue on the report, and set AI-era visibility measures beside them. At each review, ask to see every agreed question, engine by engine, named or not. Revenue follows.

Think of a neighborhood restaurant. The first sign it is working is not a full room on Friday. It is hearing its name come up when friends argue about where to eat.

Accuracy keeps the name in the answer. One wrong detail, repeated by an engine, does more damage than a missing page. So start with the questions, approve the drafts, and watch the answers before you watch the traffic.

If you want to run it with us, our AEO agency plans are Growth $99, Premium $250, Business $500 and Business Plus $1,000 a month, no contract, cancel anytime. And the promise holds: named in AI answers across your agreed target questions within 100 days, or we keep working free until you are.