AI Search Readiness (SEO / AEO / GEO)
In development. Taking enquiries.
- ·The audit tracks a fixed set of prompts over time and reports share of answers, rather than a position on a page nobody reads.
- ·This service takes no work in the legal vertical, because that is the market of the employer whose hours it would otherwise compete with.
| Becomes live when | This site itself is indexed: verified in a search console, sitemap submitted, and carrying at least one inbound link. A search readiness service whose own site cannot be found is the clearest counter example available. |
| Built with | Next.js · TypeScript |
| Delivered by | · aeo-specialist · growth-director |
| Skills used | ai-seo · programmatic-seo |
What this involves
Two audiences now read a page and only one of them ranks it. A search engine returns a list; an answer engine returns a sentence and, if you are lucky, a citation. The second one rewards different things: an entity graph it can resolve, answers that are complete in their first sentence, and figures it can quote without carrying your adjectives along.
The measurement is a fixed set of prompts, run on a schedule, recorded over time, and reported as share of answers rather than as a position on a page nobody reads. A report that cannot say which prompts were run is not a measurement.
This service takes no work in the legal vertical. That is a refusal rather than a preference: it is the market of the employer whose hours it would otherwise compete with, and saying so on the page is cheaper than being asked about it later.
The condition for this becoming a proven service is deliberately the hardest one on this page, and it is this site. Until agentjames.vercel.app is verified in a search console, has its sitemap submitted, and carries at least one inbound link, a search readiness service run from it is arguing against its own evidence. That gate is stated above and it has not been met.
How the work runs
1. Discovery
We agree what the project has to achieve, what it must not break, and how we will both know it worked, before any code is written.
2. Build
The work is built with an AI agent as the working partner and a human reviewing every change before it lands. You get commits you can read rather than a status update.
3. Review
You review running software at each milestone, not a screenshot of it, and the next milestone absorbs what you send back.
4. Launch
We deploy to production with checks in the pipeline and alerting that reaches a human, and you hold the repository and the infrastructure accounts.
Questions people actually ask
What is the difference between SEO and answer engine optimisation?
The unit of success. Traditional search optimisation competes for a position in a list of links. Answer optimisation competes to be the source a generated answer cites, which rewards resolvable entities, self-contained first sentences, and quotable figures rather than keyword density.
How is visibility in an AI answer actually measured?
By running a fixed set of prompts on a schedule and recording which sources the answers cite, then reporting the change over time. It is a sampled measurement rather than an exact one, and a report that does not publish the prompt set cannot be checked by the client paying for it.
Why does this page say the service is not proven yet?
Because this site itself is not indexed. A search readiness service whose own site cannot be found is the clearest counter-example available, and publishing the gate is more useful than publishing a claim that would not survive somebody checking it.
Why refuse work in the legal vertical?
Because James works at a law firm marketing business, and taking law firm search work through this site would compete with his employer. The refusal is on the page rather than handled quietly at the enquiry stage.