Our own website's search and AI-answer visibility, run by self-improving agents: measure daily, propose, change, then judge each change after 7 and 14 days
Clayton Cybernetics, for its own website.
Reviewed by Christopher Clayton, CEO
- Scale
- 26 tracked buyer questions, 12 probed each day, 4 data sources, 1 change ledger, 2 review checkpoints, 1 news wire every 6 hours
- Engagement
- Started 10 November 2026; ongoing and still early
The challenge
Buyers now ask an AI assistant who to hire before they ever open a search page, and they still search on Google and Bing. A new site has to be found in both. Doing that by hand means guessing, and guessing about search is how sites end up with thin, repetitive pages that rank worse. We wanted our own site to be run by the same kind of agents we build for clients: ones that measure what happens, change one thing at a time, remember what they changed and judge it later.
We run our own website with the kind of agents we build for clients. The goal is plain: people in Miami and across the US who search Google for our services, and the AI assistants they ask, should find Clayton Cybernetics. Nothing about that can be settled by opinion, so the site is managed by custom agents that measure, change, remember and judge.
Every day an AI assistant with live web search is asked 12 of 26 tracked buyer questions, on a rotation, some from a Miami viewpoint. The system stores whether we were mentioned or cited, where we ranked among cited sources and which sites were cited instead. Google Search Console and Bing add the searches that showed our pages, and site analytics adds visits by source. A daily report then gives a 14‑day trend and three to eight ranked proposals, each with its evidence. Proposals that only a person can do, such as business listings or reviews, are handed to a person and never faked.
The agents that own each part of the site turn proposals into changes under honest-content rules: no invented facts, no fake reviews, no thin pages made in bulk and no client names. Every change goes into a ledger with the proposal behind it, the pages it touched and the questions it targets, and it is judged after 7 and 14 days. What works is extended; what does not is reworked or reverted. A separate wire reads about 14 public security and IT news feeds every 6 hours and picks 12 stories, with links taken from the feeds themselves and feed text treated as untrusted data.
We are early and we say so. The first measurement, on 10 November 2026, found 0 of 12 answers mentioning or citing us, and that is the baseline every later result is compared with. In its first day the loop produced five recorded changes aimed at the gaps it found. Whether they work will show in the 7‑day and 14‑day reviews, and the page will be updated with what the numbers say, good or bad. The case is here because the mechanism is what we offer: an agent that learns from its own results and keeps a person in charge of what is claimed.
What our team delivered
- A daily measurement run: an AI assistant with live web search is asked 12 of the 26 tracked buyer questions on a rotation, some from a Miami viewpoint, and the system stores whether we were mentioned or cited, our rank among the cited sites, which domains were cited and an excerpt of the answer
- Three more data sources beside it: Google Search Console and Bing Webmaster Tools for the searches that showed our pages, and privacy-friendly site analytics for visits by source, with leads counted separately
- A daily report with a trend over 14 days and three to eight ranked proposals, each backed by the evidence that produced it; owner-only items such as business listings and reviews are routed to a person and never faked
- Implementation by the agents that own each part of the site (content, articles, FAQs, design), under honest-content rules: no invented facts, no fake reviews, no mass-produced thin pages, no client names
- A change ledger: every change is recorded with the proposal behind it, the pages touched and the questions it targets, and each is judged after 7 and 14 days; what works is kept and extended, what does not is reworked or reverted
- Faster discovery: each deploy tells search engines which pages changed, and a separate threat wire reads about 14 public security and IT news feeds every 6 hours, picks 12 stories and writes one-line summaries, with links and sources always taken from the feeds, never from the model
Result
This case is about the mechanism, not the outcome yet. The first measurement on 10 November 2026 gave a baseline of 0 of 12 questions mentioning or citing us, which is what a brand-new site should expect. Within the same day, the agents had read the first report, traced the gap to directory listings and competitors' city pages, and shipped five recorded changes: a South Florida hub, entity and location signals, answer-first sections on regulated-industry pages and articles, a law-firm opening and an emergency first-hour checklist. Their effects will be reported after 7 and 14 days, whatever they turn out to be.
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