Christian Stewart

My focus is practical rather than theoretical. I care about how search visibility is actually produced — the systems that create pages, the evidence that justifies claims, the measurement that tells you whether anything changed — and increasingly about how AI assistants retrieve and represent that work.

Connector Scout began with a build, not a content plan. I wanted a daily AI SEO analyst: a read-only workflow that could connect to Google Search Console, Google Analytics 4, and Ahrefs — with Microsoft Clarity, CrUX and PageSpeed Insights, and Semrush as optional supporting sources — normalize those very different datasets, flag the changes that actually mattered, and prepare a daily brief for a human to review.

Researching that build was harder than building it. Connector information across AI platforms turned out to be fragmented, plan-dependent, and fast-changing: the same integration would be documented in three places with different scopes, gated behind a plan tier that was only mentioned in a footnote, or renamed between releases. There was no reliable place to check which AI assistant could connect to which work system, what the connection could actually do, and where its limits were.

Connector Scout is that place. Every record is resolved from official provider documentation and carries a verification date. The full build it came from is published as the Daily AI SEO Analyst guide.

The human-review boundary is deliberate and it applies to this site as much as to the workflow. AI helps organize research and analyze normalized evidence. It does not independently publish connector claims and it does not make changes to this site. Official provider documentation and dated verification remain the basis for everything published here.

Every published claim on Connector Scout traces back to a provider’s own documentation and carries the date it was checked. Where documentation is ambiguous or two official pages disagree, the record says so rather than picking the tidier answer. Records that have not been researched to that standard are labelled as research pending and kept out of the index.

AI assists the research process — collecting candidate sources, normalizing evidence, surfacing changes between checks — but a human reviews every claim against the official source before it is published. The verification methodology sets out what counts as an acceptable source, and corrections are logged and dated when documentation changes or a record turns out to be wrong.

Connector Scout is an independent personal editorial project. It is not affiliated with, endorsed by, or an official publication of my employers, former employers, OpenAI, Anthropic, Google, Microsoft, Adobe, or any connector provider named on this site.

No platform or application pays for inclusion, placement, or a recommendation. Views and editorial judgments here are my own. Product names and trademarks belong to their respective owners.

More on how the project positions itself is on the About Connector Scout page.

If a published record no longer matches what a provider documents, the fastest route is a correction request to Connector Scout. For anything else, I am reachable on LinkedIn.