Automate SEO with an AI agent: the data → content → publish loop

The SEO workflow at most companies looks like this: a marketer exports data from Search Console on a Friday, spends Monday turning it into briefs, hands them to a writer who delivers drafts two weeks later, rounds of review follow, the post goes live a month after the original insight, and the ranking data won't be meaningful for another 60–90 days.

That is not a content problem. It is a latency problem. The insight, the action, and the measurement are separated by weeks of human handoffs. By the time the loop closes, the opportunity may have moved.

An AI growth agent removes the handoffs. It reads the data, identifies the gap, writes the content, publishes it, and monitors the result — in a continuous cycle that runs whether or not anyone is sitting at a desk.

1. Google Search Console — what you already rank for

Search Console is the most underused dataset in most companies. It shows every query your site has appeared for in the past 16 months, along with impressions, clicks, click-through rate, and average position. Most teams glance at the top 10 queries and ignore the rest.

The agent reads all of it. Specifically, it looks for queries in positions 11–30: pages two and three of Google. These pages are already indexed and relevant — Google has already decided your content is related to the query. The only problem is it is not good enough to reach page one. That is a writing and structure problem, not a relevance problem, and it is exactly what the agent can fix.

2. On-site search data — what your visitors are looking for

If your site has a search bar, every query typed into it is a content brief. Visitors who search are telling you exactly what they expected to find and did not. Tradly Memory captures this behavioural signal per visitor, which means the agent can see not just what people searched for but how often, from which pages, and whether they converted after.

A cluster of on-site searches with low conversion is a strong signal: there is demand for this topic, your site is not satisfying it, and a new page would capture visitors who are currently leaving.

3. Engagement data — what content actually works

Not all pages that rank also convert. The agent reads time-on-page, scroll depth, and return visit rate for existing content. Pages that rank but have low engagement signal a quality problem — the agent can rewrite them. Pages with high engagement but low impressions signal a distribution problem — the agent can build supporting content and internal links to lift them.

Step 1: Score content opportunities

The agent pulls query data from Search Console and scores each query on a gap score: a combination of current position, impressions (demand), current CTR vs. expected CTR for that position, and whether you have an existing page targeting the query. Queries with high impressions, positions 11–30, and no dedicated page score highest.

Step 2: Build a content brief

For each high-scoring query, the agent generates a brief: target keyword, supporting keywords from the same cluster, recommended heading structure, questions to answer (sourced from the "People also ask" box and related searches), word count target, and internal links to add. The brief is created from data, not instinct.

Step 3: Write the draft

Jack writes the post against the brief. The output follows the heading hierarchy, covers the supporting questions, includes the target keyword in the title, first paragraph, and at least two subheadings, and targets the word count needed to match or exceed the current page-one results for that query.

The draft includes structured data (FAQ schema, Article schema) and internal links to related content — two factors that consistently correlate with ranking improvement.

Step 4: Publish to CMS

Jack publishes directly to Tradly CMS. The CMS outputs content in LLM-optimised structure by default: clean heading hierarchy, canonical URLs, per-page meta tags, FAQ schema, and structured data — without any configuration required. Every published post is immediately crawlable and structured in the way both Google and AI answer engines expect.

Step 5: Monitor and iterate

After publishing, the agent tracks impressions and position for the target query. If impressions rise but position stalls in the 11–20 range, it adds internal links from higher-authority pages. If position improves but CTR is low, it rewrites the meta title and description. The loop does not end at publish — it continues until the page reaches a stable position-one ranking.

Most technical SEO problems are small and repetitive: missing meta descriptions, duplicate title tags, broken canonical tags, missing schema markup, slow image loading, broken internal links. They are easy to fix once you know they exist, but tedious to find and address at scale.

Jack's coding agent connector gives it access to your codebase or workspace VM. When it identifies a technical issue — a page without a meta description, an image without alt text, a missing FAQ schema on a high-traffic post — it opens a pull request or applies the fix directly, depending on your configuration.

This closes the gap between SEO audit and SEO action. Instead of a report that sits in Notion for three months, the fix is applied the day the issue is found.

What the coding agent can fix automatically

In a typical codebase, Jack can add or update: page-level meta titles and descriptions, canonical link tags, Open Graph and Twitter card tags, JSON-LD structured data (Article, FAQ, BreadcrumbList, Organization), image alt attributes, internal link href values, and sitemap entries for new pages.

It works within the scope you define. You can restrict it to read-only (draft PRs for review) or allow autonomous fixes for low-risk changes like meta tag updates.

For pages targeting position 11–30 queries, you should see impressions move within two to four weeks of publishing improved content. Position changes typically follow within four to eight weeks. CTR improvements from better meta titles and descriptions can show within one to two weeks of the change.

The metrics worth tracking in the agent's dashboard:

• Impressions per page — rising impressions mean Google is showing your page more often, even before position improves
• Average position — the most direct signal of ranking improvement
• CTR vs. position benchmark — if your CTR is below the industry average for your position, the meta title is the problem
• Pages published per month — velocity matters; the agent should be shipping at least four to eight posts per month to build topical authority
• Organic-attributed conversions — the ultimate metric; tracked via UTM parameters on all published content

What still needs a human

The agent handles routine content and technical fixes well. What it does not replace: editorial judgment on brand voice, decisions about entering a new topic area, relationship-building for link acquisition, and crisis communications. Think of it as a growth engineer who handles the repeatable work at scale, freeing your team to focus on strategy and relationships.

To run the full loop with Jack, you need:

• Google Search Console access — Jack authenticates via the Search Console API
• Tradly Memory pixel installed — captures on-site behaviour and search queries
• Tradly CMS — where Jack publishes content, already LLM and search optimised
• Workspace VM connection (optional) — for technical SEO fixes via the coding agent

Setup takes under an hour. Once connected, Jack runs the scoring loop on a schedule you define — daily, weekly, or continuously — and surfaces its top opportunities for your review before publishing.

You can start with human-in-the-loop publishing (Jack drafts, you approve) and move to autonomous publishing once you are confident in the output quality for your brand voice.