AI SEO content workflow: research → draft → verify → connect → publish

1. Choose a search destination, not a keyword

Group queries by the outcome the searcher wants. If several keywords lead to the same SERP and user task, they usually belong on one strong page. Split only when the intent, SERP or monetization behavior is genuinely different.

This decision prevents the most common AI-scaling mistake: generating one page per phrase and creating a site full of cannibalizing near-duplicates.

2. Build the evidence pack

Collect first-party product documentation, current pricing, authoritative references and any proprietary material the page should reflect. For software, capture a verification date because features and plans change quickly.

Koala’s Deep Research can automate part of this retrieval step, while Brand DNA can supply site or business context. Human review still decides which sources are good enough.

3. Draft against a deliberate brief

The brief should state the user problem, page role, required evidence, sections that must be covered, claims to avoid and the next useful internal destinations. AI then has a target beyond writing a fixed word count about a keyword.

For commercial pages, include the buying decision and the circumstances where the product is not the best fit.

4. Run the editorial passes

Check intent, factual accuracy, unique contribution, style and conversion separately. This is faster than trying to make it better in one vague editing pass. High-stakes niches need expert-level review and conservative claims.

5. Connect the page to the site

Add a parent hub link, useful sibling links, contextual child links and the relevant commercial path. Internal linking should explain the topic architecture to both readers and crawlers.

KoalaLinks can automate link discovery and placement, but links should still represent real topical relationships rather than a quota.

6. Publish, observe and expand from data

Ship the canonical page, include it in the sitemap, verify crawlability and monitor Search Console. Look for unexpected queries and positions 5–30. Improve the existing page when new terms share the same intent; create a new destination only when the user goal diverges.

This loop keeps the site finite and evidence-led instead of expanding forever from keyword lists.