AI Internal Linking: Review Suggestions Before Publishing

AI internal linking is most useful when it proposes relevant connections that an editor can verify. These three workflows cover target-page prompts, a destination registry and suggestions inside WordPress. They illustrate ways to keep control of links, rather than establish a ranking benefit from automation.

The lesson

Constrain AI link suggestions to real destination URLs and existing source text, then review whether each link helps the reader.

What people reported

These public accounts describe different setups. Read each reported outcome with its design limits; repeated descriptions of the same campaign are not independent replications.

u/darrenshaw_: A target-page prompt

Reddit user u/darrenshaw_ shared a prompt that proposes source pages, anchor text and exact placement for links to a target URL. The useful output is a reviewable suggestion table. The discussion also raises limits around crawl coverage, so the instruction to inspect a whole site should not be mistaken for proof that every page was inspected. Read the original report: u/darrenshaw_ — Reddit

Supply approved destinations and the actual source paragraph. A topic similarity score cannot show whether a link helps the reader at that point. Reject suggestions that require changing the paragraph's meaning or that promise an answer the destination does not deliver.

u/zvendezapguitar: A maintained registry of destinations

In the same discussion, u/zvendezapguitar describes a separate plugin workflow using registered keywords and approximately 200 evergreen destination links. Related phrases help surface opportunities after an article is written. This is a different person’s reported implementation, not an independent test of Darren’s prompt, and no ranking change is supplied. Read the original report: u/zvendezapguitar — Reddit

This contribution comes from the same Reddit discussion as the target-page prompt, not a separate controlled experiment. A registry can prevent invented URLs, but it needs maintenance when pages redirect, change purpose or disappear. Include a brief description of each destination so repeated anchor phrases do not replace editorial judgment.

u/ConsciousRealism42: Suggestions inside the WordPress editor

User u/ConsciousRealism42 describes building Contextual Link Weaver with Gemini to suggest links to published posts using anchor phrases already present in a draft. The author acknowledges variable suggestion quality; the comments also discuss insertion problems around punctuation. It is a builder’s experience with an available code reference, not SEOVision’s endorsement or test of the plugin. Read the original report: u/ConsciousRealism42 — Reddit

An editor interface shortens the path from suggestion to approval. It still needs an undo option and inspection of the final paragraph. Check punctuation, duplicate links and destination accuracy in the rendered page; a convenient plugin does not by itself establish a helpful linking strategy.

What the experiences have in common

All three approaches reduce the memory burden of remembering a content library. They also make the editorial decision visible: which page should link, to what destination, through which words and in what context? That is a more useful unit of work than requesting an arbitrary number of links.

The next check belongs to the site owner. Confirm that the source sentence exists, the destination resolves correctly and the link adds a useful next step. A semantically related page may still be too broad, outdated or commercially irrelevant. Similarity is an input to the decision, not the final reason to insert a link.

What these reports cannot establish

These reports contain no controlled ranking measurements. Two come from one discussion and may share enthusiasm or assumptions. The third is a product-build announcement. They support the feasibility of generating suggestions, while leaving precision, time savings and search impact open to testing. Counts such as 20 suggestions or a particular anchor length are not universal optimization targets.

Use an approved destination registry and rejection log

Store the canonical URL, page purpose, relevant topics and last review date for each destination. Generate candidates from this approved list. Google's crawlable link guidance supports normal anchor links and descriptive text; an AI similarity score does not substitute for these basics.

Review a small batch and record accepted and rejected suggestions with reasons. Measure review minutes per accepted link, broken destinations and context errors. Check that the published anchor is a real link and that the destination remains available. There is no useful universal quota of links per paragraph.

A test you can run: proposed protocol

Use the following protocol as a starting design. Choose one outcome and a practical review window before making changes, and retain the original observations so a disappointing result remains reportable.

1. Export a verified list of eligible destination URLs and the text of 20 source pages. Exclude non-indexable, redirected and already-linked destinations as appropriate.
2. Generate suggestions restricted to that inventory. Require the exact source sentence, destination URL and a short explanation of the reader benefit.
3. Review a shuffled mix of manual and AI suggestions without identifying the method. Record accepted, redundant, incorrect and invented placements.
4. Measure time per accepted link and the rejection rate. Implement only reviewed links, then check the rendered pages and destination responses.
5. If evaluating SEO impact, keep comparable pages unchanged and observe over several weeks. Report user navigation and organic performance separately; do not attribute every movement to the links.

Conclusion

The reports support a reviewable suggestion workflow, not automatic insertion or a promised ranking uplift. The registry and editor controls are useful because they expose the decisions a model can get wrong.

Start with one content cluster and an approved URL list. Scale only when suggestions consistently survive review and the final links help readers navigate. Fix the input registry or prompt when the same rejection reason recurs; adding more links does not solve a relevance problem.