My Two-Tool Workflow for Semantically Optimised Content

There are a lot of AI SEO tools now. I use two, and the value is mostly in how they combine rather than in either one alone.

Before the tools, the honest framing: AI visibility depends on your content and on your marketing — what you do for links and mentions. Tools help with the first. They do nothing for the second, and no tool will.

The stack

Drafting: Claude. I prefer it to ChatGPT for content writing specifically — the output quality is noticeably better for long-form. Both have free tiers; I use the paid version heavily enough to hit limits, which reset after a few hours.

Entity optimisation: NeuronWriter. This handles the part AI writing tools cannot do on their own: telling you which entities and terms the ranking pages actually cover.

On cost. Surfer SEO is the better-known option at around $99/month. NeuronWriter starts at $23/month, or about $19 paid annually. It will not give you Surfer's polish, but the results are genuinely good. If budget is a factor, NeuronWriter is the sensible choice — this is my own experience across client work.

Step 1: Extract the entities

Create a project, add your site, set country and language, then add a query. For a client of mine — a salon — I used "microblading Grapevine," with the region set to Texas.

It scans and analyses the competitors.

Now the important part: filter the competitor list by content score. Drop anything below 50%. You will find plenty scoring 80% or 90% — pick those. I usually select around four.

You are deliberately modelling against pages that already cover the topic comprehensively, not against whatever happens to rank.

What you get out:

• Entities for H1, H2 and H3 — the concepts that belong in your heading structure
• Basic entities — the mandatory terms
• Extended entities — the broader coverage layer
• A target score — mine was 81+, since that is what the strong competitors were achieving

This is your coverage specification. It is not a keyword list; it is a map of what the topic actually contains.

Step 2: Draft with a real prompt

Copy the entities across to Claude. Then the prompt does the heavy lifting.

Mine is long and deliberate. The structure:

Assign the role. "You are an expert semantic SEO content author, trained and calibrated on Koray's framework."

Koray Tuğberk GÜBÜR's framework is worth looking up if it is unfamiliar — it covers Google's information retrieval concepts, NLP, topical authority, contextual vectors and entity optimisation. A large body of work, and widely followed for good reason.

State the goal, and state what it is not. "Your goal is not to write an SEO article. Your goal is to create a page that demonstrates complete topical authority and satisfies every possible search intent around the topic."

That distinction matters. I am not asking for an article. I am asking for page content.

Give the context. The website, the focus service (microblading), the target region (Grapevine).

Set the objectives. Semantically optimised, following the framework. Cover the topic completely. Build topical authority. Avoid content dilution. Cover every important entity, with attributes, values and relationships. Build contextual bridges. Satisfy informational, commercial, navigational and transactional intent.

That last one deserves a note. For a service page, this is not writing about microblading in the abstract. It is covering where someone should get it done, who does it well, who provides it in a given area — which is where the geographic terms enter naturally.

Specify the technique. Entity-rich writing. Attribute-value relationships. Contextual bridges. Lexical diversity. Information gain. Search intent coverage. Semantic relevance. Topical completeness. Natural co-occurrence.

The key idea underneath all of it: writing the same thing ten times is repetition. Writing the same subject ten times from different angles, covering different aspects, is semantic coverage. Those look superficially similar and are completely different in effect.

Specify what not to do. No keyword stuffing. No repeated sentences. No filler. No thin content. No generic marketing copy. And critically — do not sacrifice readability chasing keyword inclusion.

On readability: paste the finished draft into the Hemingway app. It flags what is hard to read. That matters for credibility, because content nobody can comfortably read does not build trust regardless of how well optimised it is.

Give it the entities. Explicitly: these in the H1, these in the H2s, these throughout the body, and roughly how often — so they land naturally rather than being stuffed.

Add a verification step. "Before returning the content, silently verify that every important search intent discovered and every required entity has been covered. If anything is missing, redo it."

This is the highest-value line in the whole prompt. Without it the model delivers immediately and misses things. With it, it self-checks first.

Constrain the output. Title, meta description, slug. And: "Write only the finished content. Do not explain your reasoning or describe your process."

The effort goes into the prompt so the model can spend its effort on the content.

Step 3: Close the term gaps

Paste the draft back into NeuronWriter. The content score appears immediately — mine came in at 72, against a target of 81+.

Now you work the term list, which colour-codes usage:

• Red — over-optimised, used too many times
• Orange — used more than ideal
• Not used — missing entirely

Copy each group and feed it back to Claude with clear instructions:

"These terms have been over-optimised. Balance them in the content and do not exceed the required number of instances."

And for the gaps:

"Try using these terms as well, including some from the extended list."

Regenerate, paste back, re-score. Repeat until the score clears your target and the reds are resolved.

Then set your metadata in NeuronWriter and publish.

What this does and does not achieve

What you end up with is content covering a topic comprehensively at the entity level — genuinely semantically optimised rather than keyword-matched. That is a real advantage and most competing pages will not have it.

But the boundary needs stating plainly.

On-site content matters enormously for AI visibility. It is not sufficient. Your links and your mentions matter just as much. No tool in this workflow produces either.

So use the workflow, get the content right, and then invest on the off-site side too. Content quality gets you eligible for citation. Brand signals are a large part of what decides whether you actually get it.