I’ve always felt that content writing is not one of my natural strengths. (English isn’t my first language)  Writing long-form SEO articles from scratch has never been my idea of fun. But something changed when I realized I didn’t need to “write like a writer” to produce content that ranks. I just needed a process that can evolve . A workflow that combines the things I am good at: data, structure, and automation. And when I pull those pieces together, and then collaborate with our content manager for the human part, the end result is consistently strong.

It usually starts with data. I’ll open NeuronWriter and run a query for whatever keyword we’re targeting. The tool scans the top 10–30 ranking pages on Google and spits out a massive NLP keyword list. Hundreds of terms, phrases, and semantic patterns that real ranking pages are using. Without this step, letting ChatGPT “guess” what a page should include is useless. With this step, AI suddenly becomes much more predictable.

Once I have all that competitor data, I copy every visible NLP keyword from NeuronWriter and paste it into ChatGPT or Claude, but do not to write the article yet, ask GPT to build the outline. This part is surprisingly important. If you ask AI to write 1,500 words straight, it will drift all over the place. But if you feed it two things

(1) the full keyword dataset from NeuronWriter  

(2) the instruction to act like a content strategist, which produces a clean, extremely SEO-friendly outline. I usually get a full hierarchy of H2s and H3s, all loaded with the right topics.

At that point I take the outline and paste it back into NeuronWriter. The SEO score jumps immediately (from zero to something like 40–50) before writing even starts. That’s my signal that the structure is correct. No guesswork. No “writer’s instinct.” Just data telling us we’re on the right track.

Then I go back to AI for the full draft. I give it very specific instructions: use the outline, follow a friendly reading level, add internal link placeholders, keep paragraphs short, and include our company naturally where relevant. AI will generate the entire article in one go. It’s not perfect, but the hardest part is no longer blank-page writing—it’s editing.

The real improvement happens when I paste that long draft back into NeuronWriter. The score usually shoots up to the mid-70s or 80s because the coverage is so broad. The tool then highlights keywords we haven’t used yet, sections that need more depth, and terms competitors include that we’re missing. Fixing those is quick—just weave a couple of sentences in. It’s almost like topping up nutrition in a recipe.

The last step is removing the “AI shine.” AI loves long intros, unnecessary transitions, and bolding random sentences. I trim those out. I simplify the tone. And then I hand it off to our content manager, who brings the human side—experience, nuance, examples, and the voice that AI can’t mimic. Together we produce content that actually feels alive, not robotic.

Once everything feels right, I let AI generate the title tag and meta description. It’s good at producing 10–20 variations at once, and we pick the one that matches the style. After that, the article is pretty much ready to publish.

This workflow has become a good partnership model: the data comes from NeuronWriter, the structure comes from AI, the refinement comes from both the tool and human editing, and our content manager brings the personality into the final copy. My role is just orchestrating the process—feeding the right inputs, cleaning the outputs, and making sure everything stays consistent.

With the right combination of tools, data, and collaboration, even someone like me, who thinks more in workflows than in sentences, can help create content that ranks on Google.