**Author**: [Arthur Andreyev](/content/news/author/arthur-andreyev/index.html)

**Date**: Jun 24, 2026

There is little point in pretending that marketers do not use AI to create content anymore. Most of us do. The important question is not whether AI was involved, but how it was used.

The same model can produce a generic article that disappears among hundreds of similar pages, or help create a useful piece of content that ranks, attracts links, and brings consistent organic traffic. The difference is rarely the model itself. It is the research, context, instructions, examples, editorial decisions, and fact-checking that surround it.

The article below was created with the help of AI. Since publication, it has generated **almost 70K clicks from Google Search over 16 months** and continues to attract traffic consistently.

It was not produced with one prompt, and I did not publish the first draft ChatGPT gave me. I used AI throughout the process, but I controlled the topic, argument, sources, structure, examples, product context, and final editing.

In this article, I will show the workflow I use to turn research and editorial input into AI-assisted content that is accurate, original, useful, and capable of performing in search long after publication.

## Contents

- [Before the workflow: I set up the editorial context](/content/news/ai-content-creation.html#Before-the-workflow-I-set-up-the-editorial-context1/index.html)
- [Step 1. I decide how much of the process AI should handle](/content/news/ai-content-creation.html#Step-1-I-decide-how-much-of-the-process-AI-should-handle3/index.html)
- [Step 2. I validate the topic before I commit to it](/content/news/ai-content-creation.html#Step-2-I-validate-the-topic-before-I-commit-to-it7/index.html)
- [Step 3. I define the article’s position before I start writing](/content/news/ai-content-creation.html#Step-3-I-define-the-articles-position-before-I-start-writing9/index.html)
- [Step 4. I build a source pack](/content/news/ai-content-creation.html#Step-4-I-build-a-source-pack10/index.html)
- [Step 5. I write a decision brief before asking for an outline](/content/news/ai-content-creation.html#Step-5-I-write-a-decision-brief-before-asking-for-an-outline14/index.html)
- [Step 6. I create and approve the outline before drafting](/content/news/ai-content-creation.html#Step-6-I-create-and-approve-the-outline-before-drafting15/index.html)
- [Step 7. I write the article one section at a time](/content/news/ai-content-creation.html#Step-7-I-write-the-article-one-section-at-a-time16/index.html)
- [Step 8. I assemble the article and ask ChatGPT to critique it](/content/news/ai-content-creation.html#Step-8-I-assemble-the-article-and-ask-ChatGPT-to-critique-it18/index.html)
- [Step 9. I make the article mine](/content/news/ai-content-creation.html#Step-9-I-make-the-article-mine20/index.html)
- [Step 10. I run a final claim audit](/content/news/ai-content-creation.html#Step-10-I-run-a-final-claim-audit21/index.html)
- [Step 11. I optimize the finished article for search](/content/news/ai-content-creation.html#Step-11-I-optimize-the-finished-article-for-search23/index.html)
- [Step 12. I build internal links in both directions](/content/news/ai-content-creation.html#Step-12-I-build-internal-links-in-both-directions24/index.html)
- [Step 13. I monitor what happens after publication](/content/news/ai-content-creation.html#Step-13-I-monitor-what-happens-after-publication25/index.html)
- [After the workflow: I decide what not to automate](/content/news/ai-content-creation.html#After-the-workflow-I-decide-what-not-to-automate26/index.html)
- [Final thoughts](/content/news/ai-content-creation.html#Final-thoughts27/index.html)

## Before the workflow: I set up the editorial context

Before I start working on any individual article, I set up the context ChatGPT will use throughout the entire content process.

I keep our editorial instructions, reference files, product documentation, and examples of published content inside a [dedicated ChatGPT project](https://help.openai.com/en/articles/10169521-projects-in-chatgpt). This means I do not have to explain our audience, products, tone, and writing standards every time I open a new chat.

The project contains the information that stays consistent across articles: who we write for, how technical the content should be, how we describe our products, and which phrases or writing habits we avoid.

Examples are especially important. Telling ChatGPT to sound “professional and engaging” is too vague. Showing it introductions, paragraphs, and product descriptions that match our style gives it something concrete to follow.

## Step 1. I decide how much of the process AI should handle

I do not use the same AI workflow for every article.

Some topics are relatively safe to delegate. Others need much tighter control. Before I begin, I decide how much responsibility AI can realistically take on without weakening the final result.

I usually think about topics in three categories.

### Low-risk topics

AI can do more of the work when the topic is stable, well documented, and easy for me to verify.

This includes things like:
- explaining an established SEO concept;
- updating an existing guide;
- comparing documented product features;
- creating a basic how-to article.

In these cases, AI can help with research, structure, drafting, and editing because the facts are relatively easy to check and the topic does not depend on a strong personal position.

### Medium-risk topics

I use AI more carefully when the topic is changing quickly or requires interpretation.

Examples include:
- Google Search updates;
- [AI Overviews](/content/news/search-generative-experience.html);
- changes in how LLMs surface brands;
- industry predictions;
- product comparisons;
- articles based on conflicting studies.

For this type of content, AI can still speed up research and drafting, but I verify the sources more closely and make sure the article clearly separates facts from my own conclusions.

### High-risk topics

There are also topics where I would never let AI lead the process.

This includes:
- original research;
- unpublished company data;
- legal, medical, or financial claims;
- interviews;
- sensitive product comparisons;
- breaking news.

AI can still help organize notes or improve wording, but the argument, evidence, and final conclusions need much stronger human control.

**The rule I use is simple:** I trust AI most when I already know enough about the subject to recognize a bad answer.

If I cannot confidently evaluate the output, I should _not_ be delegating the core thinking to the model.

## Step 2. I validate the topic before I commit to it

Having a good idea for an article does not automatically mean that people are searching for it.

Before I spend time researching and writing, I check whether there is real demand around the topic, how people describe the problem, and what type of content currently appears in the search results.

I use [Rank Tracker](/content/rank-tracker/download.html) for this stage. I normally begin with a broad phrase and then explore related searches, questions, keyword combinations, and terms that already bring traffic to competing websites.

At this point, I am not trying to collect the largest possible list of keywords. I want to understand the search landscape behind the article.

I look at:
- the different phrases people use to describe the same problem;
- [search volume](/content/news/what-is-search-volume.html) and [keyword difficulty](/content/news/keyword-difficulty-video-tutorial.html);
- related questions that may need to be answered;
- [keywords competitors rank for](/content/news/how-to-do-keyword-research.html#Keyword-Gap11/index.html) that we do not;
- whether one topic contains several different search intents;
- the types of pages already ranking in the top results.

## Step 3. I define the article’s position before I start writing

A keyword tells me what people are searching for. It does not tell me what the article should contribute.

That is why I define the article’s position before I start collecting too much information or asking AI to produce an outline.

For example, these two briefs may target the same topic:
- How to create content with AI
- Why high-quality AI content depends more on editorial decisions than on prompting

The first describes a subject. The second gives the article a point of view.

Without that point of view, AI usually defaults to the safest possible version of the topic. It produces a reasonable introduction, a list of familiar steps, and a conclusion that nobody could strongly disagree with.

Before I move forward, I write down three things:
1. What do I believe about this topic?
2. What should the reader understand or do differently after reading?
3. What will this article add that is missing from the pages already ranking?

For this article, my position is simple: The quality of AI-assisted content depends less on the model itself and more on the decisions made around it.

That position affects the entire workflow.

## Step 4. I build a source pack

Once the topic and the article’s position are clear, I start collecting the material that will support the argument.

I do not begin by asking ChatGPT to “research the topic and write an article.” That gives the model too much control over which sources matter, which claims deserve attention, and how confidently they should be presented.

Instead, I build a source pack.

A source pack is a controlled collection of documents, data, examples, and notes that I want the article to rely on. It becomes the factual foundation for the draft.

### Primary sources

These are the sources I trust most for factual claims:
- official documentation;
- original research;
- company announcements;
- product documentation;
- direct interviews;
- our own internal data.

### Strong secondary sources

These help me understand the topic, compare interpretations, and find additional context:
- specialist industry publications;
- analysis from experienced practitioners;
- reputable news organizations;
- detailed case studies;
- independent research.

### Discovery sources

These are useful for finding questions, opinions, and areas of disagreement:
- competing articles;
- Reddit threads;
- LinkedIn posts;
- newsletters;
- community discussions.

## Step 5. I write a decision brief before asking for an outline

Once the research is complete, I turn it into a short working brief.

I do not need a twenty-page document. But I do need more than a target keyword and a working title.

The brief explains what the article is trying to achieve, who it is for, what position it should take, and which evidence it can use. It also records the decisions I do not want AI to make on its own.

## Step 6. I create and approve the outline before drafting

Once the brief is ready, I ask ChatGPT to create a detailed outline.

I never move straight from the brief to a full article. The outline is where I check whether the structure supports the main argument, whether the sections appear in the right order, and whether anything important is missing.

## Step 7. I write the article one section at a time

Once the outline is approved, I do not ask ChatGPT to generate the entire article in one go. Instead, I work through the outline one section at a time.

## Step 8. I assemble the article and ask ChatGPT to critique it

Once all the sections are ready, I combine them into one complete article and ask ChatGPT to review the full article before I begin the final edit.

## Step 9. I make the article mine

Even after the structural review, the article is not ready to publish. This is where I read the complete text myself and make sure it reflects my actual experience, opinions, and standards.

## Step 10. I run a final claim audit

Before I optimize or publish the article, I check every important factual claim one more time.

## Step 11. I optimize the finished article for search

I only return to on-page optimization once the argument, evidence, and final wording are in place.

## Step 12. I build internal links in both directions

Before publishing, I connect the new article to the rest of the website.

## Step 13. I monitor what happens after publication

Publishing the article is not the end of the workflow.

## After the workflow: I decide what not to automate

The more capable AI becomes, the easier it is to let it make decisions that should still belong to the author.

## Final thoughts

The value of AI-assisted content is not measured by how quickly it was produced, but by what it achieves after publication.