How I built a fully automated blog using AI: A step-by-step guide

The dream of a blog that runs itself is pretty tempting, right? Imagine a site that finds topics, writes articles, and hits "publish" all on its own while you're off doing well, anything else. It's the ultimate content marketing fantasy: a traffic machine on autopilot.

A lot of people are trying to make this happen by piecing together their own systems with various no-code tools. It sounds like a great idea, but once you dig in, you have to ask if it's worth the effort. Is the content any good? Will it actually show up on Google?

I went down this rabbit hole myself, and this post is all about what I found. We'll look at two ways to automate a blog. First, the popular DIY method that's more complicated than it looks. Then, I'll show you a much simpler, all-in-one alternative. Tools like the eesel AI blog writer are designed to avoid the usual headaches and give you content that's ready to go, not just a blob of text.

What is a fully automated AI blog?

First off, a "fully automated AI blog" isn't just about connecting ChatGPT to your WordPress site and calling it a day. A real automated system manages the whole content process from start to finish, without you needing to jump in constantly.

Here's what that actually involves:

1. Sourcing: The system finds relevant topics and keywords for new articles on its own.
2. Generation: It takes a keyword and turns it into a complete, structured article, not just a huge block of text.
3. Enrichment: It adds all the things that make a blog post worth reading and help it rank, like headings, meta descriptions, images, videos, and social proof.
4. Publication: The final article gets pushed directly to your CMS (like WordPress) as a draft or a live post.

The goal isn't just speed. It's about creating a system that can scale and produce good content consistently. The web is already drowning in what people are calling "dead internet ai slop", and you don't want to contribute to that.

any human reader will immediately spot this as AI and move on.

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The common DIY method for blog automation

The most common way people try to automate their blog is by daisy-chaining a bunch of different services. It's a classic no-code project, connecting apps to build a custom content pipeline. Let's walk through this popular, but potentially complex, approach.

The typical no-code tool stack

If you browse online forums or follow video guides, you'll see the same set of tools pop up again and again for a DIY setup. Most of them follow a similar recipe.

• Content Database: This is usually something simple like a Google Sheet where you dump your blog ideas or target keywords.
• Automation Hub: This is the engine that makes everything run. A tool like Make.com or Activepieces acts as the central coordinator, handling the workflow and moving data between the other apps.
• AI Model: To do the actual writing, you need to call an AI writer's API. Most people use OpenAI's GPT models, though some might use Anthropic's Claude.
• Publisher: You need an integration with your CMS, typically WordPress, to take the generated text and turn it into a post.
• Notifier: Lastly, a simple Gmail or Slack integration is often tacked on at the end to send a notification when a new draft is ready.

A step-by-step workflow example

So, how do all these parts work together? Here’s a quick overview of what a typical automation workflow looks like in a tool like Make.com.

1. Trigger: The process starts when you add a new row to your Google Sheet. This row has the blog topic or keyword.
2. Generate Title: The automation tool sends that idea to the OpenAI API with a prompt like, "Generate a catchy, SEO-friendly title for a blog post about [your idea]."
3. Generate Body: The tool then takes the new title and the original idea and makes another API call. This prompt is more involved, asking the AI to write the full article.
4. Publish Post: The title and body text are then sent to your WordPress site to create a new post, which is usually saved as a draft.
5. Send Notification: An email is automatically sent through Gmail to let you know a new AI-generated draft is ready for you to look at.

Challenges of the DIY approach

This all sounds neat, and if you like to tinker, it can be a fun project. But if your goal is to produce content that actually helps your business, this method presents several challenges that can become complex to manage.

• Generic, robotic content: A primary challenge is content quality. Without some serious prompt engineering, the text you get back often feels soulless and has a "cookie-cutter" vibe.
  

  They have that AI feel to them (you know what I mean, when you read something and go ‘ah, this is AI’)

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  It has no personality, which can be less engaging for readers and may not align with search engine guidelines for quality content. This type of content may face challenges in ranking because it can fail to meet Google's E-E-A-T (experience, expertise, authoritativeness, and trustworthiness) guidelines.
• Produces text, not assets: These workflows only give you raw text. That's it. This approach typically requires manual effort to find or create images, infographics, tables, and videos, which are all the things that make a blog post engaging. The output is often unformatted text, which requires further work to become a complete blog post.
• Lacks deep SEO and AEO: The generated text may lack the necessary structure, such as H2s and H3s, internal links, meta descriptions, and other elements needed for good SEO. It's also not optimized for AI Answer Engines (AEO), so it's unlikely to get picked up by Google’s AI Overviews.
• Complex and brittle setup: Connecting multiple services is a technical task, and the final workflow is sensitive to changes. As you can see in community forums, if one service in the chain updates its API or has an outage, the workflow can be disrupted. This can lead to significant time spent on maintenance and troubleshooting.
• Unpredictable and hidden costs: While many of these tools have free plans, the API calls to your AI model can get expensive. A new model like GPT-4o costs $5.00 per 1M input tokens and $15.00 per 1M output tokens. Every article you generate costs money, and the price can swing wildly. Plus, all your testing and tweaking also uses up tokens, so you can't even experiment for free.

A streamlined workflow with the eesel AI blog writer

After running into all the problems with the DIY method, I looked for a more integrated solution. An alternative is to use a single platform designed for this purpose. The eesel AI blog writer is a modern tool that takes that entire complicated, multi-step process and boils it down to one platform.

Simplifying the process

Instead of messing around with APIs, triggers, and prompts, eesel AI makes the whole thing incredibly simple.

1. Enter a keyword or topic for your blog post.
2. Give it your website URL so the AI can learn your brand's voice and context.
3. Generate a complete, publish-ready blog post.

That's all. You go from a keyword to a finished article without ever touching the technical stuff happening in the background.

How eesel AI addresses key automation challenges

The real advantage of a dedicated platform is how it directly addresses every problem of the DIY approach. It's not just about being easier; it's about getting better results.

Results and pricing

This isn't just theory. We used the eesel AI blog writer to grow our own company blog from 700 to 750,000 daily impressions in just 3 months. We did it by publishing over 1,000 high-quality, optimized blog posts with the tool. It's been thoroughly tested in the real world.

The pricing is also straightforward. The plan is $99 for 50 complete blog posts. No hidden fees or token counting, just a flat rate for a finished product.

Best of all, it's completely free to try. You can generate your first article for free to evaluate the output.

To see a real-world example of how these automated systems can be set up and the potential results they can drive, the video below offers a detailed walkthrough of building an AI blogging system from scratch.

This video explains how to build a fully automated blog using AI and automation to generate over $30,000 per year.

Key takeaways on building an automated blog

When it comes to building a fully automated blog, you have two clear options. You can take the DIY route, which offers a high degree of customization but can require significant technical maintenance and effort to produce high-ranking content.

Alternatively, an integrated platform can streamline the process.

The choice depends on your goals: whether you prefer to build and manage a custom workflow or use a tool that handles the technical aspects, allowing more focus on content strategy. A tool like the eesel AI blog writer is built to handle all the technical headaches for you, so you can focus on what matters.

For those looking for an all-in-one solution, a dedicated platform can help you publish optimized content more efficiently. Generate your first blog post for free and see what a truly automated content engine can do.