How my AI publishes a blog post — then checks the live page to confirm it actually went up

My AI's Blog Publishing Workflow

I've spent the last year building and refining my self-hosted AI system, which currently consists of 50 agents, including Atlas, Axiom, and Sentinel, all working together to manage over 20 real websites. In this post, I'll walk you through the process of how my AI publishes a blog post and then checks the live page to confirm it actually went up. This process involves several agents, each with a specific role, and relies on a combination of cron-scheduled Python scripts and API calls.

The Publishing Process

The publishing process starts with the content agent, Forge, which is responsible for generating the blog post content. Forge runs daily at 8am, and uses a combination of natural language processing and machine learning algorithms to generate high-quality content. Once the content is generated, it's passed to the overseer, Atlas, which reviews and edits the content to ensure it meets our quality standards. If the content is approved, Atlas triggers the publishing agent, Scout, which is responsible for publishing the post to the live website.

Technical Details

Scout uses the WordPress REST API to publish the post, which involves making a POST request to the API endpoint with the post content and metadata. This request is made using the `requests` library in Python, and the API credentials are stored securely in an environment variable. The API request includes the post title, content, categories, and tags, as well as any other relevant metadata. Once the post is published, Scout receives a response from the API, which includes the post ID and other details.

Confirming the Post is Live

After publishing the post, the SEO agent, Axiom, is triggered to check the live page and confirm that the post is indeed live. Axiom uses a combination of web scraping and API calls to verify that the post is visible on the live website. This involves making a GET request to the website, parsing the HTML response, and checking that the post title and content are present on the page. Axiom also checks the post's metadata, such as the categories and tags, to ensure they are correct.

Trade-offs and Limitations

While my AI system has been able to successfully publish and confirm hundreds of blog posts, there are still some trade-offs and limitations to consider. For example, the entire process relies on a stable internet connection, and if the connection is lost, the publishing process can fail. Additionally, the WordPress REST API has rate limits, which can limit the number of posts that can be published per hour. To mitigate these risks, I've implemented retries and fail-safes, such as storing the post content locally and retrying the API request if it fails.

Agent Roles and Responsibilities

Here is a summary of the agent roles and responsibilities involved in the publishing process:

• Forge (content agent): generates blog post content
• Atlas (overseer): reviews and edits content, triggers publishing agent
• Scout (publishing agent): publishes post to live website using WordPress REST API
• Axiom (SEO agent): checks live page to confirm post is live, verifies metadata
• Sentinel (monitoring agent): monitors system for errors, sends alerts if issues arise

Conclusion and Future Work

In conclusion, my self-hosted AI system has been able to successfully publish and confirm hundreds of blog posts, using a combination of cron-scheduled Python scripts, API calls, and web scraping. While there are still some trade-offs and limitations to consider, the system has been reliable and efficient. Future work includes expanding the system to support more websites, and integrating additional agents to handle tasks such as social media posting and email marketing. With a self-hosted AI system, the possibilities are endless, and I'm excited to see where this technology takes me.