Streamlining Blogging with Automation: Integrating GitHub, ChatGPT, and Postgres via Zapier

Faster time to market with powerful AI workflows

ByOscar Dyremyhr
~ 4 min read

In the ever-evolving digital landscape, bloggers and content creators are constantly seeking innovative ways to streamline their workflows. Automation stands out as a powerful tool, simplifying repetitive tasks and enhancing productivity. In this article, I’ll share how I transformed my blogging process using an ingenious automation flow that integrates GitHub issues, ChatGPT, and a Postgres database (via Supabase), all orchestrated through Zapier.

The Genesis: Idea to Implementation

The inception of this automation flow began with a simple idea: to leverage technology to make the process of creating and publishing blog posts more efficient. The goal was to automate the creation of a new blog post in my database whenever a GitHub issue was created and subsequently processed using ChatGPT.

The Zap 1 in action:

Zapier Automation

Step 1: Harnessing GitHub Issues as a Starting Point

Every great blog post starts with an idea. For me, these ideas begin as GitHub issues. I found GitHub issues to be an excellent way to organize and track blog post ideas. They are easy to create, can be tagged and categorized, and allow for collaborative input.

Step 2: ChatGPT – The Creative Assistant

Once an issue is created, ChatGPT comes into play. This AI-driven language model, developed by OpenAI, is a game-changer. It assists in fleshing out the blog post, providing a draft based on the initial idea. This integration significantly reduces the time spent on the initial draft and offers a unique perspective, thanks to its AI capabilities.

Step 3: Storing in Postgres via Supabase

After ChatGPT creates the draft, the next step is to store it. For this, I chose a Postgres database, managed through Supabase - an open-source Firebase alternative. Supabase offers a user-friendly interface and robust features, making it an excellent choice for managing my blog’s backend.

The Role of Zapier: The Automation Maestro

The glue that binds all these components together is Zapier. This online automation tool connects your favorite apps and services, automating workflows without the need for manual intervention. Here’s how Zapier makes the magic happen:

  • Trigger: The process begins when a new GitHub issue is created.
  • Action: Zapier then triggers ChatGPT to start working on the draft.
  • Result: Once the draft is ready, Zapier pushes this data to the Postgres database in Supabase.

The Impact: Efficiency and Creativity Unleashed

The results of this automation flow have been remarkable:

  • Time-Saving: What used to take hours, now takes minutes. The time from idea to draft has been drastically reduced.
  • Consistency: Each blog post follows a consistent format and structure, ensuring quality and coherence.
  • Flexibility: Ideas can be added to GitHub from anywhere, and the automated process takes care of the rest.

Future Enhancements and Considerations

While this automation flow works seamlessly, there’s always room for improvement:

  • Refining AI Outputs: Integrating further AI tools for grammar and style checks could enhance the quality of the drafts.
  • Feedback Loop: Implementing a system to incorporate feedback into the draft before finalizing it.

Conclusion: Embracing Automation in Blogging

This automation flow demonstrates the power of integrating various technologies to create a seamless and efficient blogging process. It’s a testament to how automation, when thoughtfully implemented, can significantly enhance productivity and creativity.

As we continue to explore the capabilities of AI and automation tools, the potential to revolutionize content creation is immense. By sharing this journey, I hope to inspire fellow bloggers and creators to explore the possibilities of automation in their creative processes.

In fact this very post was initially drafted using this very idea! The title along with the context of the issue is passed to the OpenAI (GPT-V.3.5-Turbo API) prior to sending the reponse to my backend. See here:

Github Issue


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