I love cool tools—even when they’re impractical. Sometimes I obsess over creating something just because the building process itself is rewarding. Recently, I built a system aimed at personal productivity, only to realize later it was overkill. But building it was genuinely fun, and I learned a lot! While exploration is enjoyable (and occasionally distracting), I’m increasingly drawn toward practicality. With so many subscription-based services available today, having numerous unused tools can quickly become costly. Now, more than ever, I’m motivated to build things that offer real value and solve actual problems. With that said, here’s something I created recently that is genuinely useful—and simple enough that you can try it out right away. It’s an automation workflow designed to monitor your organization’s GitHub Copilot seat usage. It automatically removes seats from users who are inactive based on customizable thresholds, saving you money. Additionally, it notifies users via Slack, giving them the opportunity to reinstate their subscription if they still need it.
GitHub repo.
Try it in AutoKitteh.
Scenario
Imagine your company’s policy grants every employee automatic access to GitHub Copilot. Over time, the cost of all these subscriptions can really add up. Even with an opt-in model, seats often remain assigned to people who aren’t actively using them. You could, of course, monitor this manually—but that would be a tedious and error-prone task. ## Solution
Solution
Automate this process with a simple Python script.
But wait, why am I even reading this blog post?
If you’re thinking, “I can easily write a Python script myself—why bother with another tool?” you’re right. The Python script itself is straightforward, and you’re welcome to copy it from here to deploy and manage on your own.
However, without AutoKitteh, you’ll have to handle:
- Deployment and maintenance
- Integrations with Slack and GitHub
- Secret management
- Server infrastructure
- Reliability and error handling
Individually, none of these steps are impossible—but collectively, they can require considerable effort and resources. AutoKitteh simplifies this significantly: all you have to do is write your script, set some basic configuration, and hit “deploy.” Your workflow runs seamlessly in the background, backed by Temporal, managing subscriptions automatically based on user activity.
And since the code is already written, you can easily try it yourself right now on your own instance of AutoKitteh.
Closing Thoughts
To be transparent, I do work at AutoKitteh. But I’m also genuinely excited about how this product can help people benefit from technology without requiring them to become infrastructure experts or seasoned tech veterans. Just like AI has opened doors to more accessible coding, I believe AutoKitteh simplifies deploying robust workflows, empowering more people to build practical solutions quickly.
And one more thing—AutoKitteh is open source, so you don’t even have to use our cloud platform.
If you prefer, you can run it entirely yourself. If you’re curious or would like help getting started, reach out—I’d be glad to chat and support you along the way.
Building with Autokitteh
One of the best things about using Autokitteh was how easy it was to set everything up. I didn’t have to worry about API complexities, server management, or authentication headaches. The platform handled all of that.
- Integrations: Connecting Gmail and ChatGPT took just a few clicks.
- Workflow Automation: Defining invoice detection and data extraction logic was straightforward.
- Deployment: With a single click, my project was live and running in the cloud.
It was like having my own AI-powered assistant handle invoices for me without writing complex backend code.
In this manner, a research agent can execute multi-stage investigations over extended periods, wait for human validation at critical decision points, and survive infrastructure disruptions – all while keeping its accumulated knowledge intact. The agent’s core logic remains focused on research methodology rather than state management, making the code more maintainable and the research process more reliable.
Autokitteh Durability
One of the key advantages of using Autokitteh is its durability. The system is designed to handle continuous invoice tracking throughout the month. Instead of relying solely on one-time processing, it allows users to request status updates at any point. This makes it perfect for generating a monthly summary while keeping track of invoices in real time. Whether you need to check progress mid-month or compile a final report, Autokitteh ensures seamless and durable automation.
Overcoming Challenges
While the system worked well, it wasn’t perfect. Here are some of the challenges I faced:
- AI Accuracy: ChatGPT occasionally misclassified emails, either failing to detect an invoice or extracting incorrect details. I had to fine-tune my prompts and add validation checks.
- Email Polling Delays: Since emails are processed at intervals, invoices aren’t always detected instantly. However, adjusting the polling frequency helped improve performance.
- Attachment Handling: Some invoices were embedded as images rather than PDFs or text. I resolved this by converting them into AI-readable files for accurate processing.
Despite these challenges, the system can save hours of manual work every week, making invoice management much more efficient.
Final Thoughts
To be transparent, I do work at AutoKitteh. But I’m also genuinely excited about how this product can help people benefit from technology without requiring them to become infrastructure experts or seasoned tech veterans. Just like AI has opened doors to more accessible coding, I believe AutoKitteh simplifies deploying robust workflows, empowering more people to build practical solutions quickly.
And one more thing—AutoKitteh is open source, so you don’t even have to use our cloud platform. If you prefer, you can run it entirely yourself.
If you’re curious or would like help getting started, reach out—I’d be glad to chat and support you along the way.
