The day my AI found and fixed a website build that had been broken for weeks

Discovery and Initial Assessment

I'll never forget the day my AI system, which I've dubbed Ollama, found and fixed a website build that had been broken for weeks. As a solo founder managing 20+ real websites, I rely heavily on my self-hosted AI system to keep everything running smoothly. The system consists of 50 agents, each with its own unique role, scheduled to run using Python's cron scheduler. The agents are powered by a single RTX 4050 6GB laptop, which provides more than enough processing power for my needs. On this particular day, the overseer agent, Atlas, detected an issue with one of the websites and alerted me to the problem.

Investigation and Diagnosis

Upon investigation, I found that the website's build process had been failing due to a complex issue with the website's dependencies. The error messages were cryptic, and I had been putting off dealing with the issue due to its complexity. However, Atlas had detected the problem and was insisting that I take a closer look. I decided to let the system try to fix the issue, so I activated the Forge agent, which is responsible for troubleshooting and fixing technical issues. Forge quickly got to work, running a series of tests and analyzing the website's code.

Resolution and Verification

After several hours of running tests and analyzing code, Forge finally identified the root cause of the issue: a compatibility problem between two dependencies. The agent then proceeded to update the dependencies and re-run the build process. To my amazement, the build process completed successfully, and the website was back online. I was impressed by the speed and accuracy of the resolution, especially considering that I had been struggling with the issue for weeks. The Sentinel agent, which is responsible for monitoring the system's performance, verified that the fix was stable and that the website was running smoothly.

Post-Mortem Analysis

After the issue was resolved, I decided to take a closer look at how the system had handled the problem. I reviewed the logs and found that the Axiom agent, which is responsible for analyzing system performance, had been monitoring the website's build process and had detected the issue early on. However, due to the complexity of the problem, Axiom had escalated the issue to Atlas, which then alerted me to the problem. I was impressed by the way the agents had worked together to identify and fix the issue. The Scout agent, which is responsible for researching and providing information, had also played a crucial role in providing Forge with the necessary information to fix the issue.

Lessons Learned and Trade-Offs

The experience taught me several valuable lessons about the importance of having a robust AI system in place. One of the key takeaways was the importance of having a diverse set of agents, each with its own unique role. This allows the system to approach problems from different angles and increases the chances of finding a solution. However, having 50 agents also means that there are trade-offs to be made. For example, the more agents I have, the more resources are required to run them. Currently, my RTX 4050 6GB laptop is capable of handling the workload, but I may need to upgrade in the future as the system grows. Some of the key benefits and trade-offs of my AI system include:

• Improved accuracy and speed of issue detection and resolution
• Increased resource requirements (e.g., processing power, memory)
• Ability to manage multiple websites and tasks simultaneously
• Complexity of managing and maintaining a large number of agents
• Potential for agent conflicts or overlapping responsibilities
• Cost savings from automated troubleshooting and resolution

Conclusion and Future Directions

In conclusion, my experience with the AI system has been incredibly positive, and I'm excited to see how it will continue to evolve and improve. The fact that the system was able to detect and fix a complex issue that had been plaguing me for weeks is a testament to its capabilities. As I continue to develop and refine the system, I'm looking forward to exploring new applications and use cases. One area I'm particularly interested in is using the system to automate content creation and optimization. With the help of the content agent and the SEO agent, I believe I can create high-quality, optimized content more efficiently and effectively than ever before. The future of AI and automation is exciting, and I'm thrilled to be a part of it.