Hey folks! I'm currently utilizing tools like Visual Studio Code with Codex and Gemini 3 Flash to help streamline my sysadmin duties, particularly when it comes to debugging and managing repetitive tasks through SSH on a Proxmox cluster. I'm looking to enhance how I log and structure the information these tools generate. My goal is to create a comprehensive knowledge base that allows me to track commands, document changes, and revisit past solutions for future use. Ideally, this should be centralized or synchronized across multiple nodes or clusters for easy access. I'm curious about how others are managing their AI integration in workflows:
- What methods are you using to log or version your interactions with AI tools?
- Is Git, structured logging, or something else part of your setup?
- Any recommend tools or frameworks for this purpose? Thanks in advance!
3 Answers
Honestly, I'm pretty hesitant about letting AI into my workflow beyond maybe auto-generating a PowerShell function. Even then, I put a lot of effort into testing and properly commenting the code myself. I prefer to keep control of my process and make sure I understand everything I'm executing.
Definitely make sure you're reviewing any code AI generates before running it. Blindly executing anything—especially automated code—can lead to significant issues down the line. I always comment every script I write, explaining each section to ensure clarity. I use GitHub for my scripts and track changes with Jira to maintain a formal record of all changes, ensuring nothing goes live without adequate documentation.
You might want to have AI generate your infrastructure-as-code (IaC) scripts and then create documentation directly from that. You can track changes through Git, and that way, every update is logged for accountability.
Totally agree on the importance of documentation. I always feel safer when there’s a ticket system in place—I wouldn't implement any changes without proper requests and rollback plans.