"Order is the sanity of the mind, the health of the body, the peace of the soul."
— Alexandra Stoddard
Once you start using AI every day for writing, planning, researching, or brainstorming, your digital life will multiply at light speed. One idea becomes five. Each chat spawns ten more. Before you know it, you have a pile of half-written outputs, unlabelled files, and a vague memory that ‘I swear I had a better version of this somewhere…’
This is a uniquely human systems problem. AI gives you infinite creative output, but without structure, that infinity quickly becomes a messy swamp. Most users rely on the search bar or scroll endlessly through old chats. But if you can’t find your best ideas, they might as well not exist at all.
Version control isn’t just for software engineers. It’s for anyone producing knowledge at scale. Think of version control as memory management. It’s how you guarantee your ideas survive the chaos of daily iteration.
If you can’t find it, you don’t have it.
When you introduce even a basic structure, your workflow gains three things:
1. Traceability. You always know which version is final.
2. Reusability. You can build upon older ideas instead of rewriting from scratch.
3. Clarity. Your mental load drops because everything has a proper place.
You stop being a collector of prompts and start being a curator of systems.
This is an extension of the previous article, providing a basic system to help you stay organised: a naming convention that keeps things consistent.
Prefix System:
A- = Active article or work in progress
R- = Research or resource
M- = Marketing or distribution
F- = Final output
REF- = Reference or permanent asset
Then add version suffixes when needed: _v1, _v2, _FINAL
Example: A-ChildrenIllustrationPlaybook_v2 → in progress;
F-ChildrenIllustrationPlaybook_FINAL → ready for export.
Apply this to all chats, files, and documents. The result? A clean, predictable naming pattern that lets you instantly know what’s current, and where to find it.
Once you’ve built your naming habit, take it one step further with a Master Index, an updated log of all your AI projects.
Columns: Title, Category, Chat Name, File Name, Date Updated, Notes.
Example entry:
001 | Version Control | AI Workflows | Final | F-VersionControl.docx | 10 Oct 2025 | Packaged for Blog
Why it works:
There’s an art to versioning. It should be designed to help you maintain control.
When you create order around your AI work, you make yourself future-proof. You can migrate between tools, like ChatGPT, Claude, and Gemini, and still have total continuity because your system lives outside the tool.
Version control isn’t about rigidity. It’s about clarity, momentum, and ownership. When everything has a label, a date, and a place, you stop being overwhelmed and start making progress that compounds.
Q: What’s the difference between AI version control and Git?
A: Git tracks code changes line by line. You’re tracking ideas and outputs.
Q: Should I save every version?
A: No. Keep milestones and discard redundant drafts.
Q: How often should I review my Master Index?
A: Every 2–4 weeks.
Q: Can I use AI to maintain the index?
A: Yes — paste your file directory and ask ChatGPT to format it into a table.
You can’t scale chaos. Version your ideas like a professional.
Start small: name your files with intent, build a Master Index, and create a rhythm of review. In less than an hour, you’ll turn your creative chaos into a repeatable system.
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