The world of AI can become quite chaotic.
You'll invest significant mental effort navigating problem spaces to solve various challenges.
Generative AI produces varying results with each run, but by documenting your steps and sequence in real time, you create a reliable path for replication or modification later.
Most consumer AI tools retain a record of your interactions, but for token based systems or agents, they won't preserve your work. It's worthwhile to store that documentation temporarily, for several reasons:
- Audit trail for challenges: If someone questions your process, you have a clear record of your actions and decisions.
- Reuse for similar problems: When facing a repeat issue, you can reference past work and adapt it, avoiding redundant effort.
- Fresh context capture: Documenting in the moment ensures accuracy, clarity, and allows faster iteration without later reconstruction.
- Onboarding and collaboration: Share insights with newcomers or less AI-savvy team members, providing them a direct guide to your methods.
- Flexibility for context switching: If interrupted, a well-documented thread lets you pause and resume seamlessly, ideal for juggling multiple projects.
- Personal reflection: Like a journal, it tracks your thought process, showing progress and skill growth over time.
Conclusion
In the fast paced chaos of AI development, documenting as you build isn't just best practice it's a competitive edge. It makes your work replicable, keeps your thinking organised, and aligns your team. Above all, it lets you advance to new challenges without revisiting old ground. In a landscape where speed and adaptability prevail, a real time record of your process becomes an invaluable asset. Build it alongside your creations, and your future self will be grateful.