Back up AI prompts, LLM artifacts, and workflows
Preserve prompt versions, model references, retrieval inputs, and evaluation cases without confusing credentials with service credits.
Read the 6-minute guideAI workflows
AI Insta Backups
Preserve the workflow behind the result.
An AI project may depend on prompts, model references, source documents, tool definitions, and evaluation cases. Save those pieces as a coherent release rather than collecting unrelated output files. Define what useful recovery looks like before deciding which artifacts to keep and how to test them.
What to preserve
- Prompt templates, variables, tool contracts, and application revision.
- Model references or permitted model files and loading requirements.
- Approved source documents, evaluation cases, and acceptance criteria.
Your starting workflow
Choose one important task and create a release manifest. Record the inputs and settings you control, separate sensitive examples from public code, and identify any hosted dependency you cannot export. Preserve authorized access through a protected recovery procedure.
Test the recovered copy
Rebuild the release in a clean environment and run the representative tests. Use sandboxed tools so the drill cannot send real messages or change production records. Record any replacement dependency and assess its behavior explicitly.
What should I save first?
Start with the prompts, input structure, model reference, and a small acceptance test for one valuable task. Add source data and tool definitions as the inventory reveals them. Preserve enough context to assess the recovered behavior.
From Insta Backups Lab
Put the plan into practice.