Git (workflow versioning)
A version control system used to track changes to workflow configurations and code. PURIST stores all workflow definitions in Git every change is reviewed, tested, and can be rolled back to any prior version in seconds.
Expert insight
Storing workflow definitions (exported as JSON) in a git repository, even for a visual no-code platform, gives you something the platform's own UI usually doesn't: a real diff between versions, a way to see exactly what changed before a workflow broke, and a rollback path that doesn't depend on someone remembering what the previous version looked like.
In a real workflow
Workflow JSON files are stored in Git, so every change has an author, a date and a reason.
Common mistakes
- Committing credentials.
- Never reviewing changes before merging.
Complexity level
Requires some familiarity with automation concepts.
Related terms
Version control (workflows)
Saving snapshots of workflow configurations so you can roll back after a bad dep…
CI/CD (Continuous Integration/Delivery)
Automated pipelines that test and deploy code changes. For automation teams, CI/…
Deployment pipeline
The automated sequence of steps that moves a workflow from development → staging…
See it in action
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More in Architecture
Keep exploring
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Lint / linting
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Load balancing
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Go deeper
Guides that cover Git
Anatomy Claude skill: what it is, how to install it, and 28 live examples
The open-source Anatomy skill turns an idea into an interactive isometric machine. What it makes, how to install and use it in Claude Code, and what we learned building 28 live figures.
Enterprise Workflow Automation: The Complete Guide for 2026
Enterprise workflow automation is no longer optional for mid-market companies competing against software-native businesses. This guide covers the tools, frameworks, and implementation roadmap that actually work at scale.
AI Pharmacovigilance Workflows: Validated, Auditable, Explainable, and Secure
Pharmacovigilance AI workflows must meet FDA 21 CFR Part 11, EMA ICHQ10, and GxP validation requirements. This guide covers the full architecture for compliant AI automation: audit trails, explainability, validation documentation, and n8n plus Claude implementation.