AI Platforms & Models

Prompt Engineering Systems

When prompts have escaped into application code as string literals and nobody can say which version produced last week's behaviour.

Treating prompts as versioned, tested artifacts rather than strings pasted into code is what makes behaviour changeable deliberately. It also makes regressions visible, which matters because prompt changes can degrade one case while improving another.

The discipline is closer to configuration management than to writing, despite the name.

What the work includes

  • Prompts stored, versioned, and reviewed like other artifacts
  • Test cases so a change can be evaluated before it ships
  • Separation of prompt content from application logic
  • Traceability from an output back to the prompt version that produced it
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// Common Questions

Questions
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Common questions about Prompt Engineering Systems.

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Because they become untraceable. When a prompt is edited inline, nobody can say which version produced last month's output, compare two variants, or roll back a change that made things worse. Prompts behave like configuration and need the same handling.

Versioning, the ability to compare variants against the same inputs, a record of which version produced which output, and a way to change a prompt without shipping code. That last point matters most, since it decouples tuning from release cycles.

By evaluating it against a fixed set of representative inputs with agreed criteria, rather than by trying a few examples that come to mind. Ad-hoc testing reliably confirms whatever the author already believed.

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