Production Prompt Best Practices

Engineering practices for moving prompts from experiments into production: versioning, error handling, cost control, safety, and operations.

Version management

Store prompts in Git, use semantic versions, separate development/staging/production, and require review before rollout.

Error handling and fallbacks

Validate output, retry format failures, switch models when needed, and return a safe fallback when all generation paths fail.

Cost optimization

Shorten prompts, cache repeated outputs, route simple tasks to cheaper models, and batch non-real-time jobs.

Safety and compliance

Limit input length, isolate user input, detect prompt injection, filter sensitive output, rate-limit usage, and keep audit logs with privacy safeguards.