Best Practices

Always include only the most relevant context for each interaction. Avoid dumping entire codebases or documents. Instead, carefully select the specific sections that matter for the task at hand.

Organize your prompts with clear sections: role definition, context, task description, output format, and constraints. This helps AI models parse and respond to your requests more effectively.

Treat your prompts as living documents. Collect feedback, analyze results, and refine your templates over time. Small adjustments can lead to significant improvements in output quality.

Include 2-3 high-quality examples in your prompts to show the AI exactly what you expect. This few-shot approach dramatically improves consistency and accuracy.

Be mindful of token limits. Prioritize the most important information, use summarization for lengthy content, and leverage ODIN's chunking features to maximize the value of every token.

Use version control for your prompt templates just like code. This allows you to track what works, roll back changes, and collaborate effectively with your team.

Test your prompts with various edge cases and input types. What works for one scenario may fail for another. Build a test suite for your critical prompts.

Create a library of proven prompt patterns and share them with your team. Document what works, what doesn't, and why. This accelerates learning and ensures consistency.