XML-style structured prompts
Using XML-like tags to organize prompt components improves clarity and helps AI models parse your requirements.Basic structure
Multi-section prompts
For complex tasks with multiple phases:Step-by-step decomposition
Breaking complex tasks into explicit steps ensures thorough, sequential execution.Sequential task structure
Template-based prompts
Reusable templates ensure consistency across similar tasks.Code review template
API design template
Documentation template
Constraint-based prompting
Explicitly defining constraints produces outputs that meet specific requirements.Strict constraint format
Conditional logic in prompts
Guide the AI to make decisions based on specified criteria.Chain-of-thought prompting
Encourage the AI to show its reasoning process for better results.1
Explicit reasoning request
Add phrases that trigger step-by-step thinking:
2
Self-critique prompts
Comparison and analysis structures
For evaluating options systematically:Decision matrix format
Persona-based structured prompts
Assign specific roles for domain expertise:Combining techniques
The most effective prompts often combine multiple structuring techniques:Best practices for structured prompts
Saving and reusing structures
1
Use custom instructions
Save frequently used structures in custom instructions for automatic inclusion.
2
Create specialized assistants
Build assistants with embedded structured prompting for specific use cases.
3
Maintain a prompt library
Keep a collection of effective structured prompts for different task types.
Next steps
Few-shot learning
Enhance structured prompts with examples
Custom instructions
Make structured prompts persistent
Create assistants
Build assistants with structured behaviors
Token management
Optimize structured prompts for token efficiency

