Best Practices

Follow these best practices to create effective, efficient, and maintainable Logic AI workflows.

Design Principles

Clear User Goals

  • Define Success Metrics: Establish specific, measurable goals for your workflow
  • User-Centered Design: Start by understanding your users' needs and pain points
  • Progressive Disclosure: Present information and options gradually to avoid overwhelming users
  • Consistent Patterns: Use similar interaction patterns throughout your workflow
  • Clear Feedback: Provide immediate feedback on user actions and system status

Logical Architecture

  • Modular Design: Break complex workflows into smaller, reusable components
  • Clean Data Flow: Establish clear paths for data to flow through your workflow
  • Separation of Concerns: Keep different functional aspects separate and well-defined
  • Minimal Complexity: Use the simplest solution that meets requirements
  • Scalable Structure: Design for future expansion from the beginning

GPT Optimization

Effective Prompting

  • Clear Instructions: Be specific about the exact output format and content you need
  • Context Enrichment: Provide relevant context to help the model understand the task
  • Example-Based Learning: Include examples of desired outputs when possible
  • Role Assignment: Define a specific role for the GPT to adopt (e.g., "You are a financial analyst")
  • Iteration Refinement: Build prompts incrementally, testing and refining as you go
Example of an optimized prompt:

You are a customer service specialist for a software company.
Your task is to:
1. Identify the main issue in the customer's message
2. Determine if it's a technical problem, billing question, or feature request
3. Provide a helpful, empathetic response (100 words max)
4. Include one relevant help documentation link if applicable

Customer message:
{user_input}

Parameter Tuning

  • Temperature Setting: Lower (0.2-0.5) for factual/consistent outputs, higher (0.7-0.9) for creative content
  • Max Tokens: Set appropriate limits to control response length and costs
  • Top-p Sampling: Adjust for diversity of responses (lower for more focused outputs)
  • Frequency/Presence Penalties: Use to reduce repetition in longer outputs
  • Stop Sequences: Define to control where the model stops generating text

Performance Optimization

  • Chain of Thought: Break complex reasoning into smaller, sequential steps
  • Batch Processing: Group similar requests when processing multiple items
  • Caching: Store and reuse common responses for repeated queries
  • Request Throttling: Implement rate limiting to manage API costs
  • Response Validation: Add logic to verify that responses meet expected criteria

Workflow Efficiency

Input Validation

  • Data Type Verification: Validate input formats before processing
  • Required Field Checks: Ensure all necessary information is provided
  • Reasonable Constraints: Set min/max values for numerical inputs
  • Pattern Matching: Use regex for structured inputs like emails or phone numbers
  • Helpful Error Messages: Provide clear guidance when validation fails

Error Handling

  • Graceful Degradation: Ensure the workflow continues to function even if parts fail
  • Meaningful Error Messages: Help users understand and fix problems
  • Fallback Options: Provide alternative paths when primary methods fail
  • Retry Logic: Automatically attempt to recover from temporary failures
  • Error Logging: Record issues for troubleshooting and improvement

Performance Considerations

  • Minimize API Calls: Reduce external service requests to improve speed and reduce costs
  • Parallel Processing: Run independent operations simultaneously when possible
  • Resource Monitoring: Track token usage, processing time, and other metrics
  • Caching Strategy: Store frequently accessed data for faster retrieval
  • Optimization Testing: Regularly test and refine performance under different conditions

Security and Compliance

Data Protection

  • Minimize Data Collection: Only gather information that's necessary for functionality
  • Secure Storage: Protect sensitive information using encryption and access controls
  • Data Sanitization: Clean inputs to prevent injection attacks
  • PII Handling: Follow best practices for personally identifiable information
  • Retention Policies: Define when and how to delete user data

Access Control

  • Principle of Least Privilege: Grant minimal permissions needed for functionality
  • Role-Based Access: Assign permissions based on user roles
  • Workflow Visibility: Control who can view, edit, and deploy workflows
  • Authentication Requirements: Implement appropriate login security
  • Activity Logging: Track who does what for audit purposes

Testing Strategies

Comprehensive Testing

  • Unit Testing: Verify individual components work correctly
  • Integration Testing: Ensure components work together properly
  • End-to-End Testing: Test the complete workflow from start to finish
  • Edge Case Testing: Try unusual or extreme inputs
  • Load Testing: Verify performance under high usage

User Experience Testing

  • User Feedback Collection: Gather input from actual users
  • A/B Testing: Compare different versions to see which performs better
  • Usability Studies: Observe how users interact with your workflow
  • Accessibility Verification: Ensure the workflow is usable by people with disabilities
  • Cross-Platform Testing: Verify functionality across different devices and browsers

Documentation and Maintenance

Comprehensive Documentation

  • Workflow Overview: Provide a high-level description and purpose
  • Component Documentation: Explain how each part works and connects
  • Configuration Guide: Detail all configurable settings
  • Troubleshooting Section: Include common issues and solutions
  • Change Log: Track modifications and updates

Sustainable Maintenance

  • Version Control: Use proper versioning for tracking changes
  • Regular Reviews: Schedule periodic evaluation of workflow performance
  • Update Planning: Anticipate model or API changes that might affect functionality
  • Performance Monitoring: Track metrics to identify degradation
  • Feedback Loop: Continuously incorporate user feedback into improvements

Next Steps

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