directus-task-management/stories/6.4.story.md

Story 6.4: Create Prompt Engineering System

Story Information

• Epic/Task: Task 6 - Develop AI Integration Layer
• Story Number: 6.4
• Title: Create Prompt Engineering System
• Status: Ready
• Complexity: Medium
• Priority: Medium
• Dependencies: Tasks 6.1, 6.3 (6.1 completed, 6.3 draft)

Story Statement

As the Directus Task Management system, I need a sophisticated prompt engineering system that manages prompt templates, optimizes prompts for different AI models, enables dynamic prompt composition, and provides A/B testing capabilities so that AI interactions are consistent, effective, and continuously improving.

Acceptance Criteria

1. Prompt template system supports variables and conditional logic
2. Template versioning tracks changes and performance metrics
3. Dynamic prompt composition handles complex multi-part prompts
4. Model-specific optimization for GPT-4, Claude, and other models
5. A/B testing framework measures prompt effectiveness
6. Prompt library includes 20+ pre-built templates for common tasks
7. Template validation ensures proper structure and syntax
8. Performance metrics track token usage and response quality
9. Template inheritance enables prompt composition and reuse
10. Unit tests achieve 80% coverage for prompt components

Dev Notes

Architecture Context References

• [Source: Story 6.1] - OpenAI and LangChain integration established
• [Source: Story 6.3] - Context management provides dynamic data
• [Source: architecture.md#AI Integration] - Prompt requirements

Previous Story Insights

• GPT-4-turbo configuration in place
• LangChain prompt templates partially implemented
• Token tracking helps optimize prompt length
• Caching can store successful prompt patterns

Prompt Engineering Architecture

System Components:

interface PromptEngineeringSystem {
  // Template management
  templateRegistry: TemplateRegistryService;
  templateEngine: TemplateEngineService;
  
  // Optimization
  promptOptimizer: PromptOptimizationService;
  modelAdapter: ModelSpecificAdapterService;
  
  // Testing and metrics
  abTestingEngine: ABTestingService;
  metricsCollector: PromptMetricsService;
  
  // Composition
  promptComposer: DynamicComposerService;
  chainBuilder: PromptChainBuilderService;
}

Template Categories:

• Task Creation Templates
• Query Resolution Templates
• Summarization Templates
• Classification Templates
• Extraction Templates
• Conversation Templates

File Locations

• Prompt Services: src/services/prompts/ - Prompt engineering services
• Templates: src/services/prompts/templates/ - Template definitions
• Optimizers: src/services/prompts/optimizers/ - Optimization logic
• Tests: tests/services/prompts/ - Prompt service tests

Tasks / Subtasks

Task 1: Set up Prompt Engineering Infrastructure (AC: 1)

• Create src/services/prompts/prompt-engineering.service.ts
• Define prompt interfaces and types
• Set up template configuration system
• Implement base template parser
• Add prompt validation utilities

Task 2: Build Template Registry System (AC: 1, 6, 9)

• Create src/services/prompts/template-registry.service.ts
• Implement template storage and retrieval
• Add template categorization
• Create template inheritance system
• Build template search functionality

Task 3: Implement Template Engine (AC: 1, 3, 7)

• Create src/services/prompts/template-engine.service.ts
• Add variable substitution system
• Implement conditional logic processing
• Create template composition functions
• Add template validation and sanitization

Task 4: Develop Model-Specific Optimizers (AC: 4)

• Create src/services/prompts/optimizers/gpt-optimizer.service.ts
• Create src/services/prompts/optimizers/claude-optimizer.service.ts
• Implement token optimization strategies
• Add model-specific formatting
• Create fallback mechanisms

Task 5: Build Dynamic Prompt Composer (AC: 3)

• Create src/services/prompts/composers/dynamic-composer.service.ts
• Implement multi-part prompt assembly
• Add context injection system
• Create prompt chaining logic
• Implement priority-based composition

Task 6: Create Pre-built Template Library (AC: 6)

• Create task creation templates
• Add summarization templates
• Build classification templates
• Create extraction templates
• Implement conversation templates

Task 7: Implement Template Versioning (AC: 2)

• Create src/services/prompts/versioning/template-version.service.ts
• Add version tracking system
• Implement rollback functionality
• Create performance tracking per version
• Add migration utilities

Task 8: Build A/B Testing Framework (AC: 5)

• Create src/services/prompts/testing/ab-testing.service.ts
• Implement test configuration system
• Add result collection and analysis
• Create statistical significance testing
• Build automated winner selection

Task 9: Implement Metrics Collection (AC: 8)

• Create src/services/prompts/metrics/prompt-metrics.service.ts
• Track token usage per template
• Measure response quality scores
• Add latency tracking
• Create cost analysis tools

Task 10: Create API Endpoints

• Add GET /api/prompts/templates
• Add POST /api/prompts/generate
• Add PUT /api/prompts/templates/:id
• Add POST /api/prompts/test
• Implement proper validation

Task 11: Write Tests (AC: 10)

• Create unit tests for template engine
• Add tests for prompt optimizers
• Test A/B testing framework
• Validate template library
• Achieve 80% coverage

Task 12: Documentation

• Create prompt engineering guide
• Document template syntax
• Add optimization best practices
• Create template examples
• Write troubleshooting guide

Dev Agent Record

To be filled by implementing agent

File List

Created:

Modified:

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Story created by: Bob (Scrum Master) Date: 2025-08-12