Production Systems: Enterprise-Grade Prompt Engineering

Level 1: Ad-hoc Prompts
├── Individual developers crafting custom prompts
├── No standardization or reuse
├── Manual testing and debugging
└── Limited scalability

Level 2: Template Systems  
├── Reusable prompt templates
├── Basic version control
├── Simple testing frameworks
└── Team collaboration tools

Level 3: Managed Platforms
├── Centralized prompt libraries
├── Automated testing pipelines
├── Performance monitoring
└── A/B testing infrastructure

Level 4: Enterprise Orchestration
├── Multi-model routing
├── Intelligent fallbacks
├── Real-time optimization
├── Global governance
└── Compliance and auditing

interface PromptTemplate {
  id: string;
  name: string;
  description: string;
  category: string;
  version: string;
  author: string;
  tags: string[];
  template: string;
  variables: TemplateVariable[];
  examples: TemplateExample[];
  metadata: TemplateMetadata;
}

interface TemplateLibrary {
  // Core development templates
  development: {
    codeGeneration: PromptTemplate[];
    debugging: PromptTemplate[];
    testing: PromptTemplate[];
    documentation: PromptTemplate[];
  };
  
  // Business domain templates  
  domains: {
    ecommerce: PromptTemplate[];
    healthcare: PromptTemplate[];
    finance: PromptTemplate[];
    education: PromptTemplate[];
  };
  
  // Specialized function templates
  specialized: {
    dataAnalysis: PromptTemplate[];
    security: PromptTemplate[];
    performance: PromptTemplate[];
    architecture: PromptTemplate[];
  };
}

const crudApiTemplate: PromptTemplate = {
  id: 'crud-api-v2.1',
  name: 'CRUD API Generator',
  description: 'Generate complete CRUD API with validation and error handling',
  category: 'development.api',
  version: '2.1.0',
  author: 'platform-team',
  tags: ['api', 'crud', 'validation', 'enterprise'],
  template: `
Create a {framework} CRUD API for {entity} with:

REQUIREMENTS:
- RESTful endpoints: GET, POST, PUT, DELETE /{resource}
- Input validation using {validation_library}
- Error handling with proper HTTP status codes
- {database} integration with connection pooling
- API documentation with {docs_framework}
- Authentication using {auth_method}
- Rate limiting: {rate_limit} requests/minute
- Logging with request correlation IDs

SECURITY:
- SQL injection prevention
- XSS protection
- CORS configuration
- Input sanitization

PERFORMANCE:
- Response caching for GET requests
- Pagination for list endpoints
- Connection pooling
- Query optimization

Include comprehensive tests and deployment configuration.
  `,
  variables: [
    { name: 'framework', type: 'select', options: ['Express.js', 'FastAPI', 'Spring Boot'] },
    { name: 'entity', type: 'string', required: true },
    { name: 'resource', type: 'string', derived: 'pluralize(entity)' },
    { name: 'validation_library', type: 'string', default: 'Joi' },
    { name: 'database', type: 'select', options: ['PostgreSQL', 'MySQL', 'MongoDB'] },
    { name: 'docs_framework', type: 'string', default: 'OpenAPI/Swagger' },
    { name: 'auth_method', type: 'string', default: 'JWT Bearer tokens' },
    { name: 'rate_limit', type: 'number', default: 1000 }
  ],
  examples: [
    {
      input: { framework: 'Express.js', entity: 'User', database: 'PostgreSQL' },
      description: 'User management API with Express and PostgreSQL'
    }
  ],
  metadata: {
    estimatedTokens: 1200,
    complexity: 'high',
    executionTime: '45s',
    successRate: 0.94
  }
};

class EnterpriseTemplateEngine {
  private templates: Map<string, PromptTemplate>;
  private cache: Map<string, string>;
  private validator: TemplateValidator;
  
  constructor() {
    this.templates = new Map();
    this.cache = new Map();
    this.validator = new TemplateValidator();
  }
  
  async renderTemplate(
    templateId: string, 
    variables: Record<string, any>,
    options: RenderOptions = {}
  ): Promise<string> {
    const template = this.getTemplate(templateId);
    
    // Validate variables
    const validation = this.validator.validate(template, variables);
    if (!validation.isValid) {
      throw new ValidationError(validation.errors);
    }
    
    // Check cache first
    const cacheKey = this.generateCacheKey(templateId, variables);
    if (this.cache.has(cacheKey)) {
      return this.cache.get(cacheKey)!;
    }
    
    // Render template
    let rendered = template.template;
    
    // Process variables
    for (const [key, value] of Object.entries(variables)) {
      const placeholder = `{${key}}`;
      rendered = rendered.replace(new RegExp(placeholder, 'g'), value);
    }
    
    // Process derived variables
    rendered = this.processDerivedVariables(template, rendered, variables);
    
    // Apply optimizations
    if (options.optimize) {
      rendered = await this.optimizePrompt(rendered);
    }
    
    // Cache result
    this.cache.set(cacheKey, rendered);
    
    return rendered;
  }
  
  async optimizePrompt(prompt: string): Promise<string> {
    // Token optimization
    const compressed = this.compressTokens(prompt);
    
    // Structure optimization  
    const structured = this.optimizeStructure(compressed);
    
    // Performance validation
    const validated = await this.validatePerformance(structured);
    
    return validated;
  }
}

interface PromptVersion {
  version: string;        // e.g., "2.1.3"
  prompt: string;
  changelog: string;
  performance: PerformanceMetrics;
  compatibility: CompatibilityInfo;
  rollbackPlan: RollbackStrategy;
}

class PromptVersionManager {
  private versions: Map<string, PromptVersion[]>;
  private activeVersions: Map<string, string>;
  private migrations: Map<string, MigrationPlan>;
  
  async deployVersion(
    promptId: string, 
    newVersion: PromptVersion,
    deploymentStrategy: 'canary' | 'blue-green' | 'rolling'
  ): Promise<DeploymentResult> {
    
    // Pre-deployment validation
    const validation = await this.validateDeployment(promptId, newVersion);
    if (!validation.passed) {
      return { success: false, errors: validation.errors };
    }
    
    // Execute deployment strategy
    switch (deploymentStrategy) {
      case 'canary':
        return await this.canaryDeploy(promptId, newVersion);
      case 'blue-green':
        return await this.blueGreenDeploy(promptId, newVersion);
      case 'rolling':
        return await this.rollingDeploy(promptId, newVersion);
    }
  }
  
  async canaryDeploy(promptId: string, newVersion: PromptVersion): Promise<DeploymentResult> {
    // Deploy to 5% of traffic
    await this.routeTraffic(promptId, newVersion.version, 0.05);
    
    // Monitor for 1 hour
    const metrics = await this.monitorPerformance(promptId, '1h');
    
    // Evaluate success criteria
    if (metrics.errorRate < 0.01 && metrics.qualityScore > 0.9) {
      // Gradually increase traffic
      await this.gradualRollout(promptId, newVersion.version);
      return { success: true, strategy: 'canary', rolloutTime: '4h' };
    } else {
      // Rollback
      await this.rollback(promptId);
      return { success: false, reason: 'Metrics did not meet criteria' };
    }
  }
}

# .github/workflows/prompt-ci-cd.yml
name: Prompt CI/CD Pipeline

on:
  push:
    branches: [main]
    paths: ['prompts/**']
  pull_request:
    paths: ['prompts/**']

jobs:
  validate:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      
      - name: Validate Prompt Syntax
        run: |
          npm run validate:prompts
          
      - name: Run Prompt Tests  
        run: |
          npm run test:prompts
          
      - name: Performance Benchmarks
        run: |
          npm run benchmark:prompts
          
      - name: Security Scan
        run: |
          npm run security:prompts

  deploy-staging:
    needs: validate
    if: github.ref == 'refs/heads/main'
    runs-on: ubuntu-latest
    steps:
      - name: Deploy to Staging
        run: |
          kubectl apply -f k8s/staging/
          
      - name: Integration Tests
        run: |
          npm run test:integration
          
  deploy-production:
    needs: deploy-staging
    runs-on: ubuntu-latest
    steps:
      - name: Production Deployment
        run: |
          kubectl apply -f k8s/production/
          
      - name: Health Check
        run: |
          npm run healthcheck:production

class ResilientPromptExecutor {
  private fallbackChain: PromptStrategy[];
  private circuitBreaker: CircuitBreaker;
  private retryPolicy: RetryPolicy;
  
  async executeWithFallback(
    prompt: string,
    context: ExecutionContext
  ): Promise<ExecutionResult> {
    
    for (const strategy of this.fallbackChain) {
      try {
        // Check circuit breaker
        if (this.circuitBreaker.isOpen(strategy.id)) {
          continue;
        }
        
        // Execute with retry policy
        const result = await this.retryPolicy.execute(
          () => strategy.execute(prompt, context)
        );
        
        // Record success
        this.circuitBreaker.recordSuccess(strategy.id);
        
        return result;
        
      } catch (error) {
        // Record failure
        this.circuitBreaker.recordFailure(strategy.id);
        
        // Log error with context
        this.logger.error('Strategy failed', {
          strategyId: strategy.id,
          prompt: prompt.substring(0, 100),
          error: error.message,
          context
        });
        
        // Continue to next strategy
      }
    }
    
    // All strategies failed
    throw new AllStrategiesFailedError('No fallback strategy succeeded');
  }
}

// Fallback strategy examples
const fallbackStrategies: PromptStrategy[] = [
  new PrimaryModelStrategy('gpt-4'), 
  new FallbackModelStrategy('gpt-3.5-turbo'),
  new CachedResponseStrategy(),
  new DefaultResponseStrategy()
];

interface ErrorRecoveryPlan {
  errorType: string;
  recoveryActions: RecoveryAction[];
  escalationPath: EscalationLevel[];
  userCommunication: UserMessage;
}

class ErrorRecoveryOrchestrator {
  private recoveryPlans: Map<string, ErrorRecoveryPlan>;
  
  async handleError(error: Error, context: any): Promise<RecoveryResult> {
    const errorType = this.classifyError(error);
    const plan = this.recoveryPlans.get(errorType);
    
    if (!plan) {
      return this.executeDefaultRecovery(error, context);
    }
    
    // Execute recovery actions in sequence
    for (const action of plan.recoveryActions) {
      try {
        const result = await action.execute(error, context);
        if (result.success) {
          return result;
        }
      } catch (recoveryError) {
        this.logger.warn('Recovery action failed', {
          action: action.name,
          error: recoveryError.message
        });
      }
    }
    
    // Escalate if recovery failed
    return this.escalate(error, context, plan.escalationPath);
  }
}

// Error classification and recovery
const errorRecoveryPlans: ErrorRecoveryPlan[] = [
  {
    errorType: 'TokenLimitExceeded',
    recoveryActions: [
      new CompressPromptAction(),
      new SplitRequestAction(),
      new UseFallbackModelAction()
    ],
    escalationPath: ['team-lead', 'engineering-manager'],
    userCommunication: {
      message: 'Request is being processed with optimized parameters',
      showProgress: true
    }
  },
  {
    errorType: 'ModelUnavailable', 
    recoveryActions: [
      new UseFallbackModelAction(),
      new UseCachedResponseAction(),
      new QueueForLaterAction()
    ],
    escalationPath: ['on-call-engineer', 'infrastructure-team'],
    userCommunication: {
      message: 'Using backup system. Results may take longer than usual.',
      estimatedDelay: '30s'
    }
  }
];

class PromptObservabilityPlatform {
  private metricsCollector: MetricsCollector;
  private alertManager: AlertManager;
  private dashboard: Dashboard;
  
  async collectMetrics(execution: PromptExecution): Promise<void> {
    // Performance metrics
    await this.metricsCollector.record('prompt.execution.duration', {
      value: execution.duration,
      tags: { 
        promptId: execution.promptId,
        model: execution.model,
        success: execution.success 
      }
    });
    
    // Quality metrics
    await this.metricsCollector.record('prompt.output.quality', {
      value: execution.qualityScore,
      tags: { 
        promptId: execution.promptId,
        evaluator: 'automated' 
      }
    });
    
    // Cost metrics
    await this.metricsCollector.record('prompt.execution.cost', {
      value: execution.cost,
      tags: { 
        promptId: execution.promptId,
        tokenCount: execution.tokenCount 
      }
    });
    
    // Business metrics
    await this.metricsCollector.record('prompt.business.impact', {
      value: execution.businessValue,
      tags: { 
        feature: execution.feature,
        userId: execution.userId 
      }
    });
  }
  
  setupAlerts(): void {
    // Performance alerts
    this.alertManager.createAlert({
      name: 'High Prompt Latency',
      condition: 'avg(prompt.execution.duration) > 10000ms over 5min',
      severity: 'warning',
      channels: ['slack-engineering', 'pagerduty']
    });
    
    // Quality alerts
    this.alertManager.createAlert({
      name: 'Quality Degradation',
      condition: 'avg(prompt.output.quality) < 0.8 over 10min',
      severity: 'critical', 
      channels: ['slack-ai-team', 'email-leads']
    });
    
    // Cost alerts
    this.alertManager.createAlert({
      name: 'Budget Overrun',
      condition: 'sum(prompt.execution.cost) > monthly_budget * 0.9',
      severity: 'high',
      channels: ['slack-finance', 'email-management']
    });
  }
}

import { trace, context, propagation } from '@opentelemetry/api';

class DistributedPromptTracing {
  private tracer = trace.getTracer('prompt-engineering');
  
  async executeWithTracing(
    promptId: string,
    input: any,
    executor: PromptExecutor
  ): Promise<any> {
    
    return await this.tracer.startActiveSpan(`prompt-execution-${promptId}`, async (span) => {
      try {
        // Set span attributes
        span.setAttributes({
          'prompt.id': promptId,
          'prompt.input.length': JSON.stringify(input).length,
          'execution.timestamp': Date.now()
        });
        
        // Context preprocessing
        const preprocessed = await this.tracePreprocessing(input);
        
        // Template rendering
        const rendered = await this.traceTemplateRendering(promptId, preprocessed);
        
        // Model execution
        const result = await this.traceModelExecution(rendered);
        
        // Post-processing
        const processed = await this.tracePostProcessing(result);
        
        // Set result attributes
        span.setAttributes({
          'prompt.output.length': JSON.stringify(processed).length,
          'execution.success': true
        });
        
        return processed;
        
      } catch (error) {
        // Record error
        span.recordException(error);
        span.setStatus({ code: trace.SpanStatusCode.ERROR });
        throw error;
        
      } finally {
        span.end();
      }
    });
  }
  
  private async traceModelExecution(prompt: string): Promise<any> {
    return await this.tracer.startActiveSpan('model-execution', async (span) => {
      const startTime = Date.now();
      
      try {
        const result = await this.callModel(prompt);
        
        span.setAttributes({
          'model.tokens.input': result.usage.promptTokens,
          'model.tokens.output': result.usage.completionTokens,
          'model.cost': this.calculateCost(result.usage),
          'model.duration': Date.now() - startTime
        });
        
        return result;
      } finally {
        span.end();
      }
    });
  }
}

class PromptRouter {
  private routingStrategies: Map<string, RoutingStrategy>;
  private loadBalancer: LoadBalancer;
  private cache: DistributedCache;
  
  async route(request: PromptRequest): Promise<PromptResponse> {
    // Determine optimal routing strategy
    const strategy = this.selectStrategy(request);
    
    // Check cache first
    const cacheKey = this.generateCacheKey(request);
    const cached = await this.cache.get(cacheKey);
    if (cached && this.isCacheValid(cached, request)) {
      return cached;
    }
    
    // Route to optimal endpoint
    const endpoint = await strategy.selectEndpoint(request);
    const response = await this.executeRequest(endpoint, request);
    
    // Cache successful responses
    if (response.success && request.cacheable) {
      await this.cache.set(cacheKey, response, request.cacheTTL);
    }
    
    return response;
  }
  
  selectStrategy(request: PromptRequest): RoutingStrategy {
    if (request.priority === 'high') {
      return this.routingStrategies.get('performance-optimized');
    }
    
    if (request.budget === 'low') {
      return this.routingStrategies.get('cost-optimized');
    }
    
    if (request.complexity === 'high') {
      return this.routingStrategies.get('quality-optimized');
    }
    
    return this.routingStrategies.get('balanced');
  }
}

// Routing strategies
const routingStrategies = {
  'performance-optimized': new PerformanceOptimizedStrategy([
    new GPT4TurboEndpoint(),
    new ClaudeInstantEndpoint(),
    new LocalModelEndpoint()
  ]),
  
  'cost-optimized': new CostOptimizedStrategy([
    new GPT35TurboEndpoint(),
    new ClaudeHaikuEndpoint(), 
    new OpenSourceEndpoint()
  ]),
  
  'quality-optimized': new QualityOptimizedStrategy([
    new GPT4Endpoint(),
    new ClaudeOpusEndpoint(),
    new PalmEndpoint()
  ])
};

# kubernetes/prompt-service-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: prompt-service
spec:
  replicas: 3
  selector:
    matchLabels:
      app: prompt-service
  template:
    metadata:
      labels:
        app: prompt-service
    spec:
      containers:
      - name: prompt-service
        image: prompt-service:v2.1.0
        resources:
          requests:
            memory: "512Mi"
            cpu: "250m"
          limits:
            memory: "2Gi" 
            cpu: "1000m"
        env:
        - name: REDIS_URL
          valueFrom:
            secretKeyRef:
              name: redis-secret
              key: url
        - name: MODEL_ENDPOINTS
          valueFrom:
            configMapKeyRef:
              name: model-config
              key: endpoints
              
---
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: prompt-service-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: prompt-service
  minReplicas: 3
  maxReplicas: 50
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70
  - type: Resource
    resource:
      name: memory
      target:
        type: Utilization
        averageUtilization: 80
  behavior:
    scaleUp:
      stabilizationWindowSeconds: 60
      policies:
      - type: Percent
        value: 100
        periodSeconds: 15
    scaleDown:
      stabilizationWindowSeconds: 300
      policies:
      - type: Percent
        value: 10
        periodSeconds: 60

class PromptSecurityManager {
  private scanner: SecurityScanner;
  private classifier: DataClassifier;
  private sanitizer: InputSanitizer;
  
  async validatePrompt(prompt: string, context: SecurityContext): Promise<SecurityValidation> {
    // Scan for sensitive data
    const sensitiveData = await this.scanner.detectSensitiveData(prompt);
    if (sensitiveData.length > 0) {
      return {
        valid: false,
        violations: sensitiveData,
        recommendation: 'Remove or mask sensitive information'
      };
    }
    
    // Check for malicious patterns
    const maliciousPatterns = await this.scanner.detectMaliciousPatterns(prompt);
    if (maliciousPatterns.length > 0) {
      return {
        valid: false,
        violations: maliciousPatterns,
        recommendation: 'Prompt contains potential security risks'
      };
    }
    
    // Validate data classification
    const classification = await this.classifier.classify(prompt);
    if (!this.isAuthorized(context.user, classification)) {
      return {
        valid: false,
        violations: ['Insufficient permissions for data classification'],
        recommendation: 'Request appropriate access permissions'
      };
    }
    
    return { valid: true, violations: [], recommendation: null };
  }
  
  async sanitizeInput(input: any): Promise<any> {
    return this.sanitizer.sanitize(input, {
      removeHtml: true,
      removeScripts: true,
      validateJson: true,
      truncateLength: 10000
    });
  }
}

class PromptAuditSystem {
  private auditLog: AuditLogger;
  private complianceChecker: ComplianceChecker;
  
  async auditPromptExecution(execution: PromptExecution): Promise<void> {
    const auditEvent = {
      timestamp: new Date(),
      eventType: 'prompt-execution',
      userId: execution.userId,
      promptId: execution.promptId,
      dataClassification: execution.dataClassification,
      outcome: execution.success ? 'success' : 'failure',
      metadata: {
        tokenCount: execution.tokenCount,
        cost: execution.cost,
        duration: execution.duration
      }
    };
    
    // Log audit event
    await this.auditLog.log(auditEvent);
    
    // Check compliance
    const complianceResult = await this.complianceChecker.check(execution);
    if (!complianceResult.compliant) {
      await this.handleComplianceViolation(execution, complianceResult);
    }
  }
  
  async generateComplianceReport(period: string): Promise<ComplianceReport> {
    const events = await this.auditLog.query({ period });
    
    return {
      period,
      totalExecutions: events.length,
      sensitiveDataProcessed: events.filter(e => e.dataClassification === 'sensitive').length,
      complianceViolations: events.filter(e => e.complianceViolations).length,
      averageCost: this.calculateAverage(events, 'cost'),
      topUsers: this.getTopUsers(events),
      riskAssessment: await this.assessRisk(events)
    };
  }
}