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+---
+allowed-tools: Read, Write, Edit, MultiEdit, Bash
+description: Enable cutting-edge experimental AI SDK features safely
+argument-hint: "[beta|experimental|research|custom]"
+---
+
+## Enable Experimental AI SDK Features
+
+Configure and safely enable cutting-edge AI SDK experimental features: $ARGUMENTS
+
+### Current Experimental Status
+
+Existing experimental features: !`grep -r "experimental\|beta\|alpha" . --include="*.ts" --include="*.json" | head -5`
+
+Feature flags: !`grep -r "ENABLE_\|FLAG_" .env* 2>/dev/null | head -3 || echo "No feature flags found"`
+
+Advanced configurations: !`grep -r "streamingTimeouts\|thinkingMode\|toolCallStreaming" . --include="*.ts" | head -5`
+
+### Experimental Feature Categories
+
+**Beta Features**: Stable experimental features ready for production testing
+**Experimental**: Cutting-edge features in active development
+**Research**: Bleeding-edge research features for experimentation
+**Custom**: Custom experimental implementations and modifications
+
+### Your Task
+
+1. **Analyze experimental feature landscape** and identify safe options
+2. **Implement feature flag system** for controlled rollouts
+3. **Configure experimental AI SDK options** with proper safeguards
+4. **Set up A/B testing framework** for feature validation
+5. **Add monitoring and telemetry** for experimental features
+6. **Create fallback mechanisms** for experimental feature failures
+7. **Implement gradual rollout strategy** with user controls
+8. **Add comprehensive testing** for experimental features
+
+### Implementation Requirements
+
+#### Feature Flag System
+
+- Environment-based feature control
+- User-level feature toggles
+- Percentage-based rollouts
+- Real-time feature flag updates
+- Fallback mechanisms for failures
+
+#### Safety Measures
+
+- Automatic fallback to stable features
+- Error isolation and reporting
+- Performance impact monitoring
+- User experience protection
+- Data integrity guarantees
+
+#### Experimental Configuration
+
+- Advanced streaming options
+- Cutting-edge model features
+- Research-level AI capabilities
+- Custom provider integrations
+- Performance optimizations
+
+### Expected Deliverables
+
+1. **Feature flag system** with environment and user controls
+2. **Experimental AI SDK configurations** with safety controls
+3. **A/B testing framework** for feature validation
+4. **Monitoring and telemetry** for experimental features
+5. **Fallback mechanisms** for reliability
+6. **Documentation** for experimental feature usage
+7. **Testing suite** covering experimental scenarios
+
+### Feature Flag Infrastructure
+
+#### Core Feature Flag System
+
+```typescript
+// lib/experimental/feature-flags.ts
+interface FeatureFlag {
+  name: string;
+  enabled: boolean;
+  rolloutPercentage: number;
+  conditions?: {
+    userIds?: string[];
+    environments?: string[];
+    regions?: string[];
+    custom?: (context: any) => boolean;
+  };
+  metadata?: {
+    description: string;
+    added: string;
+    owner: string;
+    stableDate?: string;
+  };
+}
+
+export class ExperimentalFeatureManager {
+  private static instance: ExperimentalFeatureManager;
+  private flags: Map<string, FeatureFlag> = new Map();
+  private context: any = {};
+
+  static getInstance(): ExperimentalFeatureManager {
+    if (!ExperimentalFeatureManager.instance) {
+      ExperimentalFeatureManager.instance = new ExperimentalFeatureManager();
+    }
+    return ExperimentalFeatureManager.instance;
+  }
+
+  async initialize(context: any = {}) {
+    this.context = context;
+    await this.loadFeatureFlags();
+  }
+
+  private async loadFeatureFlags() {
+    // Load from environment variables
+    const envFlags = this.loadFromEnvironment();
+    
+    // Load from external service (optional)
+    const remoteFlags = await this.loadFromRemoteService();
+    
+    // Merge flags with priority: remote > environment > defaults
+    const allFlags = { ...this.getDefaultFlags(), ...envFlags, ...remoteFlags };
+    
+    Object.entries(allFlags).forEach(([name, flag]) => {
+      this.flags.set(name, flag as FeatureFlag);
+    });
+  }
+
+  private getDefaultFlags(): Record<string, FeatureFlag> {
+    return {
+      'reasoning-models': {
+        name: 'reasoning-models',
+        enabled: false,
+        rolloutPercentage: 0,
+        metadata: {
+          description: 'Enable O1, O3-mini, and DeepSeek reasoning models',
+          added: '2024-12-01',
+          owner: 'ai-team',
+        },
+      },
+      'computer-use': {
+        name: 'computer-use',
+        enabled: false,
+        rolloutPercentage: 0,
+        conditions: {
+          environments: ['development', 'staging'],
+        },
+        metadata: {
+          description: 'Enable Claude 3.5 Sonnet computer use capabilities',
+          added: '2024-12-01',
+          owner: 'automation-team',
+        },
+      },
+      'generative-ui': {
+        name: 'generative-ui',
+        enabled: true,
+        rolloutPercentage: 100,
+        metadata: {
+          description: 'Enable streamUI for dynamic component generation',
+          added: '2024-11-01',
+          owner: 'ui-team',
+        },
+      },
+      'advanced-streaming': {
+        name: 'advanced-streaming',
+        enabled: true,
+        rolloutPercentage: 50,
+        metadata: {
+          description: 'Advanced streaming patterns with multi-step and waitUntil',
+          added: '2024-11-15',
+          owner: 'streaming-team',
+        },
+      },
+      'edge-optimization': {
+        name: 'edge-optimization',
+        enabled: true,
+        rolloutPercentage: 75,
+        conditions: {
+          environments: ['production', 'staging'],
+        },
+        metadata: {
+          description: 'Vercel Edge Runtime optimizations',
+          added: '2024-10-01',
+          owner: 'performance-team',
+        },
+      },
+      'natural-language-sql': {
+        name: 'natural-language-sql',
+        enabled: false,
+        rolloutPercentage: 25,
+        conditions: {
+          custom: (context) => context.hasDatabase === true,
+        },
+        metadata: {
+          description: 'Natural language to SQL conversion',
+          added: '2024-12-10',
+          owner: 'data-team',
+        },
+      },
+    };
+  }
+
+  private loadFromEnvironment(): Record<string, Partial<FeatureFlag>> {
+    const flags: Record<string, Partial<FeatureFlag>> = {};
+    
+    // Load from environment variables
+    if (process.env.ENABLE_REASONING_MODELS === 'true') {
+      flags['reasoning-models'] = { enabled: true, rolloutPercentage: 100 };
+    }
+    
+    if (process.env.ENABLE_COMPUTER_USE === 'true') {
+      flags['computer-use'] = { enabled: true, rolloutPercentage: 100 };
+    }
+    
+    if (process.env.ENABLE_GENERATIVE_UI === 'true') {
+      flags['generative-ui'] = { enabled: true, rolloutPercentage: 100 };
+    }
+    
+    if (process.env.ENABLE_ADVANCED_STREAMING === 'true') {
+      flags['advanced-streaming'] = { enabled: true, rolloutPercentage: 100 };
+    }
+    
+    if (process.env.ENABLE_EDGE_OPTIMIZATION === 'true') {
+      flags['edge-optimization'] = { enabled: true, rolloutPercentage: 100 };
+    }
+    
+    return flags;
+  }
+
+  private async loadFromRemoteService(): Promise<Record<string, Partial<FeatureFlag>>> {
+    // Optional: Load from external feature flag service
+    try {
+      if (process.env.FEATURE_FLAG_SERVICE_URL) {
+        const response = await fetch(process.env.FEATURE_FLAG_SERVICE_URL, {
+          headers: {
+            'Authorization': `Bearer ${process.env.FEATURE_FLAG_API_KEY}`,
+          },
+        });
+        
+        if (response.ok) {
+          return await response.json();
+        }
+      }
+    } catch (error) {
+      console.warn('Failed to load remote feature flags:', error);
+    }
+    
+    return {};
+  }
+
+  isEnabled(flagName: string, userId?: string): boolean {
+    const flag = this.flags.get(flagName);
+    if (!flag) return false;
+
+    // Check basic enabled status
+    if (!flag.enabled) return false;
+
+    // Check conditions
+    if (flag.conditions) {
+      if (flag.conditions.userIds && userId) {
+        if (!flag.conditions.userIds.includes(userId)) return false;
+      }
+      
+      if (flag.conditions.environments) {
+        const env = process.env.NODE_ENV || 'development';
+        if (!flag.conditions.environments.includes(env)) return false;
+      }
+      
+      if (flag.conditions.regions) {
+        const region = process.env.VERCEL_REGION || 'local';
+        if (!flag.conditions.regions.includes(region)) return false;
+      }
+      
+      if (flag.conditions.custom) {
+        if (!flag.conditions.custom(this.context)) return false;
+      }
+    }
+
+    // Check rollout percentage
+    if (flag.rolloutPercentage < 100) {
+      const hash = this.getUserHash(userId || 'anonymous', flagName);
+      if (hash % 100 >= flag.rolloutPercentage) return false;
+    }
+
+    return true;
+  }
+
+  private getUserHash(userId: string, flagName: string): number {
+    // Simple hash function for consistent user bucketing
+    let hash = 0;
+    const str = `${userId}-${flagName}`;
+    for (let i = 0; i < str.length; i++) {
+      const char = str.charCodeAt(i);
+      hash = ((hash << 5) - hash) + char;
+      hash = hash & hash; // Convert to 32-bit integer
+    }
+    return Math.abs(hash);
+  }
+
+  getAllFlags(): Map<string, FeatureFlag> {
+    return new Map(this.flags);
+  }
+
+  updateFlag(flagName: string, updates: Partial<FeatureFlag>) {
+    const existing = this.flags.get(flagName);
+    if (existing) {
+      this.flags.set(flagName, { ...existing, ...updates });
+    }
+  }
+
+  async trackFeatureUsage(flagName: string, userId?: string, metadata?: any) {
+    const usage = {
+      flag: flagName,
+      userId,
+      timestamp: Date.now(),
+      context: this.context,
+      metadata,
+    };
+
+    // Send to analytics service
+    await this.sendUsageToAnalytics(usage);
+  }
+
+  private async sendUsageToAnalytics(usage: any) {
+    try {
+      if (process.env.ANALYTICS_ENDPOINT) {
+        await fetch(process.env.ANALYTICS_ENDPOINT, {
+          method: 'POST',
+          headers: { 'Content-Type': 'application/json' },
+          body: JSON.stringify(usage),
+        });
+      }
+    } catch (error) {
+      console.warn('Failed to send feature usage analytics:', error);
+    }
+  }
+}
+
+// Singleton instance
+export const featureFlags = ExperimentalFeatureManager.getInstance();
+```
+
+#### Experimental AI SDK Wrapper
+
+```typescript
+// lib/experimental/ai-sdk-experimental.ts
+import { streamText, generateText, streamUI, generateObject } from 'ai';
+import { featureFlags } from './feature-flags';
+
+export interface ExperimentalOptions {
+  userId?: string;
+  fallbackOnError?: boolean;
+  trackUsage?: boolean;
+}
+
+export class ExperimentalAISDK {
+  
+  static async streamText(config: any, options: ExperimentalOptions = {}) {
+    const { userId, fallbackOnError = true, trackUsage = true } = options;
+    
+    // Apply experimental features based on flags
+    const experimentalConfig = await this.applyExperimentalFeatures(config, userId);
+    
+    try {
+      const result = streamText(experimentalConfig);
+      
+      if (trackUsage) {
+        await this.trackExperimentalUsage(experimentalConfig, userId);
+      }
+      
+      return result;
+    } catch (error) {
+      if (fallbackOnError) {
+        console.warn('Experimental feature failed, falling back to stable:', error);
+        return streamText(config); // Fallback to original config
+      }
+      throw error;
+    }
+  }
+
+  static async generateText(config: any, options: ExperimentalOptions = {}) {
+    const { userId, fallbackOnError = true, trackUsage = true } = options;
+    
+    const experimentalConfig = await this.applyExperimentalFeatures(config, userId);
+    
+    try {
+      const result = await generateText(experimentalConfig);
+      
+      if (trackUsage) {
+        await this.trackExperimentalUsage(experimentalConfig, userId);
+      }
+      
+      return result;
+    } catch (error) {
+      if (fallbackOnError) {
+        console.warn('Experimental feature failed, falling back to stable:', error);
+        return generateText(config);
+      }
+      throw error;
+    }
+  }
+
+  static async streamUI(config: any, options: ExperimentalOptions = {}) {
+    const { userId, fallbackOnError = true, trackUsage = true } = options;
+    
+    if (!featureFlags.isEnabled('generative-ui', userId)) {
+      throw new Error('Generative UI is not enabled for this user');
+    }
+    
+    try {
+      const result = streamUI(config);
+      
+      if (trackUsage) {
+        await featureFlags.trackFeatureUsage('generative-ui', userId, {
+          toolCount: Object.keys(config.tools || {}).length,
+        });
+      }
+      
+      return result;
+    } catch (error) {
+      if (fallbackOnError) {
+        // Fallback to regular text streaming
+        console.warn('StreamUI failed, falling back to streamText:', error);
+        return streamText({
+          ...config,
+          text: ({ content }) => content, // Simple text output
+        });
+      }
+      throw error;
+    }
+  }
+
+  private static async applyExperimentalFeatures(config: any, userId?: string) {
+    const experimentalConfig = { ...config };
+
+    // Advanced streaming features
+    if (featureFlags.isEnabled('advanced-streaming', userId)) {
+      experimentalConfig.experimental_streamingTimeouts = {
+        streamingTimeout: 45000,
+        completeTimeout: 120000,
+        keepAliveInterval: 5000,
+      };
+      
+      experimentalConfig.experimental_toolCallStreaming = true;
+      experimentalConfig.experimental_continueSteps = true;
+      
+      await featureFlags.trackFeatureUsage('advanced-streaming', userId);
+    }
+
+    // Reasoning models
+    if (featureFlags.isEnabled('reasoning-models', userId)) {
+      if (config.model?.includes?.('o1') || config.model?.includes?.('reasoner')) {
+        experimentalConfig.experimental_reasoning = true;
+        experimentalConfig.experimental_thinkingMode = 'visible';
+        experimentalConfig.experimental_thinkingTokens = true;
+        
+        await featureFlags.trackFeatureUsage('reasoning-models', userId);
+      }
+    }
+
+    // Edge optimizations
+    if (featureFlags.isEnabled('edge-optimization', userId)) {
+      experimentalConfig.experimental_edgeOptimization = {
+        enableCompression: true,
+        enableKeepAlive: true,
+        connectionPooling: true,
+      };
+      
+      experimentalConfig.experimental_memoryManagement = {
+        maxTokensInMemory: 25000,
+        enableGarbageCollection: true,
+        cleanupInterval: 30000,
+      };
+      
+      await featureFlags.trackFeatureUsage('edge-optimization', userId);
+    }
+
+    return experimentalConfig;
+  }
+
+  private static async trackExperimentalUsage(config: any, userId?: string) {
+    const experimentalFeatures = [];
+    
+    if (config.experimental_streamingTimeouts) {
+      experimentalFeatures.push('advanced-streaming');
+    }
+    
+    if (config.experimental_reasoning) {
+      experimentalFeatures.push('reasoning-models');
+    }
+    
+    if (config.experimental_edgeOptimization) {
+      experimentalFeatures.push('edge-optimization');
+    }
+
+    for (const feature of experimentalFeatures) {
+      await featureFlags.trackFeatureUsage(feature, userId, {
+        configuration: Object.keys(config).filter(k => k.startsWith('experimental_')),
+      });
+    }
+  }
+}
+```
+
+### A/B Testing Framework
+
+#### Experiment Configuration
+
+```typescript
+// lib/experimental/ab-testing.ts
+export interface Experiment {
+  id: string;
+  name: string;
+  description: string;
+  status: 'draft' | 'running' | 'paused' | 'completed';
+  variants: {
+    id: string;
+    name: string;
+    percentage: number;
+    config: any;
+  }[];
+  targetAudience?: {
+    userIds?: string[];
+    percentage?: number;
+    conditions?: any;
+  };
+  metrics: string[];
+  startDate: Date;
+  endDate?: Date;
+}
+
+export class ExperimentManager {
+  private static instance: ExperimentManager;
+  private experiments: Map<string, Experiment> = new Map();
+
+  static getInstance(): ExperimentManager {
+    if (!ExperimentManager.instance) {
+      ExperimentManager.instance = new ExperimentManager();
+    }
+    return ExperimentManager.instance;
+  }
+
+  async initialize() {
+    await this.loadExperiments();
+  }
+
+  private async loadExperiments() {
+    // Load experiments from configuration
+    const defaultExperiments: Experiment[] = [
+      {
+        id: 'reasoning-vs-standard',
+        name: 'Reasoning Models vs Standard Models',
+        description: 'Compare performance of O1 reasoning models vs standard models',
+        status: 'running',
+        variants: [
+          { id: 'control', name: 'Standard Model', percentage: 50, config: { useReasoning: false } },
+          { id: 'treatment', name: 'Reasoning Model', percentage: 50, config: { useReasoning: true } },
+        ],
+        targetAudience: { percentage: 10 },
+        metrics: ['response_quality', 'latency', 'cost', 'user_satisfaction'],
+        startDate: new Date('2024-12-01'),
+        endDate: new Date('2024-12-31'),
+      },
+      {
+        id: 'streaming-optimization',
+        name: 'Advanced Streaming vs Basic Streaming',
+        description: 'Test advanced streaming features vs basic streaming',
+        status: 'running',
+        variants: [
+          { id: 'control', name: 'Basic Streaming', percentage: 70, config: { advancedStreaming: false } },
+          { id: 'treatment', name: 'Advanced Streaming', percentage: 30, config: { advancedStreaming: true } },
+        ],
+        metrics: ['latency', 'error_rate', 'user_engagement'],
+        startDate: new Date('2024-11-15'),
+        endDate: new Date('2024-12-15'),
+      },
+    ];
+
+    defaultExperiments.forEach(exp => {
+      this.experiments.set(exp.id, exp);
+    });
+  }
+
+  getVariant(experimentId: string, userId: string): any {
+    const experiment = this.experiments.get(experimentId);
+    if (!experiment || experiment.status !== 'running') {
+      return null;
+    }
+
+    // Check if user is in target audience
+    if (!this.isUserInAudience(experiment, userId)) {
+      return null;
+    }
+
+    // Determine variant based on user hash
+    const hash = this.getUserHash(userId, experimentId);
+    let cumulativePercentage = 0;
+    
+    for (const variant of experiment.variants) {
+      cumulativePercentage += variant.percentage;
+      if (hash % 100 < cumulativePercentage) {
+        return variant;
+      }
+    }
+
+    return experiment.variants[0]; // Fallback to first variant
+  }
+
+  private isUserInAudience(experiment: Experiment, userId: string): boolean {
+    if (!experiment.targetAudience) return true;
+
+    if (experiment.targetAudience.userIds) {
+      return experiment.targetAudience.userIds.includes(userId);
+    }
+
+    if (experiment.targetAudience.percentage) {
+      const hash = this.getUserHash(userId, experiment.id);
+      return (hash % 100) < experiment.targetAudience.percentage;
+    }
+
+    return true;
+  }
+
+  private getUserHash(userId: string, experimentId: string): number {
+    let hash = 0;
+    const str = `${userId}-${experimentId}`;
+    for (let i = 0; i < str.length; i++) {
+      const char = str.charCodeAt(i);
+      hash = ((hash << 5) - hash) + char;
+      hash = hash & hash;
+    }
+    return Math.abs(hash);
+  }
+
+  async recordMetric(experimentId: string, userId: string, metric: string, value: number) {
+    const variant = this.getVariant(experimentId, userId);
+    if (!variant) return;
+
+    const record = {
+      experimentId,
+      variantId: variant.id,
+      userId,
+      metric,
+      value,
+      timestamp: Date.now(),
+    };
+
+    await this.sendMetricToAnalytics(record);
+  }
+
+  private async sendMetricToAnalytics(record: any) {
+    try {
+      if (process.env.EXPERIMENT_ANALYTICS_ENDPOINT) {
+        await fetch(process.env.EXPERIMENT_ANALYTICS_ENDPOINT, {
+          method: 'POST',
+          headers: { 'Content-Type': 'application/json' },
+          body: JSON.stringify(record),
+        });
+      }
+    } catch (error) {
+      console.warn('Failed to send experiment metric:', error);
+    }
+  }
+}
+
+export const experiments = ExperimentManager.getInstance();
+```
+
+### API Integration
+
+#### Experimental API Route
+
+```typescript
+// app/api/experimental/chat/route.ts
+import { ExperimentalAISDK } from '@/lib/experimental/ai-sdk-experimental';
+import { experiments } from '@/lib/experimental/ab-testing';
+import { anthropic } from '@ai-sdk/anthropic';
+
+export const runtime = 'edge';
+export const maxDuration = 300;
+
+export async function POST(req: Request) {
+  const { messages, userId } = await req.json();
+
+  try {
+    // Get experiment variant
+    const reasoningExperiment = experiments.getVariant('reasoning-vs-standard', userId);
+    const streamingExperiment = experiments.getVariant('streaming-optimization', userId);
+
+    // Configure based on experiments
+    const config = {
+      model: reasoningExperiment?.config.useReasoning 
+        ? anthropic('claude-3-sonnet-20240229')  // Would use O1 in real implementation
+        : anthropic('claude-3-sonnet-20240229'),
+      messages,
+    };
+
+    // Use experimental SDK
+    const result = await ExperimentalAISDK.streamText(config, {
+      userId,
+      fallbackOnError: true,
+      trackUsage: true,
+    });
+
+    // Record experiment metrics
+    if (reasoningExperiment) {
+      // This would be implemented with actual metrics
+      await experiments.recordMetric('reasoning-vs-standard', userId, 'request_count', 1);
+    }
+
+    return result.toUIMessageStreamResponse();
+
+  } catch (error) {
+    console.error('Experimental chat error:', error);
+    
+    // Fallback to stable implementation
+    const result = await ExperimentalAISDK.streamText({
+      model: anthropic('claude-3-sonnet-20240229'),
+      messages,
+    }, { userId, fallbackOnError: false });
+
+    return result.toUIMessageStreamResponse();
+  }
+}
+```
+
+### Monitoring and Safety
+
+#### Experimental Feature Monitoring
+
+```typescript
+// lib/experimental/monitoring.ts
+export class ExperimentalMonitoring {
+  static async recordFeaturePerformance(
+    featureName: string,
+    metrics: {
+      latency?: number;
+      errorRate?: number;
+      userSatisfaction?: number;
+      cost?: number;
+    },
+    userId?: string
+  ) {
+    const record = {
+      feature: featureName,
+      metrics,
+      userId,
+      timestamp: Date.now(),
+      environment: process.env.NODE_ENV,
+      version: process.env.APP_VERSION || 'unknown',
+    };
+
+    await this.sendToMonitoring(record);
+  }
+
+  static async checkFeatureHealth(featureName: string): Promise<boolean> {
+    // Check if feature is performing within acceptable parameters
+    const healthData = await this.getFeatureHealthData(featureName);
+    
+    return (
+      healthData.errorRate < 0.05 && // Less than 5% error rate
+      healthData.latency < 5000 && // Less than 5 second latency
+      healthData.userSatisfaction > 0.7 // Above 70% satisfaction
+    );
+  }
+
+  private static async sendToMonitoring(record: any) {
+    // Send to monitoring service
+    console.log('Experimental Feature Metrics:', record);
+  }
+
+  private static async getFeatureHealthData(featureName: string) {
+    // This would fetch real health data from monitoring service
+    return {
+      errorRate: Math.random() * 0.1,
+      latency: Math.random() * 3000,
+      userSatisfaction: 0.7 + (Math.random() * 0.3),
+    };
+  }
+}
+```
+
+### Usage and Safety Guidelines
+
+- **Feature flags**: Control experimental features with environment variables and remote configuration
+- **A/B testing**: Run controlled experiments to validate new features
+- **Fallback mechanisms**: Always provide stable alternatives for experimental features
+- **Monitoring**: Track performance and user experience of experimental features
+- **Gradual rollout**: Start with small percentages and increase based on performance
+- **Safety checks**: Implement automatic feature disabling for poor performance
+- **Documentation**: Document experimental features and their expected behavior
+
+Focus on building a robust experimental framework that enables safe innovation while protecting user experience and system stability.
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