Windsurf rules

1# Advanced AI Optimization
2 
3**Activation Mode**: Manual
4**Usage**: `@ai-optimization` - Use when optimizing AI performance, costs, or implementing advanced AI patterns
5 
6<performance_optimization>
7- Cache AI responses when appropriate using Redis or in-memory solutions
8- Implement request debouncing and batching for AI API calls
9- Use edge functions for AI API proxying to reduce latency
10- Consider streaming responses for long-running AI operations
11- Monitor token usage and implement cost optimization strategies
12</performance_optimization>
13 
14<advanced_patterns>
15- Implement prompt versioning and A/B testing for AI interactions
16- Use vector databases for AI-powered search and recommendation features
17- Implement AI model switching based on task complexity and cost
18- Create AI agent patterns with tool calling and function execution
19- Implement multi-modal AI integrations (text, image, audio)
20</advanced_patterns>
21 
22<monitoring_and_analytics>
23- Log AI API usage, costs, and performance metrics
24- Monitor response times and error rates for AI services
25- Track user interactions and satisfaction with AI features
26- Implement health checks and alerting for AI service availability
27- Use OpenTelemetry or similar for AI service observability
28</monitoring_and_analytics>
29 
30<scalability_considerations>
31- Design AI workflows for horizontal scaling and load balancing
32- Implement queue systems for background AI processing
33- Consider serverless architectures for variable AI workloads
34- Use database optimization for AI-generated content storage
35- Implement proper AI service failover and redundancy strategies
36</scalability_considerations>