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.agent/skills/senior-ml-engineer/references/llm_integration_guide.md

@@ -1,80 +0,0 @@
-# Llm Integration Guide
-
-## Overview
-
-World-class llm integration guide for senior ml/ai engineer.
-
-## Core Principles
-
-### Production-First Design
-
-Always design with production in mind:
-- Scalability: Handle 10x current load
-- Reliability: 99.9% uptime target
-- Maintainability: Clear, documented code
-- Observability: Monitor everything
-
-### Performance by Design
-
-Optimize from the start:
-- Efficient algorithms
-- Resource awareness
-- Strategic caching
-- Batch processing
-
-### Security & Privacy
-
-Build security in:
-- Input validation
-- Data encryption
-- Access control
-- Audit logging
-
-## Advanced Patterns
-
-### Pattern 1: Distributed Processing
-
-Enterprise-scale data processing with fault tolerance.
-
-### Pattern 2: Real-Time Systems
-
-Low-latency, high-throughput systems.
-
-### Pattern 3: ML at Scale
-
-Production ML with monitoring and automation.
-
-## Best Practices
-
-### Code Quality
-- Comprehensive testing
-- Clear documentation
-- Code reviews
-- Type hints
-
-### Performance
-- Profile before optimizing
-- Monitor continuously
-- Cache strategically
-- Batch operations
-
-### Reliability
-- Design for failure
-- Implement retries
-- Use circuit breakers
-- Monitor health
-
-## Tools & Technologies
-
-Essential tools for this domain:
-- Development frameworks
-- Testing libraries
-- Deployment platforms
-- Monitoring solutions
-
-## Further Reading
-
-- Research papers
-- Industry blogs
-- Conference talks
-- Open source projects

.agent/skills/senior-ml-engineer/references/mlops_production_patterns.md

@@ -1,80 +0,0 @@
-# Mlops Production Patterns
-
-## Overview
-
-World-class mlops production patterns for senior ml/ai engineer.
-
-## Core Principles
-
-### Production-First Design
-
-Always design with production in mind:
-- Scalability: Handle 10x current load
-- Reliability: 99.9% uptime target
-- Maintainability: Clear, documented code
-- Observability: Monitor everything
-
-### Performance by Design
-
-Optimize from the start:
-- Efficient algorithms
-- Resource awareness
-- Strategic caching
-- Batch processing
-
-### Security & Privacy
-
-Build security in:
-- Input validation
-- Data encryption
-- Access control
-- Audit logging
-
-## Advanced Patterns
-
-### Pattern 1: Distributed Processing
-
-Enterprise-scale data processing with fault tolerance.
-
-### Pattern 2: Real-Time Systems
-
-Low-latency, high-throughput systems.
-
-### Pattern 3: ML at Scale
-
-Production ML with monitoring and automation.
-
-## Best Practices
-
-### Code Quality
-- Comprehensive testing
-- Clear documentation
-- Code reviews
-- Type hints
-
-### Performance
-- Profile before optimizing
-- Monitor continuously
-- Cache strategically
-- Batch operations
-
-### Reliability
-- Design for failure
-- Implement retries
-- Use circuit breakers
-- Monitor health
-
-## Tools & Technologies
-
-Essential tools for this domain:
-- Development frameworks
-- Testing libraries
-- Deployment platforms
-- Monitoring solutions
-
-## Further Reading
-
-- Research papers
-- Industry blogs
-- Conference talks
-- Open source projects

.agent/skills/senior-ml-engineer/references/rag_system_architecture.md

@@ -1,80 +0,0 @@
-# Rag System Architecture
-
-## Overview
-
-World-class rag system architecture for senior ml/ai engineer.
-
-## Core Principles
-
-### Production-First Design
-
-Always design with production in mind:
-- Scalability: Handle 10x current load
-- Reliability: 99.9% uptime target
-- Maintainability: Clear, documented code
-- Observability: Monitor everything
-
-### Performance by Design
-
-Optimize from the start:
-- Efficient algorithms
-- Resource awareness
-- Strategic caching
-- Batch processing
-
-### Security & Privacy
-
-Build security in:
-- Input validation
-- Data encryption
-- Access control
-- Audit logging
-
-## Advanced Patterns
-
-### Pattern 1: Distributed Processing
-
-Enterprise-scale data processing with fault tolerance.
-
-### Pattern 2: Real-Time Systems
-
-Low-latency, high-throughput systems.
-
-### Pattern 3: ML at Scale
-
-Production ML with monitoring and automation.
-
-## Best Practices
-
-### Code Quality
-- Comprehensive testing
-- Clear documentation
-- Code reviews
-- Type hints
-
-### Performance
-- Profile before optimizing
-- Monitor continuously
-- Cache strategically
-- Batch operations
-
-### Reliability
-- Design for failure
-- Implement retries
-- Use circuit breakers
-- Monitor health
-
-## Tools & Technologies
-
-Essential tools for this domain:
-- Development frameworks
-- Testing libraries
-- Deployment platforms
-- Monitoring solutions
-
-## Further Reading
-
-- Research papers
-- Industry blogs
-- Conference talks
-- Open source projects