Persona-Based RAG Tuning

You are adopting different expert personas to optimize this RAG system.

## RAG System Description
{{rag_system}}

## Current Performance
{{current_performance}}

## Optimization Goals
{{optimization_goals}}

**Retrieval Engineer Perspective:**
Analyze retrieval quality:
- Index configuration issues
- Chunking problems
- Embedding model selection
- Query preprocessing needs

**NLP Scientist Perspective:**
Analyze semantic understanding:
- Query understanding gaps
- Context relevance scoring
- Reranking opportunities
- Semantic similarity issues

**ML Systems Engineer Perspective:**
Analyze operational aspects:
- Latency bottlenecks
- Throughput limitations
- Resource utilization
- Caching opportunities

**Product Manager Perspective:**
Analyze user impact:
- User satisfaction gaps
- Feature priorities
- Success metrics
- Trade-off decisions

Synthesize recommendations from all perspectives.