March 2025 Recap: Advanced Patterns and Production Readiness

March 2025 focused on advanced patterns and production-readiness. Here’s what we covered.

Key Topics This Month

Advanced RAG Patterns

• Query transformation techniques
• Reranking strategies for precision
• Chunking optimization approaches
• Context window management

Knowledge Integration

• Knowledge graphs with AI
• GraphRAG implementation
• Semantic layer design
• Data mesh + AI patterns

Production Essentials

• Testing AI applications
• Guardrails and safety
• Prompt injection defense
• AI observability

Model Optimization

• Fine-tuning strategies
• Model distillation
• Prompt caching
• Function calling patterns

Multi-Modal AI

• Vision-language applications
• Audio processing
• Document understanding
• Cross-modal reasoning

Code Patterns to Remember

# March 2025 Essential Patterns

# 1. Query Expansion for better recall
async def expand_query(query: str) -> list[str]:
    variations = await llm.generate_variations(query)
    return [query] + variations

# 2. Cross-encoder reranking for precision
def rerank(query: str, docs: list, top_k: int = 5) -> list:
    scores = cross_encoder.predict([[query, doc] for doc in docs])
    return sorted(zip(docs, scores), key=lambda x: x[1], reverse=True)[:top_k]

# 3. Guardrails wrapper
async def safe_generate(prompt: str) -> str:
    if not await check_input_safety(prompt):
        return "I cannot process that request."
    response = await llm.generate(prompt)
    if not await check_output_safety(response):
        return "I cannot provide that response."
    return response

# 4. Quality tracking
def track_response(question: str, response: str, context: str):
    metrics = evaluate_rag(question, response, context)
    observability.log(metrics)

Looking Ahead to April

April kicks off Q2 with focus on:

• Build 2025 preparation
• Copilot development patterns
• Windows AI features
• On-device model deployment

Stay tuned for more practical AI content in April!