production-grade system designs. failure modes, observability, and the stuff that actually matters.
Production-ready Retrieval-Augmented Generation systems with chunking, embeddings, reranking, and citations
PII detection, jailbreak prevention, tool safety, and content filtering
Gold sets, LLM-as-judge risks, regression testing, and offline/online evaluation
Token streaming, response caching, and performance optimization
Choosing between vector databases, hybrid search, and embedding strategies
Decision guide for choosing the right approach for your use case
Complete guide to building evaluation systems for LLM applications: gold sets, LLM-as-judge, regression testing, offline/online evaluation, and production monitoring
Comprehensive guide to implementing PII detection, jailbreak prevention, content filtering, tool safety, and output validation in production LLM applications
Complete guide to building production-ready Retrieval-Augmented Generation systems with chunking strategies, embedding models, reranking, citations, and observability
Complete guide to implementing token streaming, response caching, and performance optimization for production LLM systems
Comprehensive guide to vector database selection: performance, scalability, cost, features, and when to use Pinecone, Weaviate, Qdrant, Milvus, or PostgreSQL