Command vs. query prompts: a CQRS-inspired framework for structuring LLM interactionsTreating action-oriented and retrieval-oriented prompts as fundamentally different concerns leads to cleaner, more predictable AI behaviour
Apply CQRS thinking to prompt engineering — learn how splitting command and query prompts improves LLM reliability, tracing, and eval coverage.
RAG 101 for AI Engineers: From Naive Retrieval to Production-Grade PipelinesChunking, embeddings, reranking, citations, evaluation, and failure modes explained simply.
A step-by-step guide to building a reliable RAG system, covering chunking, embeddings, retrieval, reranking, context windows, and evaluation tactics for better answers.