Introduction: Basic RAG retrieves documents and stuffs them into context. Advanced RAG transforms retrieval into a sophisticated pipeline that dramatically improves answer quality. This guide covers the techniques that separate production RAG systems from prototypes: query rewriting to improve retrieval, hybrid search combining dense and sparse methods, cross-encoder reranking for precision, contextual compression to fit […]
Read more →Category: Technology Engineering
Technology Engineering
Retrieval Evaluation Metrics: Measuring What Matters in Search and RAG Systems
Introduction: Retrieval evaluation is the foundation of building effective RAG systems and search applications. Without proper metrics, you’re flying blind—unable to tell if your retrieval improvements actually help or hurt end-user experience. This guide covers the essential metrics for evaluating retrieval systems: precision and recall at various cutoffs, Mean Reciprocal Rank (MRR), Normalized Discounted Cumulative […]
Read more →Retrieval Augmented Fine-Tuning (RAFT): Training LLMs to Excel at RAG Tasks
Introduction: Retrieval Augmented Fine-Tuning (RAFT) represents a powerful approach to improving LLM performance on domain-specific tasks by combining the benefits of fine-tuning with retrieval-augmented generation. Traditional RAG systems retrieve relevant documents at inference time and include them in the prompt, but the base model wasn’t trained to effectively use retrieved context. RAFT addresses this by […]
Read more →The Hidden Tax on Innovation: Why FinOps Is the Most Important Discipline You’re Probably Ignoring
Every organization eventually faces the same uncomfortable realization: their cloud bill has become a runaway train. What starts as a modest monthly expense metastasizes into millions of dollars in annual spend, with nobody quite able to explain where all the money goes. FinOps Framework Overview The Three Pillars of FinOps The FinOps Foundation defines three […]
Read more →The Architecture Decision That Will Make or Break Your System: Monolith vs Microservices in 2025
The debate between monolithic and microservices architectures has evolved significantly over the past decade. What was once a straightforward “microservices are better” narrative has matured into a nuanced understanding that the right architecture depends entirely on context. After leading architecture decisions across dozens of enterprise systems, I’ve learned that the most expensive mistakes come not […]
Read more →Multi-turn Conversation Design: Building Natural Dialogue Systems with LLMs
Introduction: Multi-turn conversations are where LLM applications become truly useful. Users don’t just ask single questions—they refine, follow up, reference previous context, and expect the assistant to remember what was discussed. Building effective multi-turn systems requires careful attention to context management, history compression, turn-taking logic, and graceful handling of topic changes. This guide covers practical […]
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