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 […]
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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 →Building AI-Powered Frontends: Real-Time LLM Interactions in React
Building AI-Powered Frontends: Real-Time LLM Interactions in React Expert Guide to Creating Seamless, Real-Time AI Experiences in Modern React Applications After building dozens of AI-powered applications over the past few years, I’ve learned that the frontend experience makes or breaks an AI product. It’s not enough to have a powerful LLM backend—users need to feel […]
Read more →Memory Systems for LLMs: Buffers, Summaries, and Vector Storage
Introduction: LLMs have no inherent memory—each request starts fresh. Building effective memory systems enables conversations that span sessions, personalization based on user history, and agents that learn from past interactions. Memory architectures range from simple conversation buffers to sophisticated vector-based long-term storage with semantic retrieval. This guide covers practical memory patterns: conversation buffers, sliding windows, […]
Read more →Large Language Models Deep Dive: Understanding the Engines Behind Modern AI
Go beyond the basics and understand how LLMs actually work. Master prompting techniques, compare models, and learn cost optimization strategies for production use.
Read more →Event-Driven Architecture on GCP: Mastering Cloud Pub/Sub for Real-Time Systems
Google Cloud Pub/Sub provides the foundation for event-driven architectures at any scale, offering globally distributed messaging with exactly-once delivery semantics and sub-second latency. This comprehensive guide explores Pub/Sub’s enterprise capabilities. Cloud Pub/Sub Architecture Overview Pub/Sub Architecture: Topics, Subscriptions, and Delivery Guarantees Pub/Sub implements a publish-subscribe pattern where publishers send messages to topics and subscribers receive […]
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