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 […]
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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 […]
Read more →Building Multi-Agent Workflows: Advanced LangGraph Patterns
Building multi-agent workflows requires careful orchestration. After building 18+ multi-agent systems with LangGraph, I’ve learned what works. Here’s the complete guide to advanced LangGraph patterns for multi-agent workflows. Figure 1: Multi-Agent Architecture with LangGraph Why Multi-Agent Workflows Multi-agent systems offer significant advantages: Specialization: Each agent handles specific tasks Parallelism: Agents can work simultaneously Scalability: Add […]
Read more →Generative AI Fundamentals: A Practical Guide to the Technology Reshaping Software
Cut through the hype and understand what Generative AI actually is, how it works, and why it matters. A hands-on introduction for developers and architects ready to build with LLMs.
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