Introduction: Prompts are code—they define your application’s behavior and should be managed with the same rigor as source code. Yet many teams treat prompts as ad-hoc strings scattered throughout their codebase, making it impossible to track changes, compare versions, or systematically improve performance. This guide covers practical prompt management: version control systems for prompts, A/B […]
Read more →Category: Artificial Intelligence(AI)
Azure OpenAI Service with Python: Building Enterprise AI Applications
After spending two decades building enterprise applications, I’ve watched countless “revolutionary” technologies come and go. But Azure OpenAI Service represents something genuinely different—a managed platform that brings the power of GPT-4 and other foundation models into the enterprise with the security, compliance, and operational controls that production systems demand. Here’s what I’ve learned from integrating […]
Read more →LLM Guardrails and Safety: Protecting Your AI Application from Attacks
Introduction: Deploying LLMs in production without guardrails is like driving without seatbelts—it might work fine until it doesn’t. Users will try to jailbreak your system, inject malicious prompts, extract training data, and push your model into generating harmful content. Guardrails are the safety layer between raw LLM capabilities and your users. This guide covers implementing […]
Read more →Claude API Deep Dive: Building with Anthropic’s Models
A comprehensive guide to the Anthropic Claude API covering Claude 3.5 Sonnet, tool use, vision, computer use, and production best practices.
Read more →The Complete Guide to RAG Architecture: From Fundamentals to Production
Master Retrieval-Augmented Generation (RAG) with this expert-level guide. Learn about RAG types (Naive, Advanced, Modular, Agentic), chunking strategies, embedding models, vector databases, hybrid retrieval, and production best practices with high-quality architecture diagrams.
Read more →Advanced Retrieval Strategies for RAG: The Complete Guide to Dense, Hybrid, and Multi-Stage Search
Introduction: Retrieval is the foundation of RAG systems—the quality of retrieved documents directly impacts generation quality. Different retrieval strategies excel in different scenarios: dense retrieval captures semantic similarity, sparse retrieval handles exact keyword matches, and hybrid approaches combine both. This guide covers advanced retrieval techniques: embedding-based dense retrieval, BM25 and sparse methods, hybrid search strategies, […]
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