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 →Category: Artificial Intelligence(AI)
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, […]
Read more →Prompt Templates and Versioning: Building Maintainable LLM Applications
Introduction: Production LLM applications need structured prompt management—not ad-hoc string concatenation scattered across code. Prompt templates provide reusable, parameterized prompts with consistent formatting. Versioning enables A/B testing, rollbacks, and tracking which prompts produced which results. This guide covers practical prompt template patterns: template engines and variable substitution, prompt registries, version control strategies, A/B testing frameworks, […]
Read more →Deploying LLM Applications on Cloud Run: A Complete Guide
Last year, I deployed our first LLM application to Cloud Run. What should have taken hours took three days. Cold starts killed our latency. Memory limits caused crashes. Timeouts broke long-running requests. After deploying 20+ LLM applications to Cloud Run, I’ve learned what works and what doesn’t. Here’s the complete guide. Figure 1: Cloud Run […]
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