Introduction: LLM applications face unique security challenges—prompt injection, data leakage, jailbreaking, and harmful content generation. Traditional security measures don’t address these AI-specific threats. This guide covers defensive techniques for production LLM systems: input sanitization, prompt injection detection, output filtering, rate limiting, content moderation, and audit logging. These patterns help you build LLM applications that are […]
Read more →Category: Emerging Technologies
Emerging technologies include a variety of technologies such as educational technology, information technology, nanotechnology, biotechnology, cognitive science, psychotechnology, robotics, and artificial intelligence.
Introduction to Generative AI: A Comprehensive Guide
The first time I watched a generative model produce coherent text from a simple prompt, I knew we had crossed a threshold that would reshape how we build software. After two decades of working with various AI and ML systems, from rule-based expert systems to deep learning pipelines, I can say with confidence that generative […]
Read more →Embedding Strategies: Model Selection, Batching, and Long Document Handling
Introduction: Embeddings are the foundation of semantic search, RAG systems, and similarity-based applications. Choosing the right embedding model and strategy significantly impacts retrieval quality, latency, and cost. Different models excel at different tasks—some optimize for semantic similarity, others for retrieval, and some for specific domains. This guide covers practical embedding strategies: model selection based on […]
Read more →Production RAG Architecture: Building Scalable Vector Search Systems
Three months into production, our RAG system started failing at 2AM. Not gracefully—complete outages. The problem wasn’t the models or the embeddings. It was the architecture. After rebuilding it twice, here’s what I learned about building RAG systems that actually work in production. Figure 1: Production RAG Architecture Overview The Night Everything Broke It was […]
Read more →Scaling Up Your Pods: How Horizontal Pod Autoscaling Wins
After two decades of managing containerized workloads across production environments, I’ve come to appreciate that the difference between a good Kubernetes deployment and a great one often comes down to how intelligently it responds to changing demand. Horizontal Pod Autoscaling (HPA) represents one of those fundamental capabilities that separates reactive operations from proactive infrastructure management. […]
Read more →Structured Output from LLMs: JSON Mode, Function Calling, and Instructor
Introduction: Getting LLMs to return structured data instead of free-form text is essential for building reliable applications. Whether you need JSON for API responses, typed objects for downstream processing, or specific formats for data extraction, structured output techniques ensure consistency and parseability. This guide covers the major approaches: JSON mode, function calling, the Instructor library, […]
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