After two decades of building enterprise systems, I’ve witnessed numerous technology waves—from SOA to microservices, from on-premises to cloud-native. But nothing has matched the velocity and transformative potential of generative AI. The challenge isn’t whether to adopt it; it’s how to do so without creating technical debt that will haunt your organization for years. The […]
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.
Vector Databases: Why They Matter in the Age of Generative AI
After two decades of architecting enterprise systems and spending the past year deeply immersed in Generative AI implementations, I can state with confidence that vector databases have become the cornerstone of modern AI infrastructure. If you’re building anything involving Large Language Models, semantic search, or Retrieval-Augmented Generation (RAG), understanding vector databases isn’t optional—it’s essential. This […]
Read more →Prompt Chaining Patterns: Breaking Complex Tasks into Manageable Steps
Introduction: Complex tasks often exceed what a single LLM call can handle well. Breaking problems into smaller steps—where each step’s output feeds into the next—produces better results than trying to do everything at once. Prompt chaining decomposes complex workflows into sequential LLM calls, each focused on a specific subtask. This guide covers practical chaining patterns: […]
Read more →OpenAI Assistants API: Building Stateful AI Agents with Code Interpreter and File Search
Introduction: OpenAI’s Assistants API, launched at DevDay 2023, represents a significant evolution in how developers build AI-powered applications. Unlike the stateless Chat Completions API, Assistants provides a managed, stateful runtime for building sophisticated AI agents with built-in tools like Code Interpreter and File Search. The API handles conversation threading, file management, and tool execution, allowing […]
Read more →LLM Cost Optimization: Reducing API Spend Without Sacrificing Quality (Part 1 of 2)
Introduction: LLM API costs can spiral quickly—a chatbot handling 10,000 daily users at $0.01 per conversation costs $3,000 monthly. Production systems need cost optimization without sacrificing quality. This guide covers practical strategies: semantic caching to avoid redundant calls, model routing to use cheaper models when possible, prompt compression to reduce token counts, and monitoring to […]
Read more →LLM Evaluation: Metrics, Benchmarks, and A/B Testing
Introduction: Evaluating LLM outputs is challenging because there’s often no single “correct” answer. Traditional metrics like BLEU and ROUGE fall short for open-ended generation. This guide covers modern evaluation approaches: automated metrics for specific tasks, LLM-as-judge for quality assessment, human evaluation frameworks, A/B testing in production, and building comprehensive evaluation pipelines. These techniques help you […]
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