GPU resource management is critical for cost-effective AI workloads. After managing GPU resources for 40+ AI projects, I’ve learned what works. Here’s the complete guide to optimizing GPU resources in the cloud. Figure 1: GPU Resource Management Architecture Why GPU Resource Management Matters GPU resources are expensive and limited: Cost: GPUs are the most expensive […]
Read more →Month: June 2024
Document Processing with LLMs: From PDFs to Structured Data
Introduction: Documents are everywhere—PDFs, Word files, scanned images, spreadsheets. Extracting structured information from unstructured documents is one of the most valuable LLM applications. This guide covers building document processing pipelines: extracting text from various formats, chunking strategies for long documents, processing with LLMs for extraction and summarization, and handling edge cases like tables, images, and […]
Read more →Building AI Agents with Tool Use: From ReAct to Production Systems
Introduction: AI agents represent the next evolution beyond simple chatbots—they can reason about problems, break them into steps, use external tools, and iterate until they achieve a goal. Unlike traditional LLM applications that respond to a single prompt, agents maintain state, make decisions, and take actions in the real world. The key innovation is tool […]
Read more →Prompt Performance Monitoring: Tracking LLM Response Quality
Three weeks after launching our AI customer support system, we noticed something strange. Response quality was degrading—slowly, almost imperceptibly. Users weren’t complaining yet, but satisfaction scores were dropping. The problem? We had no way to measure prompt performance. We were optimizing blind. That’s when I built a comprehensive prompt performance monitoring system. Figure 1: Prompt […]
Read more →Token Management for LLM Applications: Counting, Budgeting, and Cost Control
Introduction: Token management is critical for LLM applications—tokens directly impact cost, latency, and whether your prompt fits within context limits. Understanding how to count tokens accurately, truncate context intelligently, and allocate token budgets across different parts of your prompt separates amateur implementations from production-ready systems. This guide covers practical token management: counting with tiktoken, smart […]
Read more →A Comparative Guide to Generative AI Frameworks for Chatbot Development
After two decades of building conversational systems, I have watched the chatbot landscape transform from simple rule-based decision trees to sophisticated AI-powered agents capable of nuanced, context-aware dialogue. The explosion of generative AI frameworks has created both unprecedented opportunities and significant decision paralysis for engineering teams. This guide distills my production experience across dozens of […]
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