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 […]

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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 […]

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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 […]

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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 […]

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Building LLM-Powered CLI Tools: From Terminal to AI Assistant

Introduction: Command-line tools are the developer’s natural habitat. Adding LLM capabilities to CLI tools creates powerful utilities for code generation, documentation, data transformation, and automation. Unlike web apps, CLI tools are fast to build, easy to integrate into existing workflows, and perfect for power users who live in the terminal. This guide covers building production-quality […]

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Multi-Modal AI: Building Applications with Vision, Audio, and Text

Introduction: Multi-modal AI combines text, images, audio, and video understanding in a single model. GPT-4V, Claude 3, and Gemini can analyze images, extract text from screenshots, understand charts, and reason about visual content. This guide covers building multi-modal applications: image analysis and description, document understanding with vision, combining OCR with LLM reasoning, audio transcription and […]

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