Introduction: Fine-tuning transforms a general-purpose LLM into a specialized model for your specific use case. While prompt engineering works for many applications, fine-tuning offers advantages when you need consistent formatting, domain-specific knowledge, or reduced latency from shorter prompts. This guide covers practical fine-tuning: when to fine-tune versus prompt engineer, preparing training data, running fine-tuning jobs […]
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Document Processing with LLMs: From PDFs to Structured Data (Part 1 of 2)
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 →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 →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 […]
Read more →Hallucinations in Generative AI: Understanding, Challenges, and Solutions
The Reality Check We All Need The first time I encountered a hallucination in a production AI system, it cost my client three days of debugging and a significant amount of trust. A customer-facing chatbot had confidently provided detailed instructions for a product feature that simply did not exist. The response was articulate, well-structured, and […]
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