C4: Container, Code, Cloud & Context
Designing intelligent systems, one layer at a time. ~ Nithin Mohan T K
When Anaconda released their AI Navigator tool, I was skeptical. After two decades of building data science environments from scratch, managing conda environments manually, and wrestling with dependency conflicts across dozens of projects, I wondered if yet another GUI tool could actually solve the problems that have plagued Python development for years. After six months […]
Read more →Introduction: Processing documents with LLMs unlocks powerful capabilities: extracting structured data from unstructured text, summarizing lengthy reports, answering questions about document content, and transforming documents between formats. However, effective document processing requires more than just sending text to an LLM—it demands careful parsing, intelligent chunking, and strategic prompting. This guide covers practical document processing patterns: […]
Read more →Introduction: Observability is essential for production LLM applications—you need visibility into latency, token usage, costs, error rates, and output quality. Unlike traditional applications where you can rely on status codes and response times, LLM applications require tracking prompt versions, model behavior, and semantic quality metrics. This guide covers practical observability: distributed tracing for multi-step LLM […]
Read more →Introduction: Evaluating LLM outputs is fundamentally different from traditional ML evaluation. There’s no single ground truth for creative tasks, quality is subjective, and outputs vary with each generation. Yet rigorous evaluation is essential for production systems—you need to know if your prompts are working, if model changes improve quality, and if your system meets user […]
Read more →Master parameter-efficient fine-tuning with LoRA and QLoRA. Learn how to customize LLMs like Llama 3 and Mistral on consumer hardware with step-by-step implementation guides.
Read more →Introduction: Natural language to SQL is one of the most practical LLM applications. Business users can query databases without knowing SQL, analysts can explore data faster, and developers can prototype queries quickly. But naive implementations fail spectacularly—generating invalid SQL, hallucinating table names, or producing queries that return wrong results. This guide covers building robust text-to-SQL […]
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