AI tutorial - IT technology blog
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AI Agents: What They Are & How to Build Your First Automated Workflow

AI agents are changing how we automate complex IT tasks, using large language models (LLMs) with specialized tools and advanced reasoning. This tutorial shows you how to build your first agent with Python and LangChain, covering environment setup, configuration, and key monitoring techniques.
AI tutorial - IT technology blog
Posted inAI

Mastering Model Context Protocol (MCP): Empowering AI with External Tools

The Model Context Protocol (MCP) is crucial for AI models to interact effectively with external tools and APIs, overcoming their inherent limitations. This comprehensive guide covers the core concepts of MCP, from defining tools and orchestrating calls to handling complex workflows and prioritizing security. Learn how to build dynamic AI applications that fetch real-time data and perform actions far beyond their initial training.
AI tutorial - IT technology blog
Posted inAI

NotebookLM: Your AI Research Assistant Tutorial

Discover how Google's NotebookLM functions as an AI research assistant. It helps you analyze, summarize, and extract insights directly from your uploaded documents and web sources. This tutorial guides you through its unique grounded AI approach and practical usage to streamline your information gathering, making your research more efficient and reliable.
AI tutorial - IT technology blog
Posted inAI

Boost Efficiency: AI-Powered CLI Tools for DevOps & SysAdmin Workflows

Explore how AI-powered command-line interface tools are revolutionizing DevOps and SysAdmin workflows. This tutorial covers practical applications, from natural language command generation to AI-assisted log analysis and script development, highlighting tangible benefits for efficiency and problem-solving in the real world.
AI tutorial - IT technology blog
Posted inAI

Fine-Tuning LLMs for Production: When and How to Master It

When your LLM struggles with specific domain knowledge or consistent output in production, fine-tuning might be the most effective solution. This article explores when and how to apply fine-tuning, focusing on practical steps and modern, efficient techniques like LoRA, to achieve stable and precise results for your AI applications.