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Introduction: CrewAI has emerged as one of the most intuitive frameworks for building multi-agent AI systems. Unlike traditional agent frameworks that focus on single-agent loops, CrewAI introduces a role-playing paradigm where specialized AI agents collaborate as a “crew” to accomplish complex tasks. Released in late 2023 and rapidly gaining adoption throughout 2024, CrewAI simplifies the […]

Introduction: The Model Context Protocol (MCP) is an open standard developed by Anthropic that enables AI assistants to securely connect with external data sources and tools. Think of MCP as a universal adapter that lets AI models interact with your files, databases, APIs, and services through a standardized interface. Instead of building custom integrations for […]

Introduction: Prompt engineering has emerged as one of the most critical skills in the AI era. The difference between a mediocre AI response and an exceptional one often comes down to how you structure your prompt. After years of working with large language models across production systems, I’ve distilled the most effective techniques into this […]

Introduction: Prompts are the interface between your application and LLMs. As applications grow, managing prompts becomes challenging—they’re scattered across code, hard to version, and difficult to test. A prompt template system brings order to this chaos. It separates prompt logic from application code, enables versioning and A/B testing, and makes prompts reusable across different contexts. […]

Introduction: Knowledge graphs represent information as entities and relationships, enabling powerful reasoning and querying capabilities. LLMs excel at extracting structured knowledge from unstructured text—identifying entities, relationships, and attributes that can be stored in graph databases. This guide covers building knowledge graphs with LLMs: entity and relation extraction, graph schema design, populating Neo4j and other graph […]