5 articles
Build a working AI agent from scratch — one that can use tools, make decisions, and complete multi-step tasks. No prior agent experience needed.
Function calling lets LLMs request specific tool actions rather than just generating text. Here's how it works, when to use it, and practical examples in Python.
MCP is Anthropic's open standard for connecting AI assistants to external tools and data sources. Here's what it is, how it works, and why it matters for AI developers.
LangChain handles linear pipelines. LangGraph handles everything that needs loops, branching, or persistent state. Here's the exact decision framework — with code showing when each breaks and why.
