
How to Build an AI Agent from Scratch Using Claude API (With Full Code)
I've built a lot of AI demos that looked impressive in a notebook and fell apart in production. The usual culprit? Treating an LLM like a search engine, one prompt in, one answer out, instead of what it actually is: a reasoning engine you can wire into real workflows. This tutorial is about doing it properly. We're going to build a functional AI agent using Anthropic's Claude API from the ground up, not a wrapper around a framework, but the actual mechanics: a ReAct loop, custom tool use, and a structure you can actually deploy. By the end you'll have running code and a mental model that makes every agent tutorial after this one make sense. Let's get into it. What We're Actually Building The agent we're building will: Accept a user query Decide which tools it needs to answer Call those tools, observe the results Reason over the results and either call more tools or return a final answer This pattern is called ReAct (Reasoning + Acting). It's the backbone of most production agents and i
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