Build a Basic AI Agent from Scratch (www.ruxu.dev)

A new tutorial series has emerged, focusing on building a basic AI agent from scratch using Python, highlighting the growing significance of AI agents in 2026. Following the release of powerful models like Claude Code and Codex, these agents are increasingly becoming essential tools for developers and knowledge work. The tutorial emphasizes understanding the underlying mechanics instead of utilizing pre-built frameworks by constructing a simple agent that operates in a continuous loop, connects with a large language model (LLM), accepts user input, and maintains conversational context. The article outlines the core components necessary for the agent: a persistent loop, an LLM connection (using a local instance of the Ollama model), user input handling, and a context management system. While the current implementation functions like a basic chatbot, it lacks the capability to perform actions in its environment such as executing commands or retrieving data. The next phase of the series promises to enhance the agent's functionality by introducing tool-calling features, showcasing the potential advancements AI agents can achieve as they continue to evolve.