Ai-Agents

You open Claude Code on a new project. You ask it to fix a bug. It changes the wrong file. It uses the wrong architecture pattern. It runs the wrong build command. Not because Claude is bad. Because it doesn’t know your project. That is what context files solve. A CLAUDE.md or AGENTS.md file tells the AI everything it needs to know about your project before it starts working. It is the single most impactful thing you can do to improve AI coding agent output. ...

In the previous article, we learned what AI coding agents are. Now let’s build one. Not a toy demo. A real agent that reads your code, finds problems, fixes them, runs tests, and commits the result. You will understand how agents work from the inside. We will use Python and the Anthropic SDK (Claude API). The concepts apply to any AI provider. What We Are Building A simple agent that: Reads a Python file Sends it to Claude with instructions to fix linting errors Writes the fixed code back to the file Runs the linter to verify the fix If it still fails — tries again (up to 3 attempts) Commits the result with git This is the same loop that Claude Code and Copilot Agent use internally — just smaller and simpler. ...

A few years ago, AI coding tools just suggested the next line while you typed. Helpful, but you still wrote most of the code. That changed completely. In 2026, AI coding agents don’t just suggest — they plan, write, test, and ship code on their own. You describe what you want, and the agent builds it. It creates files, edits existing code, runs your tests, fixes failures, and opens a pull request. ...