Coding Agents (Like Claude Code) for Real Projects

Coding agents (Claude Code, Cursor, GitHub Copilot Workspace) work on real coding projects. They write code, run tests, debug — like a coding partner who never gets tired.

Some examples

• 'Build me a simple game in Python with these features [list].'
• 'My code is broken. Run it, find the bug, fix it.'
• 'Add a new feature to my project — explain what you did.'
• 'Refactor this code to be cleaner.'

Try it!

What coding agents actually do under the hood

Coding agents like Claude Code, Cursor, and GitHub Copilot Workspace aren't just autocomplete on steroids. They're agentic loops that read your codebase, write code, run tests, read the error output, fix the code, and repeat — all without you manually running every command. Understanding this loop matters for using them well. When you give a coding agent a task like 'add user authentication to this Express app,' it will: read your existing code structure, look up relevant patterns, generate the auth code, insert it in the right files, run your test suite, read failing tests, fix the issues, and report back. Each of those is a discrete step with a tool call. When the agent gets it wrong, it's often at a specific step — usually either misreading your existing code structure or generating code that makes wrong assumptions about your libraries. Knowing which step failed helps you write a better prompt to correct it.

• Always read what the agent changed — use 'git diff' after every coding agent session
• Provide good context upfront: repo structure, tech stack, coding conventions, test framework
• Let the agent run your test suite — passing tests are the only reliable quality check
• Break large features into pull-request-sized chunks; smaller scopes = better agent output