Agentic Coding

What is Agentic Coding?

While classic AI assistants suggest individual lines of code, agentic coding systems take on entire tasks: from refactoring to test creation to bug fixes. The productivity gains are enormous — routine tasks that take developers hours are completed by the agent in minutes. At the same time, the approach requires new skills: developers must learn to effectively direct agents and systematically review their output.

Agentic Coding goes well beyond classic code completion. While traditional AI assistants suggest individual lines of code, agentic coding systems take over the entire development process: they analyze requirements, plan the architecture, write code, run tests, and fix errors — in an autonomous loop. Tools like Claude Code, Cursor, or Devin are practical examples of this approach.

The key lies in the combination of tool calling and iterative reasoning. An agentic coding agent has access to the terminal, filesystem, browser, and testing frameworks. It can write code, execute it, analyze error messages, and correct the code — without a human approving every step. This fundamentally distinguishes Agentic Coding from Vibe Coding, where the AI generates code but the human retains control.

For companies, Agentic Coding means a substantial productivity increase in software development. Routine tasks like refactoring, test creation, or bug fixes can be largely automated. At the same time, the approach requires new skills in Agentic Engineering: developers must learn to effectively direct agents, review their output, and set security guardrails.