Agentic coding describes a way of working in which an AI agent, not just an autocomplete, does the engineering. As Anthropic’s own documentation for Claude Code puts it, an agentic coding environment differs from a chatbot that answers questions and waits: it can read your files, run commands, make changes, and autonomously work through problems while you watch, redirect, or step away entirely. The human describes what they want, and the agent explores the codebase, forms a plan, and implements it.
This is a step beyond the suggestion-based assistance of the early GitHub Copilot era. The defining ingredients are a loop and a way to verify: the agent takes an action, checks the result against something concrete like a test suite or a build, and iterates until the check passes. Good practice around these tools centers on giving the agent verifiable goals, separating exploration and planning from implementation, and managing the limited context window carefully, because performance degrades as that window fills.
Agentic coding matters because it changes the unit of delegation in software work, from a line or a function to a whole task or pull request. The same idea powers products as varied as the terminal tool aider, the editor Cursor, and the cloud agents Devin and OpenAI Codex. For a business reader, it is the shift that turns AI from a typing aid into something closer to a junior team member that needs clear goals, guardrails, and review.