Agentic coding

Where autocomplete suggests the next line and chat answers a question, an agentic coding tool takes a goal — “add pagination to this endpoint and cover it with tests” — and works it: reading the codebase, making edits across files, running the test suite, reading the failures, and trying again. Claude Code, Cursor’s agent mode, and Copilot’s agent are the mainstream examples.

The quality of the result depends far more on the environment than on the prompt. An agent with fast tests, strict types, clear module boundaries, and a good context file behaves like a competent engineer. The same agent in a codebase with none of those thrashes, because it has no feedback signal to correct against.

The commonly cited “80% problem” captures the failure mode: an agent gets a task most of the way there quickly, and the last stretch — the edge cases, the integration, the bit that has to actually be right — takes longer to review and repair than writing it would have. That gap narrows as the codebase gets more agent-ready, and widens when it isn’t.