Agentic Coding
Agentic coding describes workflows where the model or IDE extension can act like a junior developer: read the repo, create files, run commands, and debug until the task is done, within your guardrails.
It differs from plain tab completion through planning, tool loops, and giving the model responsibility for multiple connected steps. Compare Cursor, Claude Code, and vibe coding when the trade-off is speed vs control.
Key characteristics
- Lets AI read the codebase, propose changes, run commands, and iterate until a task is solved.
- Requires clear guardrails such as tests, limited permissions, and code review before merge.
- Is especially useful for refactoring, debugging, and boilerplate, but less suitable for critical code without manual verification.
Example
A concrete example is giving the agent the task: "Add a new endpoint and write tests."
Instead of returning one code suggestion, it can:
- read the existing folder structure and follow project conventions
- create or update files in the right order
- run tests and interpret error messages
- iterate until the test suite passes
That autonomous loop is exactly what separates agentic coding from standard autocomplete.