What a Coding Agent Is
A coding agent is an AI that doesn’t just suggest text. It can read your files, run commands, and make changes — working in a loop until a task is actually done.
The Agent Loop
An agent doesn’t answer once and stop. It cycles — and that cycle is what separates it from a chatbot.
- Reads context — your files, the error, the task
- Plans & acts — edits files, runs tools and commands
- Observes the result — did the test pass, did it build?
- Repeats until the task is done or it needs you
Levels of Autonomy
Coding agents sit on a spectrum. You choose how much rope to give one for the task at hand.
When To Use One
Agents shine on work that is clear to specify and easy to check.
- Well-scoped tasks — one feature, one fix, a clear goal
- Boilerplate & repetitive edits across many files
- Exploring an unfamiliar codebase
- Writing tests for code you already have
When Not To
An agent is not always the right tool. Hold back when:
- You can’t yet specify the problem — if you can’t describe it, the agent can’t solve it
- The change is high-stakes and you can’t verify the result
- You’d learn more doing it yourself — skill you’ll want later
Build It
How to implement: pick one small, well-scoped task and hand it to a coding agent (Claude Code, Cursor, or similar) end-to-end — then watch the read → act → observe loop happen. GenAI‑101 has hands-on Claude Code labs; here we stay conceptual.
- Weekly AI Tasks tracker — you’ll build most of it by directing a coding agent; scope each piece (one endpoint, one view) so the agent can finish and you can check it.
- Personal brand site — a great first agent task: well-scoped, low-stakes, and easy to eyeball the result.
What You Learned
A coding agent reads, acts, observes, and repeats — that loop is the difference from a chatbot. Autonomy is a dial: more speed, more review. Use one for scoped, checkable work; skip it when you can’t specify or verify.