In practice
Ask a coding agent to fix a failing checkout test. It finds the test, reads the code around it, changes the bug, runs the suite and reports back. You didn't open a file.
Wikipedia lists the software developer agent among the types of AI agent, an AI program that pursues goals and acts without constant human direction. Claude Code, Cursor, Codex and Grok each fit that description, in a terminal, an editor or the cloud.
A coding agent isn't an autocomplete tool, which predicts what you type next inside your editor. It isn't a chatbot, which answers and waits. And it isn't a replacement for review: the person still reads the diff.
How to brief one
- State the result you want, not the steps.
- Point to the files, the existing pattern and what is out of scope.
- Say how it will know it is done: a test, a build or a screenshot.
- Keep your standing rules in AGENTS.md so each session starts from them.
- Read the diff and the evidence before you merge.
Common mistakes
- Treating it like autocomplete: tiny prompts, no checks, then surprise at a large diff.
- Giving two agents the same job. They overwrite each other.
- Merging because it says it's done. Ask for the test output.
Why it matters for product builders
Where autocomplete speeds up typing, an agent takes whole tasks. That moves your job from writing code to briefing, reviewing and deciding.
It also means agents act on what they're told. If two agents get different instructions, they build different things, and the rework lands on you.
What changes in AI-first products
The term is new with this wave of tools, so there is no older practice to contrast. What changed is who does the typing. What didn't change is that someone has to know what customers need.
Running two or more agents is where the strain shows: each one starts without the others' context. Annsa gives them one source of direction and connects to Claude Code, Cursor, Codex and Grok over MCP.
See how Annsa does it: Direct your agents →