What Are AI Agent Loops?
A practical explanation of AI agent loops, feedback gates, exit conditions, and why they are safer than one-shot prompts.
An AI agent loop is a reusable instruction protocol for a coding agent. It does not just tell the agent what to do. It also tells the agent how to check progress, when to continue, when to stop, and what evidence to return.
A normal prompt often ends after one response. A loop adds a feedback gate such as npm test, pnpm build, gh pr checks, or a manual review checklist. The agent should run the gate after each pass, inspect the result, fix the smallest remaining issue, and stop only when the exit condition is satisfied.
Good loops have five parts:
- A clear goal.
- Required context and tools.
- A check command or review gate.
- Guardrails that prevent bypassing validation.
- A final response format with evidence.
This structure is useful because coding agents can otherwise skip verification, over-edit files, or claim success before the project is actually healthy.