What is an AI coding loop?
It is a repeated workflow where a coding agent works on bounded tasks and leaves output for developer inspection before the next step or merge.
Glossary
An AI coding loop is a repeated plan, implement, inspect, and continue workflow for agent-assisted software development.
Why it matters
An AI coding loop turns agent work into repeatable iterations instead of one long, drifting chat session.
An AI coding loop is a repeatable workflow where a developer defines a bounded task, an AI coding agent implements against that task, and the resulting changes are inspected before continuing or merging. Hal structures this loop around PRDs, validation, runtime state, reports, and review.
An AI coding loop is a repeatable sequence for using an AI coding agent on software work. A healthy loop defines the task, runs implementation, records what happened, and gives a developer a review point.
Hal frames the loop around PRDs and stories. The site describes the sequence as planning, conversion, validation, running, reporting, archiving, and human review.
A reviewable loop leaves artifacts. Those can include changed files, commits, reports, workflow state, acceptance criteria, and archive history.
Avoid one broad prompt that asks an agent to implement an entire complex feature without boundaries. Long unstructured sessions are harder to inspect and easier to drift.
Short answers before you put this into an agent workflow.
It is a repeated workflow where a coding agent works on bounded tasks and leaves output for developer inspection before the next step or merge.
Hal describes a flow through planning, conversion, validation, implementation, reporting, archiving, and review.
Keep exploring the pieces of a reviewable coding loop.