The core of Loop Engineering is simple.
Instead of manually prompting the AI every turn with "do this now," "verify this," "write docs," or "create the next issue," you define a goal and let the AI iterate autonomously until it reaches the completion state.
To do this right, you need at least 6 core elements:
1. Automations: Automate execution, verification, follow-up tasks, and state updates.
2. Worktrees: Isolate tasks for safe experimentation without breaking the main branch.
3. Skills: Turn repetitive workflows like code review, QA, documentation, and refactoring into reusable execution units.
4. Plugins/Connectors: Hook into real-world tools like GitHub, Linear, browsers, and external APIs.
5. Sub-agents: Instead of one agent doing everything sequentially, distribute roles like reviewer, implementer, QA, and researcher for parallel evaluation.
6. Memory: Store decisions, rationale, changes, verification results, and follow-up issues so context outlives a single chat session.
For example, consider this goal:
> Improve the current dashboard so real users can actually understand it. Iterate through UX review, bug fixes, visual QA, doc updates, and issue organization until users can instantly judge what is happening, what to read, and what to do next from a single screen.
This is not simply "fix the dashboard UI."
It is a loop that drives product quality to a definitive state of completion.
The loop interprets the goal, asks clarifying questions to set baselines if necessary, then implements, reviews, and tests in an isolated workspace. If it fails, it revises. Outputs are saved as a human-readable Wiki and a machine-readable Memory. Finally, it isolates remaining tasks into new issues and verifies the stopping criteria.
The key takeaway: AI is not replacing the engineer.
The system takes over the repetitive prompting loop, while the engineer remains entirely responsible for goals, judgment, verification, and direction.
Build the loop, stay the engineer.
If you want to get a practical feel for this, I recommend checking out this repository: github.com/rlaope/loop
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