@freeman1266: Loop Engineering needs five things: 1. Goal Definition - Not "do one thing", but "keep doing until this condition is met." The /goal primitive lets you define a verifiable stopping condition, judged by an independent small model—not by the agent doing the work…
Summary
Introduces the five key elements of Loop Engineering: Goal Definition, Iteration Loop, State Management, Verification Mechanism, and Self-correction, designed to achieve continuous improvement through automated AI agent loops.
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Loop Engineering requires five things:
-
Goal Definition
Not “do one thing,” but “keep doing until this condition is met.” The/goalprimitive lets you define a verifiable stopping condition, judged by an independent small model — not by the Agent doing the work grading itself. -
Iteration Loop (Automation)
Automatically triggered on a schedule, performing its own discovery and triage. Runs every morning, finds issues, distributes tasks, and sends results to your inbox — instead of you having to check everywhere. -
State Management (Memory/State)
Agents forget, but repos don’t. A markdown file, a Linear board — anything that exists outside a single conversation — can serve as the loop’s memory. The next day’s run picks up where yesterday left off. -
Verification Mechanism (Sub-agent Verifier)
The model that writes code is too generous when scoring itself. Separate the “writer” from the “checker” — have a second Agent catch issues the first one talked itself into ignoring. This is the only reason you can walk away. -
Self-correction
Find the problem, open a worktree, draft a fix, review it, open a PR — fully automated. You only handle the part the loop can’t.
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