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Loop Engineering

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Loop Engineering is the practice of designing recurring systems for AI agents and coding agents. Instead of prompting an agent turn by turn, you build a loop that discovers work, delegates it to one or more agents, verifies the result against tests or other deterministic gates, persists state outside the model, decides what happens next, and runs again on a cadence, an event, or until a verifiable goal is reached. It sits above prompt, context, and harness engineering: those improve a single run, while loop engineering governs repeated agent work over time, including budgets, retries, escalation to humans, and stopping conditions.

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howashoji / Looptrack

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Issue tracker serving as external memory for AI coding agents, enabling loop engineering. Records AI-planned work items apart from project issues, showing plans and decisions and logging task tokens for reports. ／ AI コーディングエージェントの外部記憶となり、ループエンジニアリングを実現するイシュー管理ツール。プロジェクト本来のイシューとは別に、AI が分解した作業単位の課題を記録する。AI の作業計画と意思決定を可視化し、各作業のトークンも記録して分析レポートを出力できる。

golang mcp issue-tracker self-hosted loop codex ai-agents github-copilot claude-code loop-engineering
  • Updated Oct 1, 2026
  • Go
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50 followers
Website
github.com/topics/loop-engineering

Related topics

agentic-ai ai-agents automation llm prompt-engineering