Loop engineering is the practice of designing automated systems that prompt AI coding agents on your behalf, rather than prompting them manually turn by turn. The concept, articulated by engineers at Anthropic and OpenAI, centers on five building blocks now present in both Claude Code and Codex: automations (scheduled discovery/triage), worktrees (parallel agent isolation via git), skills (persistent project context), plugins/connectors (MCP-based tool integrations), and sub-agents (maker/checker separation). A sixth element — external memory like a markdown file or Linear board — ties runs together across sessions. The post walks through how these pieces combine into a self-running loop that triages CI failures, drafts fixes, reviews them, opens PRs, and updates tickets autonomously. The author is cautiously optimistic but warns about token costs, comprehension debt (shipping code you don't understand), and cognitive surrender — the risk of disengaging from the work entirely when the loop runs itself.

13m read timeFrom addyo.substack.com
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The five pieces, and then notesAutomations, this is the heartbeatWorktrees so parallel doesn’t turn into chaosSkills, so you stop explaining your project every single timePlugins and connectors, the loop touches your real toolsSub-agents, keep the maker away from the checkerWhat one loop looks likeWhat the loop still does not do for youBuild the loop. Stay the engineer.
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