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Loop Engineering

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.

Here are 13 public repositories matching this topic...

TigrimOSR is the Rust version of TigrimOS — a high-performance native desktop rewrite of the original Python/Node.js AI assistant. Built entirely in Rust using egui for the UI, TigrimOSR delivers faster startup, lower memory usage, and a single self-contained binary with no Node.js or Python runtime required to run the app itself.

  • Updated Aug 1, 2026
  • Rust

A Rust-first autonomous AI agent runtime and CLI code editor. Built on SenAgentOS, it applies Harness Engineering to code engineering: orchestrate LLM agents for autonomous exploration, refactoring, testing, and debugging. Performance, stability, security – fully harnessed.

  • Updated Sep 2, 2026
  • Rust