LoopX adds a persistent control plane for long-running AI agents
aigclink · x · 2026-08-04
LoopX is a lightweight control plane for long-running AI agent work. It keeps durable state across bounded agent turns so the loop does not lose goals, evidence, quotas, or handoffs.
The project is designed to sit on top of runtimes like Codex, Claude Code, and Cursor rather than replace them. Its state kernel stores objectives, public/private boundaries, user and agent todos, decision scopes, run history, evidence, and quota/reward overlays.
The repo shows two 200+ hour real traces:
- an open-source issue fix that survives multiple PR/review cycles;
- an AutoML experiment where hypotheses, evidence, dead ends, and promote/stop gates stay organized in one graph.
The author’s pitch is that agent runtimes should execute bounded turns, while LoopX preserves the stable control state and writes back compact evidence after durable transitions.
Related event: LoopX Introduces Lightweight Control Plane for Long-Running AI Agents(2 posts)→
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