SOURCE-LINKED INTELLIGENCE
An Architecture for Long-Horizon Agents: Levels, Ticks and Cascaded Intelligence
Language-model agents are increasingly asked to carry out work spanning days or weeks, such as an operations remediation or a research programme. Such a task outlives any context window, any process and any interval at which a person can attend. In this paper, we argue that a long-horizon agent must run continually without forgetting before it can learn continually. This ability lies in the harness around the model rather than in the model itself. We derive seven bottlenecks from the long-horizon setting and answer them with a hierarchical architecture of three parts: (i) levels indexed by tim
Read original source ↗ Open in workspace
- recordType
- paper
- region
- Global
Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-17T00:15:24.000Z
- arXiv · Artificial Intelligence · 2026-09-17T00:15:24.000Z
First collected: 2026-09-19T20:26:32.566Z. This is not the publication date.