Intent Compilation Framework for Open-World AI Agents

A recent preprint on arXiv (2604.25000) presents intent compilation, a technique for converting partially defined human intentions into artifacts that can be examined and that govern AI operations. The study differentiates between closed-world solvers and open-world agents, noting that verification in open environments involves semantic, evidentiary, procedural, and institutional aspects. It introduces the concept of residual openness as a closure-gap vector, defines delegation envelopes as areas for pre-authorized actions, and clarifies the difference between misclosure and undersearch. Additionally, it proposes benchmark metrics for assessing when closure is reached. This research explores the challenges of deploying advanced models in open institutions.