Toward a Science of Intent: Closure Gaps and Delegation Envelopes for Open-World AI Agents

ArXi:2604.25000v1 Announce Type: new Recent work has framed intelligence in verifiable tasks as reducing time-to-solution through learned structure and test-time search, while systems work has explored learned runtimes in which computation, memory and I/O migrate into model state. These perspectives do not explain why capable models remain difficult to deploy in open institutions. We propose intent compilation: the transformation of partially specified human purpose into inspectable artifacts that bind execution.