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LazyAgent: Demand-Driven Materialization and Physical Optimization of Agentic Programs

arXiv · AI, language, vision and robotics · article · Sep 19, 2026 · UTC

Current agent runtimes that plan before acting generally execute a step once it becomes ready. We present LazyAgent, a unified execution framework for agent-authored programs organized around a live, goal-derived demanded set. LazyAgent refreshes a backward closure from requested outputs as execution state changes and materializes a ready node only when the active goal requires it. This replaces repeated local judgments with one linear-time graph analysis followed by constant-time membership tests, allowing programs to remain broad while execution stays request-specific. On programs that descr

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