This paper introduces agentic meta-reasoning, an inference-time framework where a controller makes explicit decisions about task execution while workers perform computations. Tested on multiple benchmarks including program reconstruction, the approach achieves significant improvements over direct control baselines, with gains of 3.6–4.2 points across frontier models and better performance at larger compute budgets.