Mobile sensing is difficult without power. Emerging Computational RFIDs (CRFIDs) provide both sensing and generalpurpose computation without batteries-instead relying on small capacitors charged by energy harvesting. CRFIDs have small form factors and consume less energy than traditional sensor motes. However, CRFIDs have yet to see widespread use because of limited autonomy and the propensity for frequent power loss as a result of the necessarily small capacitors that serve as a microcontroller's power supply. Our results show that hybrid harvesting CRFIDs, which use an ambient energy micro-harvester, can complete a variety of useful workloads-even in an environment with little ambient energy available.Our contributions include (1) benchmarks demonstrating that micro-harvesting from ambient energy sources enables greater range and read rate, as well as autonomous operation by hybrid CRFIDs, (2) a measurement study that stresses the limits of effective ambient energy harvesting for diverse workloads, (3) application studies that demonstrate the benefits of hybrid CRFIDs, and (4) a trace-driven simulator to model and evaluate the expected behavior of a CRFID with different capacitor sizes and operating under varying conditions of mobility and solar energy harvesting. Our results show that ambient harvesting can triple the effective communication range of a CRFID, quadruple the read rate, and achieve 95% uptime in RAM retention mode despite long periods of low light.