In metal additive manufacturing (AM), the laser powder-based directed energy deposition (DED) process stands out as a highly promising approach, enabling rapid, layer-wise fabrication and repair of high-volume, complex geometries. DED supports not only custom-tailored designs with single materials but also enables the use of functionally graded materials. However, the process faces challenges due to the melt pool instability, repeated rapid heating and cooling cycles, uneven heat distribution as layers accumulate, and slower production speed compared to traditional milling processes. These factors complicate the management of geometric accuracy, material properties, residual stress, and overall productivity, thereby limiting broader industrial adoption. A real-time closed-loop energy control system is imperative to improve the general quality of DED parts and to promote a wider application. This study proposes and demonstrates a productive energy fluence (PEF) controller that integrates feed rate and laser power adjustments to enhance geometric accuracy and productivity through optimized temperature management. In this hybrid system, a feed rate (FR)-based energy control strategy was initially activated to maintain the layer's median temperature while enhancing productivity by increasing both the FR and powder flow rate (PFR). This approach leverages the inherent energy accumulation of DED process to enhance productivity by reducing energy fluence (EF) input while maintaining powder fluence (PF) input. Once the FR-based control reached its temperature management limit, the system automatically switched to laser power (LP)-based energy control strategy, dynamically adjusting the EF by regulating LP to stabilize the layer's median temperature and geometric accuracy with minimal LP adjustment. Experiments on step-thin wall geometries and high-aspect-ratio thin walls have demonstrated improved geometric accuracy and reduced production time, achieved by comparing a hybrid control strategy against single LP-based and FR-based energy control strategies, as well as an uncontrolled process.