Battery-free sensing has revolutionized IoT applications, but current solutions relying on signal variations between transmitted and backscattered signals remain vulnerable to environmental dynamics and deployment variations. This paper promotes a paradigm shift: inferring targets through antenna impedance variations instead of signal fluctuations, thereby eliminating the impact of unpredictable wireless communication. We demonstrate the effectiveness of this paradigm by reimplementing three existing applications: RIO [1], Keystub [2], and RF-EATS [3]. Compared to original signal-based implementations, our approach shows significant improvements in accuracy and robustness across diverse environments. Furthermore, By integrating antenna engineering with advanced materials science, we also transform antennas into innovative sensors for pressure, temperature, and UV light sensing. This interdisciplinary methodology pushes the boundaries of battery-free sensing, opening new avenues for IoT applications.