Data-driven interatomic potentials, like atomic cluster expansion (ACE), are revolutionizing material simulations. These models achieve quantum-mechanical accuracy in approximating the potential energy surface, enabling researchers to explore previously inaccessible time and length scales. However, creating a comprehensive training database specific to the material remains a challenge. In this talk, we propose an information-theoretic approach to streamline the design of force fields for material-specific applications using linear ACE potentials. This method will be shown to create accurate potentials for complex alloys like AlSi10Mg, Ti6Al4V and MoNbTaW, allowing us to investigate phase transitions (solid-solid, solid-liquid) and predict various metallurgical phenomena, including precipitation hardening and the discovery of dual phases.