However, point defects that are commonly involved in surface catalysis can feature complex potential energy surfaces with multiple local minima. That is to say, there exists multiple metastable configurations and only one true ground-state configuration. The elephant in the room is then, is the necessity of such non-trivial task of locating the true global minimum for the PES justifiable? Well, the oversight of the actual configuration of the defect species can certainly cause the subsequent analysis to become redundant. This fatal flaw will mislead us to the wrong mechanism of defect formation, causing erroneous conclusion of inert defect species as the active sites, and vice versa. Unfortunately, this occurrence is typical in the reductionist approach for defects in complex host materials, compromising the integrity of the approach to improve catalytic performance by inducing the defects site. Evidently, this represents a major obstruction to the accuracy and robustness of first principles defect predictions. To resolve this obvious limitation, we can either apply random sampling to the neighboring atoms of the defect site as proposed in the Ab Initio Random Structure Sampling (AIRRS) approach by Pickard and Need or exploit machine learning to navigate the defects configuration energy landscape and predict its local minima as demonstrated by Arrigoni and Madson . While the machine learning approach can attain accuracy comparable to that of first-principles calculations with the scalability of classical calculations, it is not without their fallacies, including the issue of data quantity, data quality, and data bias. Although the AIRSS is rather intuitive for simple host materials (low-dimensional chemical space), a caveat to note is that random sampling on high-dimensional chemical space lowers its efficiency and the increase in computational cost makes the approach infeasible. Thus, one can imagine that the proper identification of defect sites in catalytic surface is not as straightforward as it would appear, and vigilance must be upheld when differentiating between the metastable and ground-state configurations.