(TD-)DFT methods depend on the choice of functional, which is still often designed in a semi-empirical way for specific properties and/or molecular systems, and, as such, it is hard to improve in a systematic way. The reliable performance of a certain functional for new properties is therefore not assured. Oftentimes, (TD-)DFT methods need to be benchmarked against high-end methods, such as those based on the coupled cluster (CC) ansatz. The fully ab initio CC methods do not contain or require a priori assumptions about the nature of the studied system, which are common in the construction of many DFT functionals. Thus, CC methods treat different molecules on more equal footing and provide less biased results compared to DFT, which on the other hand can be sensitive to particular combinations of molecules and functionals. The CC ansatz also offers a clear and systematic path toward the full theoretical limit, though at the price of a steep increase in the computational costs moving up the hierarchy of CC approximations. However, the CC model only provides a good approximation when the system can be well described by a single determinant.