Today, the big-data era requires retrosynthesis planning tools to be a fast and accurate replacement for laborious, human-mind-based manual work. We show, however, that designing retrosynthesis planning algorithms is still a challenging task and require constant improvement for faster runtime and more accurate results. For example, replacing a fraction of UCB failed to improve AiZynthFinder accuracy which suggests that synthetic accessibility scores need to be carefully crafted for the target tool.