Make things clean and neat. But always understand: if it's clean and neat, it's missing something.
There is no one best way to represent knowledge, or to solve problems, and limitations of present-day machine intelligence stem largely from seeking 'unified theories', or trying to repair the deficiencies of theoretically neat, but conceptually impoverished ideological positions. Our purely numerical connectionist networks are inherently deficient in abilities to reason well; our purely symbolic logical systems are inherently deficient in abilities to represent the all-important 'heuristic connections' between things — the uncertain, approximate, and analogical linkages that we need for making new hypotheses. The versatility that we need can be found only in larger-scale architectures that can exploit and manage the advantages of several types of representations at the same time. Then, each can be used to overcome the deficiencies of the others.