An experts systems must perform well that is achieve the same levels of performance in the domain of interest that human experts can achieve. But simply producing good solutions is not enough. Real experts not only produce good solutions but often find them quickly while novices tend to take much longer to find the same solutions. Thus an expert systems must be skilful apply its knowledge to produce solutions both efficiently and effectively suing the shortcuts or tricks that human experts use to eliminate wasteful or unnecessary calculations. To truly mimic a human experts an experts system also have robustness. This means having not only depth in subject but breadth as well.