A neuro fuzzy method to design analog circuits is explained, where the universe of discourse of the fuzzy system is adjusted by means of a self-organized artificial neural network. As an example of this approach, an op-amp is optimized in order to hold a predetermined aim; where the unity gain bandwidth is an objective of design, and the restrictions of open-loop gain and margin phase are treated as objectives too. Firstly, the experience of the behavior of the circuit is obtained, hence an inference system is constructed and a neural network is applied to achieve a faster convergence into a desired solution. This approach is characterized by having a simple implementation, a very natural understanding and a better performance than static methods of fuzzy optimization.