It can be very difficult to manually create software systems which capture the knowledge of an expert. It is an expensive and laborious process that often results in a suboptimal solution. In this paper we propose a new approach which does not require complete manual knowledge construction. The described system is relevant and usable for the end user from the beginning of its development. It is continuously being trained by the experts while they are using it. The study pays attention to the development of the hypotheses that the developing system uses as it adapts to feedback it receives from its own actions on itself, on objects, on the users of the system and the reflection on this feedback. This paper explains how the computer learns from the experts using an example system which performs handwriting recognition. In order to provide a general mechanism, the principle of learning to learn is proposed and applied to the problem of handwriting recognition. The goal is the creation of a system that learns to 'google' through handwritten documents, starting from scratch with a pile of raw images.