Recent developments in artificial intelligence have surprisingly been only on the machine-learning related technologies. This growing trend brings new hardships to the already problematic AI programming sector that looks like a zoo of paradigms. AI is unfortunately full of incompatible technologies that can hardly cooperate in a common multidisciplinary project. These technologies are also under the threat of being abandoned in favor of the emerging machine learning techniques. However, there are many valuable ideas and concepts in the classical AI approaches that can be quite useful in the awaiting challenges of general AI. Such a great endeavor will necessitate everything we know about representing and processing knowledge.  Meta-modeling of the AI domain as a whole can bring about model driven development as a glue for the fragmented development efforts. In the long run it also has the capacity to trigger a unification and revival of the art of AI programming around a more structured central paradigm.