Artificial Intelligence (AI) with its Machine-Learning (ML) vertiginous advances are dramatically reshaping our way of developing software either as (prompting) GenerativeAI- or purely ML-based ones. Nevertheless, this newly emerging AI-Era of software is unfortunately not significantly benefiting from decades of investigations and findings around software-engineering (SE) concepts, principles and methods. The resulting is plethora of GenerativeAI- and ML-based software: Black-boxed rigid ill-conceptually and completely isolated from our ”ordinary” yet mostly disciplined software landscape. The aim of this paper is to contribute in leveraging such unsatisfactory Prompting and ML-based software form to be well-conceptually, dynamically adaptable by intrinsically fitting it within our ”ordinary” domain-oriented software landscape: We refer generically to as AI-Powered (knowledge-intensive) applications software; thereby reconciliating Domain- and AI-Experts instead of contemporarily miserable ’confrontation’.