In this paper, we contribute to the discussion on how to best design human-centric MIR tools for live audio mixing by bridging the gap between research on complex systems, the psychology of automation and the design of tools that support creativity in music production. We present the design of the Channel-AI, an embedded AI system which performs instrument recognition and generates parameter settings suggestions for gain levels, gating, compression and equalization which are specific to the input signal and the instrument type. We discuss what we believe to be the key design principles and perspectives on the making of intelligent tools for creativity and for experts in the loop. We demonstrate how these principles have been applied to inform the design of the interaction between expert live audio mixing engineers with the Channel-AI (i.e. a corpus of AI features embedded in the Midas HD Console. We report the findings from a preliminary evaluation we conducted with three professional mixing engineers and reflect on mixing engineers' comments about the Channel-AI on social media.