[smaddox]

It's not enough to just have API's published unidirectionally, if you want the system to evolve into something optimally fit for a particular job.

Think of layers in a convolutional neural network, for example. Each layer of neural units provides information to the next layer, but fixing the output of the higher layers limits the trainability and ultimate accuracy of the trained network. In order to maximize fitness, full backpropagation (or similar) is needed, with all layers being trained.

What's needed for self-negotiated API's is a generalization of the CNN model (or similar) into a variable-length serial communication format. Humans would define a fitness function either explicitly or implicitly by interacting with the system, and the self-negotiating API system would use some many-parameter optimization algorithm to alter both the Server and Client(s) and maximize the total fitness.