Does an idea need to be "original" to be "new", or is novelty simply a byproduct of a broken expectation? Beyond Echo explores what it would mean for an AI system to generate ideas that are experienced as genuinely new, rather than predictable recombinations of existing patterns. The project questions whether novelty is an objective property of ideas or a perceptual one, shaped by what an observer (human or machine) already knows. Drawing on the Information Gap theory of curiosity, I investigate how expectation, surprise and unanswered questions drive human ideation, and whether similar dynamics can be meaningfully modeled in artificial systems. My project combines conceptual inquiry with experimental probes of generative and representational models, examining how ideas occupy and move through semantic embedding spaces, asking whether novelty can be induced by altering how models explore their own representational structures. Rather than treating creativity as a fixed capability, Beyond Echo treats it as an emergent property shaped by architecture, representation and interaction. The project aims to surface both the possibilities and the limits of current AI systems, and to reflect on what it would mean if machines could produce ideas that are indistinguishable from human insight. Would human creativity be compromised if ideation could be outsourced?