The future is not something algorithms predict—it's something they produce. In this concluding exploration of Elena Esposito's work, we examine how algorithmic prediction transforms the very nature of futurity, turning forecasts into self-fulfilling prophecies and creating new forms of social contingency. Drawing on her analysis of financial algorithms, recommendation systems, and predictive analytics, we discover that AI doesn't simply calculate what will happen; it opens and closes possibilities, shapes probabilities, constructs the space of what can happen. This has profound implications: if algorithms are architects of possibility, then they're not just observing social reality—they're building it. We explore how this transforms knowledge, memory, agency, and the fundamental openness of the future. As machine learning systems increasingly mediate our access to information, shape our decisions, and structure our social interactions, the question becomes: What kind of futures are algorithms creating? And crucially: Can we create algorithms that preserve human creativity, surprise, and genuine contingency?