Software processes rely on both structured system knowledge such as code, version histories, and logs, and tacit knowledge including human rationale, practices, and decisions. We argue that effective human–AI collaboration requires shared and evolving knowledge spaces that integrate these knowledge sources and make their connections explicit. Using differential testing as a motivating case, we describe our initial prototype and the challenges it revealed, and we outline a broader vision for dynamic knowledge networks that support more effective collaboration between humans and AI.