Bioinformatics stands at a precarious intersection: while the bi- ological questions are cutting-edge, the software infrastructure supporting them is often fragile, “ad hoc", and ephemeral. In this paper, we reflect on the state of the practice through a qualitative study of bioinformatics researchers. Our findings reveal a systemic failure: researchers with Computer Science backgrounds struggle to bridge the biological “knowledge gap", while those with Biology backgrounds are bogged down by “installation hell" and fragmented documentation. We argue that the current solution — expecting sci- entists to also be expert systems engineers — is unscalable. We pro- pose a vision of Knowledge-Aware Code Generation: an AI-driven paradigm where “invisible" agents observe exploratory analysis, automatically synthesizing the necessary software infrastructure (containers, regression tests, and documentation) by leveraging domain-specific knowledge graphs.