Recent years have produced a patchwork of promising methods for netlist reverse engineering, especially in partitioning and module identification. However, only a small fraction of this research translates into tools that are reliable, scalable, interoperable, and usable in practice. This talk argues that the dominant challenge today is no longer the invention of isolated algorithmic techniques, but the systematic integration of existing methods into an automated, end-to-end workflow that can be deployed, maintained, and trusted as an industry-grade tool. Only such an integrated approach enables reverse engineers to move beyond low-level structural recovery toward higher-level objectives, including the identification of implemented algorithms and the development of actionable, system-level understanding. We therefore need to examine how current state-of-the-art methods perform when applied to realistic netlists, and which techniques are sufficiently robust to be incorporated into a practical reverse engineering pipeline. Beyond purely algorithmic aspects, we also examine the organizational constraints and usability requirements that such a pipeline must address. This includes, for example, the need for on-premise deployment, support for multi-user collaboration, secure sharing of reverse engineering results, and a productive interplay between automated analysis and human expertise, acknowledging that reverse engineering outcomes are inherently imperfect. Finally, we ask how the field can move beyond fragmented and short-lived research prototypes toward a more unified and maintainable platform, and what would be required to make this transition viable for all stakeholders. We outline a roadmap of the technical, operational, and usability challenges ahead, with the goal of fostering discussion around the features and capabilities needed to make automated netlist reverse engineering feasible in practice.

For two decades, reverse engineering has evolved from a niche manual craft into a foundational pillar of security assurance. Yet, as the two impulse talks at the beginning of this session have shown, the field currently stands at a crossroads. While we look upon years of research and hundreds of technical methods, the practical reality is a landscape of fragmented prototypes, low reproducibility, and significant "translation friction" between academic theory and industry application.

This panel discussion moves beyond the "what" of reverse engineering to confront the "how" of its future. We bring together a diverse cohort of experts to bridge the gap between academic success, open-source mindset and contributions, and industry-grade workflows. This panel will discuss a range of ongoing challenges and their potential for tension between stakeholders, but also promising solutions, all to aim for a future where automated netlist analysis is not just a research possibility, but a reliable, scalable, and trustworthy reality.