The current industry approach to AI safety, which focuses on censoring a model's "latent space," is flawed and ineffective. True safety work should reorient around preventing real-world, "meatspace" harm (e.g., data breaches). Security vulnerabilities should be fixed at the system level, not by trying to "lobotomize" the model itself.

Unlike a biocompatibility study that can be scheduled for a specific quarter, cybersecurity cannot be treated as a one-time milestone. It must be an iterative process integrated throughout the entire product lifecycle, from initial design and software development to post-market surveillance.

The core innovation for the Cobra OS wasn't a complex discovery but the disciplined application of a known principle: miniaturizing endovascular devices always makes them safer. By focusing on shrinking the device, they inherently improved safety by reducing the size of the arterial access site.

MedTech companies mistakenly assign product cybersecurity to their IT teams, whose focus is data protection. Product security is about patient safety and should be owned by Quality Assurance, as all documentation must integrate into the Quality Management System (QMS) like other design files.

Retrofitting cybersecurity into a medical device near submission is a common, catastrophic error. The FDA requires security to be designed-in from the start. "Bolting it on" later leads to significant delays and costs, much like trying to add rebar to an already-poured foundation.

Enterprises face millions of potential vulnerabilities, making prioritization impossible. The key is to ignore the noise and focus only on the small fraction that are actually exploitable by hackers. This shifts remediation efforts from theoretical weaknesses to real-world business risk.

In high-stakes regulated fields, documentation like FMEAs is not red tape. It's a critical tool for understanding failure modes, mitigating risks, and ensuring product viability and patient safety, especially for a startup where one recall can be fatal.

Security's focus shifted from physical (bodyguards) to digital (cybersecurity) with the internet. As AI agents become primary economic actors, security must undergo a similar fundamental reinvention. The core business value may be the same (like Blockbuster vs. Netflix), but the security architecture must be rebuilt from first principles.

Dr. Jordan Schlain frames AI in healthcare as fundamentally different from typical tech development. The guiding principle must shift from Silicon Valley's "move fast and break things" to "move fast and not harm people." This is because healthcare is a "land of small errors and big consequences," requiring robust failure plans and accountability.