The FDA previously operated as seven distinct centers, each with its own legal and communications teams. This extreme siloing created nightmares for developers of combination products and led to absurd inefficiencies, like employees being unable to email files between centers.
To accelerate AI adoption, Block intentionally dismantled its siloed General Manager (GM) structure, which had given autonomy to units like Cash App. They centralized into a functional organization to drive engineering excellence, unify policies, and create a strong foundation for a company-wide AI transformation.
BridgeBio's unique structure creates dedicated subsidiaries for each program. This empowers small, focused teams closest to the science to make key decisions—"play calling on the field"—without layers of bureaucracy. This model dramatically accelerates development, leading to unprecedented output of new drugs.
Companies run numerous disconnected AI pilots in R&D, commercial, and other silos, each with its own metrics. This fragmented approach prevents enterprise-wide impact and disconnects AI investment from C-suite goals like share price or revenue growth. The core problem is strategic, not technical.
While political drama at the top of the FDA captures headlines, the agency's rank-and-file reviewers are largely maintaining operational continuity. Many drug programs are still receiving necessary feedback within expected timeframes, suggesting the core machinery of the FDA is resilient.
Customers interact with a company as a single entity, but internally, separate departments like sales and support optimize for their own conflicting metrics. This creates a confusing and inefficient experience, a direct result of Conway's Law in action.
The 'FDA for AI' analogy is flawed because the FDA's rigid, one-drug-one-disease model is ill-suited for a general-purpose technology. This structure struggles with modern personalized medicine, and a similar top-down regime for AI could embed faulty assumptions, stifling innovation and adaptability for a rapidly evolving field.
The FDA commissioner found that scientific reviewers only share groundbreaking ideas for process improvement when guaranteed anonymity, fearing repercussions from their supervisors. This highlights a stifling bureaucratic culture where true innovation happens in one-on-one meetings, not formal briefings.
The current disconnect between the FDA leadership's public calls for flexibility and its divisions' strict actions is not new. For decades, the agency's hierarchy has acted as a promotional arm to encourage industry, while the review divisions have maintained a more conservative, old-school approach to rigor. This historical pattern is often overlooked.
When patient engagement is owned by a single department, it's often treated as optional. To make it a core business driver, responsibility must be shared across R&D, medical, regulatory, and commercial teams. This requires a structural and cultural shift to become truly transformational for the organization.
Organizing by function (e.g., all sales together) seems efficient but incentivizes teams to optimize their individual metrics, not the company's success. This sub-optimization prevents cross-functional learning and leads to blame games, ultimately harming the entire customer value stream and creating a non-learning organization.