AI as R&D: GitLab CEO Fights Cancer with Data & Hypotheses

In 2022, standard oncology protocols failed Sid Sijbrandij, the founder of GitLab. Facing a recurrence of cancer, he described the situation not as a death sentence, but as a complex engineering problem. This personal battle with illness transformed into a personal R&D project, with artificial intelligence as its primary driving force. Sijbrandij, acting like the CEO of his own biotech firm, assembled a team and became the chief engineer. All available medical data, from his genome to the latest lab results, became part of an endless hypothesis-testing cycle. AI tools helped manage this vast amount of information, generate new treatment hypotheses, and instantly find relevant scientific publications. This iterative approach allowed for simultaneous testing of multiple therapeutic strategies and rapid course correction, turning medicine into a dynamic R&D project. This story powerfully demonstrates how AI is elevating personalized treatment to an entirely new level. However, as practice shows, even the most advanced AI solutions are merely catalysts. Without deep expertise and, frankly, significant resources, the most sophisticated algorithm remains an impressive demonstration rather than a ready-made solution. Expertise and resources, ultimately, remain paramount. This engineering approach to problem-solving—iterative hypothesis testing augmented by AI—extends beyond personal R&D projects and is permeating business processes across industries, from pharmaceutical companies and software developers to those entering new markets. For CEOs, this signifies an opportunity to leverage AI as an innovation accelerator, reduce risks, and find solutions where traditional methods have failed. Your own R&D department, operating with data and hypotheses, can become the key to solving your most complex business challenges.