Deep-tech innovation, which harnesses advanced scientific understanding to create groundbreaking technologies, has seen significant growth — and investment — over the past decade. But investors and leaders who pivot into deep tech also face a steep learning curve, as it presents unique challenges: prolonged R&D periods, high upfront costs, and stringent regulatory landscapes. Companies that try to apply traditional startup methodologies, like the lean startup approach, to deep-tech ventures may face surprising pitfalls as deep-tech projects often involve technologies that do not yet exist. While traditional tech startups try to refine existing tech and try to reduce market uncertainty, deep-tech startups need to mitigate technological uncertainty. While methodologies such as lean don’t transfer directly, deep-tech startups can adapt parts of the approach. They should focus on demonstrating proof of concept, defining milestones with compelling data, forming strategic partnerships, navigating regulations, embracing “learning by thinking,” leveraging AI and digital tools, and fostering a culture of truth.
