After SaaS: The Physical Decade
The hosts:
Mark Windeknecht, World Fund
Pina Fritz, Deep Science Ventures
What is this Ripple about?
As AI drives software development costs toward zero, traditional SaaS moats are eroding. The next decade belongs to companies mastering physical complexity, but AI is also compressing hardware development cycles. What does this mean for climate tech investing?
Why this topic timely or urgent in 2026
The inflection point is now. AI coding agents are already commoditizing standard software development, and within 1–2 years most application-layer software will be buildable at near-zero marginal cost. This fundamentally reshapes where durable value gets created and climate tech is uniquely exposed: the sector's most important companies (PV module manufacturers, battery cell producers, heat pump OEMs, and transformer makers) are hardware businesses. At the same time, AI-assisted design tools, generative CAD, and materials discovery are beginning to compress hardware iteration cycles from 7 years to potentially 2–3. The venture and operating logic for climate hardware needs to be rethought. Now, before the next wave of investment decisions gets made on outdated assumptions.
Key questions or challenges being explored
If AI makes software a commodity, which hardware categories in the energy transition build the most durable moats and why?
AI is accelerating hardware development cycles through generative design, digital twins, and materials discovery. Does this change the venture model for climate hardware: less capital, faster iteration, different risk profile?
If the decade belongs to physical complexity, what does that mean for Europe specifically? Where are our structural advantages, and which hardware categories are we already losing to Asia?
The main tension or debate at the heart of this discussion
Hardware has historically been the harder bet for venture. Longer cycles, more capital, lower margins, harder to scale. If hardware moats are now the most durable, does that mean the current venture model is simply broken for the most important climate companies? And if AI compresses hardware iteration cycles, does hardware start to look more like software, faster, cheaper, more iterative, or does it just mean better-resourced incumbents (CATL, Bosch, Siemens) pull even further ahead, leaving startups permanently locked out of the most valuable positions?
Who would get the most value from attending this Ripple?
Founders building hardware companies in the energy transition, or considering whether to, who want to understand how AI tooling changes their development cycles, capital needs, and competitive positioning. Engineers and operators at the intersection of physical systems and software who are deciding where to place their next decade. Climate tech investors will also benefit, but the sharpest conversations will come from the people actually building the atoms.