Steve is a General Partner at Foundation Capital, where he works at the intersection of business, technology, and design. He has led investments in, and served on the boards of, Sunrun [RUN], Control4 [CTRL], Bolt Threads, Cerebras, ForUsAll, Framer, Loft Orbital, Mantle, Mode, Pocket (acquired by Mozilla), Sentient Energy, and Simple Habit.
Mention generative AI in a crowded room, and reactions fall somewhere on a spectrum from worry to wonder. Venture capitalists—particularly those like me who work with founders at the very first stages of company creation—are fond of saying that we’re still in the “early days” of a technology’s life cycle. But with the breakneck advances in AI over the past year, from the launch of ChatGPT last November to the emergence of multimodal models, this statement feels uniquely unexaggerated.
Steve Jobs famously likened the computer to a “bicycle for the the mind”: a tool that augments and extends the human intellect. Generative AI transforms this bicycle into a supersonic jet. By accelerating toward creative capabilities once deemed exclusively human, this latest wave of AI models compels us to rethink the nature of our relationship with computers.
At the same time, AI lifts the ceiling, pushing out the perimeter of what experts can achieve. By automating monotonous, repetitive tasks—nudging boxes, adjusting corner radii, removing backgrounds, and so on—it frees professionals to tackle higher-order challenges, like setting vision and strategy, conceiving systems and frameworks, and crafting end-to-end experiences.
Early software interfaces tend to expose the most direct interface to a new computing capability. Over time, these interfaces adopt new metaphors that better resonate with how humans think and navigate virtual space. The first personal computers, for example, laid bare the raw power of microprocessors and memory via command-line interfaces. Later evolutions, like Windows and Mac OS, introduced more user-friendly metaphors—desktops, folders, and trash cans—to humanize this power.
More fluent abstractions for AI capabilities have the potential to unlock massive amounts of utility and joy for everyday users. In the best product experiences, AI will be so seamlessly integrated that we’ll no longer perceive it as “AI” at all.For all their impressive abilities, generative AI models are a far cry from being reliable enough for most real-world applications. This gap between “gee whiz!” demos and dependable deployments is what technologists refer to as the “last mile” problem.
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