Rebecca Kaden is a former journalist who applies her storytelling background to venture investing, treating investment theses as narratives she develops and lives with for years rather than pursuing opportunistic deals. She focuses on consumer companies with leveraged growth models where technology amplifies brand and distribution, and she mentors founders on crafting compelling narratives that connect their personal stories to market opportunities.

• Focus on the shift from software as a toolset to AI as programmable labor that performs actual work. She distinguishes between agents acting as copilots that assist humans and pilots that take the wheel entirely, such as legal agents that can autonomously close funding rounds or handle tax filings without human intervention.
• Interest in democratizing industrial automation and robotics for the long tail of the economy, including family-owned businesses and smaller manufacturers. She highlights companies like Tutor Intelligence that offer robots-as-a-service to make high-performance automation financially accessible beyond just massive corporations.
• Thesis on using programmable systems to drive the cost of traditionally expensive services down to near zero. She points to healthcare innovation where AI doctors, like those from Doctronic, write prescriptions without humans in the loop, fundamentally changing accessibility and market cost structures.
• Concerns regarding energy as the primary constraint for AI growth and the need for new architectures at the intersection of the physical and digital worlds. She specifically notes that unlocking future possibilities requires making compute dramatically more efficient to solve the energy problem inherent in scaling intelligence.
• Belief in a seismic shift in education where AI is central to how schools are built and how students learn. She advocates for interest-driven models that foster a love for learning, citing Sora Schools as an example of an institution designed for this new era rather than adapting old systems.
• Exploration of how AI agents utilize context versus memory and the trade-offs between generalizing and specializing. She discusses how velocity is crucial for teams building these tools, highlighting founders who rapidly ship updates to create agents that can eventually run companies autonomously.