Cristina brings a rare "inside operator" perspective to venture investing, having been Stripe's 28th employee and first business development hire, then Head of Platform & Partnerships at Notion, and now COO at Linear, giving her deep experience in what actually scales product-led companies from the inside out. She's particularly known for her tactical, playbook-oriented approach to advising founders, sharing detailed lessons learned from building partnerships and GTM strategies at these iconic companies rather than high-level advice.

• A strong focus on the intersection of artificial intelligence and developer workflows. The account frequently discusses how AI agents are shifting the value in software development away from the implementation grind and toward high-level decision-making and final quality review.
• Advocacy for specialized AI models over a single dominant system. Highlights include backing companies that build focused tools for specific tasks, noting that future successful AI startups will likely earn trust through reliability and speed in niche applications rather than trying to do everything.
• Deep interest in high-performance operational tools that reduce administrative friction. Frequently shares case studies, such as Oscar Health or Cursor, where large teams migrated away from complex legacy tracking systems to faster platforms to avoid hitting ceilings on productivity.
• Appreciation for the concept of craft within scaling businesses. Uses examples like a chocolate maker to illustrate that technology and automation should be used to enhance attention to detail and values, rather than just for cutting costs or growing quickly.
• Investment interest in B2B infrastructure and financial technology. Recently highlighted support for a startup tackling manual accounting bottlenecks, signaling a preference for founders with deep industry experience solving unglamorous but essential back-office problems.
• Belief in the importance of context for AI utility. Argues that for coding agents and automated tools to function effectively, they require a deep, integrated layer of information about what the team is actually working on, rather than just operating in a vacuum.