Every year, executives visit Silicon Valley to visit leading tech companies and to meet leading entrepreneurs, especially now with a new breed of AI-Native startups.
AI-Native are a new breed of startups that ship faster with tiny teams, deliver near-instant time-to-value, and generate outsized revenue per employee (RPE) while scaling without scaling headcount, and create moats that keep them competitive as they evolve.
In this is a special session, Brian will bring Silicon Valley to you. He'll reveal his research around "AInfinite thinking" and what it means to think like an AI Native startup by exploring the mindsets of founders and investors.
You’ll walk away with a blueprint to learn from AI-Natives: how they build moats, how they structure teams around outcomes, and how they redesign work so humans focus on judgment, creativity, and deep thinking while AI handles analysis, synthesis, and execution.
During his time in Silicon Valley, Brian has helped launch over 1,000 startups, including Airbnb, Uber, Tripit, Twitch, Zappos, Google, Amazon, and Meta. Brian has also advised investors and guided celebrities on their startup investments, including Oprah, Shaq, Adrien Grenier, Katie Couric and Ashton Kutcher. KGO called him a “Silicon Valley staple” and “one of the top people to know in Silicon Valley” by Huffpost.
Audience Takeaways...
Adopt the AI-native “Founder OS”: move with speed, customer obsession, and relentless learning.
Design a moat beyond the model: compete with proprietary workflows, data advantage, and distributions.
Ship to learn, not to impress: prototype fast, measure impact, iterate in-market, and let usage—not committees—decide.
Make AI a team sport: rewire how work gets done with human+agent collaboration, clear guardrails, and new operating rhythms.
Think like an investor: place disciplined bets, kill zombie projects, and scale what proves traction with focus and conviction.
Measure what matters: track time-to-value, adoption, revenue-per-employee, cost-to-serve, and agentic capacity to accelerate ROI and double down where the numbers prove momentum.
The AI-Native playbook for tiny teams that scale outcomes, not headcount
How to improve RPE and compress time-to-value by redesigning decisions, handoffs, and workflows
The new defensible moats: data + distribution + trust + experience—and how to build them internally
A practical path from pilots to an AI-native operating model (roles, workflow, governance)
What to change first to move faster: the work, not the tech