A $10B Hedge Fund’s AI Playbook (Best of the Pod) (1h 7m)

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• Release date: 2026-08-26
• Listen on Spotify: Open episode
• Episode description:

  Will England is the CEO of Walleye Capital, a hedge fund managing nearly $10 billion in assets. An engineer by training with a math background from Oxford, he has spent his career at the intersection of machines and markets—and has made AI fluency mandatory for all 400 employees.England believes refusing to use AI is like refusing to use the internet in 1995 because it wasn’t perfect. His use of AI is public and effusive, including in a firm-wide email that opened with “I used ChatGPT to write this email. You should be using it, too, and be proud of it.” AI informs how Walleye drafts memos and selects stocks.On Every’s AI & I, Dan Shipper spoke with England about why he’s betting his entire organization on AI, why “results are what matter” more than blood, sweat, and tears, and what the American frontier can teach us about leading through technological change.Like, subscribe, comment, and share!To hear more from Dan Shipper:Subscribe to Every: https://every.to/subscribeFollow Dan Shipper on X: https://twitter.com/danshipperGo to https://attio.com/every and get 15% off your first year. Timestamps:0:00 Start0:51 Introduction3:25 What pushed Will to go all in on AI15:15 Inside the ‘AI-first’ memo Will shared at Walleye17:02 Why you shouldn’t be afraid of using AI for work31:25 How Will uses LLMs to sharpen his thinking35:57 Walleye’s approach to using AI to reduce risk39:35 What history can teach us about leading through change57:10 Will’s first principles for making better decisions59:23 Why Will journals every day—and how AI makes it easierLinks to resources mentioned in the episode:Will England/Walleye Capital: https://walleyecapital.com/bio/will-englandEvery’s AI tools—Monologue, Cora, Spiral, and Sparkle: https://every.to/studioEvery’s AI consulting: https://every.to/consulting

Summary

• 🚀 CEO-Led AI Culture Shift: A hedge fund CEO mandates AI training and leads by example with an inspiring ‘all-in’ memo, transforming organizational resistance into rapid adoption and measurable productivity gains.
• 🧠 AI as Job Enhancer, Not Threat: Reframing ChatGPT use as essential ‘operating leverage’ rather than cheating helps employees overcome fear, focusing on higher-level thinking while leaders provide training and tools.
• 📊 Data Lake & Collective Intelligence: Recording all meetings and documents into a searchable ‘Borg’ system allows LLMs to synthesize insights, boosting analysis in quant trading, risk management, and across departments.
• 📜 Historical Lessons for AI Transitions: Drawing parallels to the post-Civil War era of rapid change (railroads, barbed wire), the discussion highlights how embracing new tech prevents obsolescence and enables thriving amid disruption.
• ⚖️ First Principles & Incentives: Timeless principles like aligning incentives, intellectual honesty, and measuring what matters remain crucial; AI amplifies their power by freeing time for deeper thinking and better decisions.

Insights

• How can a CEO’s personal conviction and hands-on leadership accelerate AI adoption across an entire organization?
  • Time: 0:13 – 15:51
  • Answer: Speaker 2, as owner-operator of a $10B hedge fund, wrote a firm-wide memo declaring ‘Walleye is all in on AI’ and made training mandatory, leading by example to shift culture from fear to enthusiasm. This top-down approach with incentives like leaderboards and tool suggestion rewards unlocked rapid productivity gains. It shows leadership tone is essential for overcoming resistance in larger firms.
• Why should professionals treat AI tools like ChatGPT as essential productivity enhancers rather than academic shortcuts or threats to their jobs?
  • Time: 13:17 – 18:55
  • Answer: The memo explicitly states ‘Using ChatGPT is not cheating’ and compares refusing AI to rejecting the internet in 1995, framing it as a ‘magical elixir’ for 20%+ efficiency. This mindset shift addresses anxiety by redefining jobs to include AI fluency, with leaders responsible for training staff. It emphasizes results over effort in real-world business contexts.
• How can systematically recording and synthesizing all organizational data create a ‘collective intelligence’ that augments human decision-making?

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