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In this episode of Shift AI, Patrick Hillmann, Chief Strategy Officer at Logical Intelligence, joins host Boaz Ashkenazy for a conversation about why the next era of AI cannot be built on probability alone.
Patrick shares his unconventional path into AI, from crisis communications and cybersecurity work at Edelman and General Electric, to steering Binance through its most turbulent years and a major DOJ settlement. At Logical Intelligence, Patrick now works alongside Yann LeCun, a Fields Medalist, and engineers from Meta, Google, and Cruise to build deterministic, energy-based reasoning models.
Patrick explains why LLMs behave like a confident intern, fast and articulate, but wrong in ways you only catch if you already know the answer, and why critical systems like power grids, hospitals, and self-driving cars need a layer of certainty that probabilistic systems cannot provide. He and Boaz dig into Logical Intelligence's benchmark results, including a 98% score on the notoriously difficult Putnam math competition, and a public Sudoku test where their energy-based model, Kona, beat every major LLM combined while running on a fraction of the compute cost.
This episode is essential listening for CTOs, technical leaders, and anyone trying to understand what comes after the current generation of large language models.
Chapters
[00:00] Patrick's Improbable Path: From Grad School to the Front Lines of a Geopolitical Crisis
[02:43] From Binance to Chief Strategy Officer at Logical Intelligence
[02:54] The First Paid Job: Unloading UPS Trucks in 100 Degree Heat
[04:31] The UPS Lesson That Still Shapes How He Thinks About Work
[04:47] Why LLMs Are Confident Guessing Machines, Not Truth Machines
[07:14] The Team Behind Logical Intelligence: A Fields Medalist, Yann LeCun, and Math Olympiad Engineers
[08:55] Is Logical Intelligence Betting Against LLMs?
[10:32] The AI Sandwich: Where LLMs, Reasoning Layers, and World Models Fit
[12:36] The Putnam Benchmark and Why Formal Proofs Don't Get Partial Credit
[15:44] What Is an Energy-Based Model, Really?
[19:54] Eve Badia's 15-Year Path to the Energy-Based Reasoning Model
[22:04] Formal Verification and the Future of Secure Code Generation
[23:33] When Unverified Code Fails: The Molson Coors Ransomware Story
[25:39] Why AI Coding Tools Create Rat's Nests Engineers Can't Debug
[28:53] The Sudoku Test: 98% Accuracy for $4 vs $14,000 for the Leading LLMs
[31:13] ByteDance, China, and the Race for Formal Methods
[33:42] Two Words for the Future of AI: Chaotic Determinism
[37:12] Where to Follow Logical Intelligence and Founder Eve Badia
Connect with Patrick Hillmann
LinkedIn: https://www.linkedin.com/in/crisiscommunications
Connect with Boaz Ashkenazy
LinkedIn: https://www.linkedin.com/in/boazashkenazy/
Email: [email protected]
By Boaz Ashkenazy5
55 ratings
In this episode of Shift AI, Patrick Hillmann, Chief Strategy Officer at Logical Intelligence, joins host Boaz Ashkenazy for a conversation about why the next era of AI cannot be built on probability alone.
Patrick shares his unconventional path into AI, from crisis communications and cybersecurity work at Edelman and General Electric, to steering Binance through its most turbulent years and a major DOJ settlement. At Logical Intelligence, Patrick now works alongside Yann LeCun, a Fields Medalist, and engineers from Meta, Google, and Cruise to build deterministic, energy-based reasoning models.
Patrick explains why LLMs behave like a confident intern, fast and articulate, but wrong in ways you only catch if you already know the answer, and why critical systems like power grids, hospitals, and self-driving cars need a layer of certainty that probabilistic systems cannot provide. He and Boaz dig into Logical Intelligence's benchmark results, including a 98% score on the notoriously difficult Putnam math competition, and a public Sudoku test where their energy-based model, Kona, beat every major LLM combined while running on a fraction of the compute cost.
This episode is essential listening for CTOs, technical leaders, and anyone trying to understand what comes after the current generation of large language models.
Chapters
[00:00] Patrick's Improbable Path: From Grad School to the Front Lines of a Geopolitical Crisis
[02:43] From Binance to Chief Strategy Officer at Logical Intelligence
[02:54] The First Paid Job: Unloading UPS Trucks in 100 Degree Heat
[04:31] The UPS Lesson That Still Shapes How He Thinks About Work
[04:47] Why LLMs Are Confident Guessing Machines, Not Truth Machines
[07:14] The Team Behind Logical Intelligence: A Fields Medalist, Yann LeCun, and Math Olympiad Engineers
[08:55] Is Logical Intelligence Betting Against LLMs?
[10:32] The AI Sandwich: Where LLMs, Reasoning Layers, and World Models Fit
[12:36] The Putnam Benchmark and Why Formal Proofs Don't Get Partial Credit
[15:44] What Is an Energy-Based Model, Really?
[19:54] Eve Badia's 15-Year Path to the Energy-Based Reasoning Model
[22:04] Formal Verification and the Future of Secure Code Generation
[23:33] When Unverified Code Fails: The Molson Coors Ransomware Story
[25:39] Why AI Coding Tools Create Rat's Nests Engineers Can't Debug
[28:53] The Sudoku Test: 98% Accuracy for $4 vs $14,000 for the Leading LLMs
[31:13] ByteDance, China, and the Race for Formal Methods
[33:42] Two Words for the Future of AI: Chaotic Determinism
[37:12] Where to Follow Logical Intelligence and Founder Eve Badia
Connect with Patrick Hillmann
LinkedIn: https://www.linkedin.com/in/crisiscommunications
Connect with Boaz Ashkenazy
LinkedIn: https://www.linkedin.com/in/boazashkenazy/
Email: [email protected]

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