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David Allison is a world-renowned scientist and award-winning scientific writer who has spent more than two decades at the forefront of obesity research. In this episode, David joins for his third appearance on The Drive to bring clarity to one of the most contentious topics in modern nutrition—protein. He explores the historical pattern of demonizing macronutrients, the origins and limitations of the RDA for protein, and what the evidence really says about higher protein intake, muscle protein synthesis, and whether concerns about harm are supported by actual data. He also discusses the challenges of conducting rigorous nutrition studies, including the limits of epidemiology and crossover designs, as well as conflicts of interest in nutrition science and why transparency around data, methods, and logic matter more than funding sources. The episode closes with a discussion on processed and ultra-processed foods, the public health challenges of tackling obesity, and whether future solutions may depend more on drugs like GLP-1 agonists or broader societal changes. This is part one of a two-part deep dive on protein, setting the stage for next week’s conversation with Rhonda Patrick.

We discuss:

• The cyclical pattern of demonizing different macronutrients in nutrition and why protein has recently become the latest target of controversy [3:15];
• The origin and limits of the protein RDA: from survival thresholds to modern optimization [6:30];
• Trust vs. trustworthiness: why data, methods, and logic matter more than motives in science [13:30];
• The challenges of nutrition science: methodological limits, emotional bias, and the path to honest progress [17:15];
• Why the protein RDA is largely inadequate for most people, and the lack of human evidence that high protein intake is harmful [30:30];
• Understanding the dose-response curve for muscle protein synthesis as protein intake increases [45:15];
• Why nutrition trials are chronically underpowered due to weak economic incentives, and how this skews evidence quality and perceptions of conflict [48:15];
• The limitations and biases of nutrition epidemiology, and the potential role of AI-assisted review to improve it [56:15];
• The lack of compelling evidence of harm with higher protein intake, and why we should shift away from assuming danger [1:04:15];
• Pragmatic targets for protein intake [1:09:30];
• Defining processed and ultra-processed foods and whether they are inherently harmful [1:16:15];
• The search for a guiding principle of what’s healthy to eat: simple heuristics vs. judging foods by their molecular composition [1:25:00];
• Why conventional public health interventions for obesity have largely failed [1:38:15];
• Two ideas from David for addressing the metabolic health problem in society [1:42:30];
• The potential of GLP-1 agonists to play a large role in public health [1:46:30]; and
• More.

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In this special episode of The Drive, Peter addresses the recent headlines linking acetaminophen (Tylenol) use during pregnancy to autism in exposed children. Recognizing the confusion these claims have sparked among patients, listeners, and the broader public, Peter uses this episode to provide a framework for thinking critically about complex conditions and the research related to them. He highlights the dramatic rise in autism diagnoses over recent decades, noting that multifactorial conditions rarely have a single cause, and emphasizes the importance of resisting oversimplified explanations. Peter also stresses that humans are not naturally wired for scientific thinking, making disciplined frameworks like the Bradford Hill criteria essential for evaluating causality in epidemiology. Ultimately, he uses this framework to explore the evidence surrounding acetaminophen use during pregnancy and its potential link to autism.

We discuss:

• Laying the groundwork for this discussion, the rise in autism rates, and the value in using frameworks [1:00];
• The FDA pregnancy drug categories, where Tylenol falls within that framework, and a structured method for evaluating scientific evidence and causality [6:00];
• What exactly are the claims being made about acetaminophen and autism? [13:45];
• The increase in autism rates and why so many things are being linked to autism: the multiple comparisons problem [15:00];
• Evaluating the review paper that triggered the recent concern over acetaminophen and autism [21:45];
• Breaking down the largest studies on prenatal Tylenol exposure and autism: is there a causal link? [35:00];
• Why observational studies can’t prove causality, the role of confounding variables, and the importance of frameworks like the Bradford Hill criteria [43:30];
• Applying the Bradford Hill criteria: testing the case for Tylenol and autism [45:45];
• Putting it all together to answer the question: Does acetaminophen use during pregnancy increase the risk of autism? [56:15];
• If autism risk is overwhelmingly genetic, what explains the dramatic rise in autism diagnoses? [59:15];
• Other risk factors for autism: parental age, maternal health, environment, and where Tylenol fits in [1:09:15];
• Medication use during pregnancy: balancing risks, benefits, and FDA categories [1:15:15];
• Considerations for taking Tylenol during pregnancy [1:19:30];
• Final thoughts: critical thinking, balanced risk assessment, and the importance of context when evaluating medications like Tylenol during pregnancy [1:22:30]; and
• More.

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Joe Liemandt is a software entrepreneur turned education reformer who left Stanford in 1989 to found Trilogy, a highly profitable private software company, before pivoting to transforming K-12 learning. In this episode, Joe shares how he transitioned from leading a global software enterprise to becoming principal of Alpha School, where his focus is building a mastery-based, individualized education model that leverages AI as the missing infrastructure for large-scale change. He details the shortcomings of traditional K-12 education, explains how Alpha replaces conventional seat time with focused academics, and outlines the role of AI tutors and human coaches in helping students accelerate through material. Joe also discusses early results, the data-driven systems that track progress, and his ambitious plan to reach a billion children in the next 20 years by combining cutting-edge technology with proven learning science.

We discuss:

• Joe’s early interest in AI and the story of how he quit school to build Trilogy [4:45];
• Joe’s first encounter with Alpha School and how it sparked his journey into education innovation [8:15];
• America’s declining K-12 performance and the hidden power of mastering fundamentals [13:00];
• How traditional time-based grade progression undermines later learning, and how mastery-focused instruction can transform student achievement [20:30];
• Motivation as the key to high-level learning: how Alpha School fosters motivation with its “Timeback” model and leverages AI to accelerate learning [28:45];
• Core principles of learning: how high standards, mastery-based instruction, and supportive struggle foster both academic excellence and personal growth [35:45];
• Breaking down self-imposed limitations with foundational skills, defined time requirements, and a mastery model [41:15];
• Using short-term extrinsic rewards to help students overcome limiting beliefs and ignite lasting intrinsic motivation [46:45];
• $100 for 100: a simple but powerful incentive system that helps students fill academic gaps and master fundamentals [53:45];
• How AI is the pivotal technology that can finally allow proven learning science to scale and unlock unprecedented student potential [57:45];
• The emergence of generative AI that catalyzed Joe’s billion-dollar investment in education [1:09:45];
• The path and obstacles to integrating Alpha’s AI-powered model into mainstream education [1:12:00];
• Reimagining schooling from the ground up across five key dimensions [1:22:30];
• The potential of this educational approach to reduce inequality in academic success [1:30:00];
• Why the biggest challenge to scaling Alpha’s AI-driven education is cultural adoption and systemic redesign [1:34:00];
• Peter’s daughter’s experience at Alpha School [1:38:30];
• Alpha School’s expansion plans and need for people and resources for maximum impact [1:42:30]; and
• More.

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