The Polymath

Achintya Krishnan

Join me on The Polymath in learning about a diverse range of topics in easy to understand podcasts to uncover complicated topics.

  1. 6 de ago.

    Reversibility: Decisions You Can and Can't Undo

    Hernán Cortés burned his ships on the coast of Mexico, eliminating retreat for 600 soldiers facing an empire of millions. That's the most extreme irreversible decision ever made. But most of us make irreversible decisions every day without realizing it—and paralyze ourselves over reversible ones. Reversible decisions deserve speed. Irreversible decisions deserve caution. Jeff Bezos built Amazon's decision culture on this: Type 1 (irreversible) vs Type 2 (reversible). We'll show you the full spectrum of reversibility, why we get it wrong, tools for irreversible decisions (pre-mortem, 10/10/10, seeking disconfirming information), and tools for reversible decisions (default to action, small bets, review points). Connects to asymmetry, probabilistic thinking, opportunity cost, and optionality. Move fast where you can recover. Think deeply where you can't.

  2. 20 de jul.

    Episode 39: Scale: Why Size Changes Everything

    A giant sequoia and a blade of grass need the same things—sunlight, water, nutrients. Same inputs. Completely different organism. That's scale. And it changes everything—not just how big something is, but how it fundamentally works. We'll explore the square-cube law (why ants can carry 50x their weight but giant ants couldn't walk), how cities scale superlinearly (double the population, more than double the innovation AND the crime), why companies hit structural walls at certain sizes (the Dunbar Number, startup vs corporation dynamics), how expertise compresses non-linearly, and how habits transform into identity at the scale of decades. The rules that work at small scale break at large scale—and vice versa. Cities aren't big towns. Corporations aren't big startups. The human body isn't a scaled-up mouse. Connects to asymmetry (scale creates disproportionate returns), feedback loops (behave differently at different scales), network effects (value grows superlinearly), and systems thinking (emergent properties change with scale). Understanding scale is understanding why what works here fails there—and that's one of the most powerful insights in existence.

  3. 14 de jul.

    Episode 38: Asymmetry: Why Equal Inputs Don't Mean Equal Outputs

    One match starts a wildfire. One decision at 25 shapes an entire career. One habit compounded over 30 years determines your health at 60. Small inputs create massive outputs. Large inputs sometimes create nothing. The relationship between effort and result is almost never equal—and this asymmetry has structure you can understand and exploit. We'll show you where asymmetry comes from (compounding, network effects, leverage, tipping points, power laws), why asymmetric risk/reward is the foundation of great decisions (limited downside, uncapped upside), how information asymmetry creates compounding advantage, why most people quit too early (value lives past the threshold), and how a small number of decisions have disproportionate impact on your life. Combine with opportunity cost (compounding paths vs linear ones), marginal thinking (asymmetric returns on effort direction), skin in the game (seek asymmetric stakes), and second-order thinking (asymmetry lives in downstream effects). The biggest wins don't come from working harder. They come from finding situations where small inputs produce massive outputs—then positioning yourself there.

  4. 8 de jul.

    Episode 37: Skin in the Game: Why Stakes Matter

    The single best predictor of whether advice is worth taking isn't credentials or confidence—it's whether the person giving it has something real to lose if they're wrong. Skin in the game means bearing the consequences of your own decisions. When you do, incentives align, decisions improve, and true beliefs become visible through actions. It's missing everywhere: fund managers collect fees whether you win or lose, politicians make policies they don't live under, pundits give predictions with no accountability, consultants give advice and leave before consequences arrive. We'll show you how to evaluate who has skin in the game, how to choose advisors structurally aligned with your interests, how to add stakes to your own decisions to sharpen thinking, and how to design systems that align consequences with decision-makers. Combines with incentives (skin in the game creates right incentives), circle of competence (consequences force genuine competence), probabilistic thinking (calibration requires accountability), and second-order thinking (consequences extend your horizon). Hammurabi knew it in 1750 BC. Most institutions still haven't learned it.

  5. 30 de jun.

    Episode 36: Circle of Competence: Knowing What You Don't Know

    Warren Buffett is one of the greatest investors ever—not because he knows everything, but because he knows exactly what he knows and refuses to go outside it. That's the circle of competence: the area where your understanding is deep enough to make reliable judgments. We constantly violate it because success breeds false confidence, familiarity feels like understanding, social pressure makes us fake expertise, and we can't see our own blind spots. We'll show you how to map your circle (be honest about how you know what you know, find the edges through failure, talk to people who know more), how to use it (high-stakes decisions inside, defer to genuine experts outside, be explicit about gaps), and how to expand it (first principles, real-world application, discomfort of being a beginner). Combines with the map/territory distinction, probabilistic thinking, and inversion. Confidence without competence is dangerous. This is how you know the difference.

  6. 9 de jun.

    Episode 35: The Map Is Not the Territory: Models vs Reality

    Every model is a simplified representation of reality—and that's both its power and its limitation. A map of San Francisco shows streets and landmarks, but not the smell of sourdough, the fog, the hills, the culture. The map is useful because it's simpler than the territory, but it's never the same as the terrain. We confuse maps with territory when models become invisible, precision feels like accuracy, we optimize for metrics instead of outcomes (Goodhart's Law), and models create false understanding. Examples: nutrition science (calories vs complex metabolism), personality tests (labels vs fluid humans), business frameworks (structure vs messy reality), economic models (rational actors vs irrational markets), org charts (formal vs informal power). Use models effectively: hold them lightly, check against reality, know what's left out, use multiple models, update them, zoom appropriately. Combine with first principles (go back to bedrock truth), second-order thinking (models miss second-order effects), probabilistic thinking (probabilities depend on model accuracy), and inversion (what if the model is wrong?). All models are wrong. Some are useful. Reality always wins.

  7. 4 de mai.

    Episode 34: Marginal Thinking: The Next One, Not the Average

    Don't think about the average. Think about the next one. Most people ask "Is this good overall?" Marginal thinkers ask "Is the next one worth it?" At a buffet, you've paid $20 for unlimited food. Should you get a third plate? Average thinking: "$6.67 per plate, good deal!" Marginal thinking: "Am I still hungry, or will I regret this?" The cost is sunk. The only question is: is the next plate worth it right now? We'll show you why marginal thinking matters: ignore sunk costs, ask "what changes if I do one more?", recognize diminishing returns (first slice amazing, fifth slice regret), compare marginal benefit to marginal cost. Apply to eating, work (is this next hour productive?), relationships (is this next year valuable?), learning (is this next chapter useful?), business (what does this next hire add?). Combine with opportunity cost (what else could the next one be?), second-order thinking (what does the next one lead to?), and probabilistic thinking (expected marginal return). Decisions are made at the margin, not the average. Think incrementally.

  8. 4 de mai.

    Episode 33: Opportunity Cost: What You're Really Giving Up

    The real cost of anything isn't the price—it's what you could have done instead. Every yes is a thousand nos. Buy a $50,000 car? The cost is $50,000 invested at 7% = $380,000 in 30 years. Spend 3 hours scrolling? The cost is everything else you could have done. Take a safe job? The cost is the risk you didn't take. Opportunity costs are invisible—they don't show up on statements. So we ignore them. We optimize for visible costs (price, time) and miss invisible costs (alternatives, compounding). We'll show you how to make invisible costs visible, compare alternatives not just single options, think in "cost per use AND cost of not using," and consider compounding. Apply to time (your scarcest resource), money (compounds exponentially), relationships (finite depth), career (skills compound), and attention (presence matters). Combine with probabilistic thinking (expected value of alternatives), second-order thinking (what does sacrificing this lead to?), and inversion (what am I NOT giving up?). Every choice has a cost. Choose wisely.

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Sobre

Join me on The Polymath in learning about a diverse range of topics in easy to understand podcasts to uncover complicated topics.

Informações

  • Criado por
    Achintya Krishnan
  • Anos de atividade
    2026
  • Episódios
    40
  • Classificação
    Livre
  • Copyright
    © Achintya Krishnan
  • Site do podcast
    The Polymath