Lessons from Cedric Chin

Cedric Chin, the operator and writer behind the influential blog Commoncog, has become a go-to source for those looking to accelerate their business expertise. His work delves into the nuances of skill acquisition, decision-making, and the often-misunderstood nature of knowledge in complex fields. By questioning popular concepts and digging into academic research, Chin offers a more grounded approach to professional mastery.

On Tacit Knowledge and the Limits of Frameworks

Chin's most significant contribution is arguably his popularization of the concept of tacit knowledge—the kind of knowledge that is difficult to write down or articulate. He argues that the most valuable expertise is of this nature, and it cannot be learned from books alone.

On the nature of tacit knowledge: "Tacit knowledge is knowledge that cannot be captured through words alone." [1]
How tacit knowledge is acquired: "Tacit knowledge instruction happens through things like imitation, emulation, and apprenticeship. You learn by copying what the master does, blindly, until you internalise the principles behind the actions." [1]
The illusion of simple explanations: "If you ever hear someone explaining things in terms of a long list of caveats, the odds are good that you're looking at tacit knowledge in action." [1]
The expert's "feeling": When you ask an expert how they made a decision, they'll often say "it just felt right." This isn't a cop-out; it's the manifestation of deeply internalized, tacit knowledge. [2]
The problem with frameworks: Smart operators know that the way an expert operates isn't fully captured in the framework they articulate. The real value is in the unarticulated knowledge in their head. [3]
The failure of "first principles" in messy domains: "Experts in ill-structured domains reason by comparison to previous cases, not by reference to first principles." [1]
Context is king: "You can't easily reduce cases in ill-structured domains into generalisable principles. You often have to treat the case as its whole thing." [1]
The trap of articulate advice: "People who are smart who can write really well who sound very convincing but have never done the thing they can give you an incredibly detailed picture about things that don't matter. And then you will waste like months of your life." [4]
The limits of deliberate practice: "Deliberate practice can only exist in fields like music and math and chess." For complex domains like business, it's less applicable. [1][5]
The alternative to deliberate practice: "The process of learning tacit knowledge looks something like the following: you find a master, you work under them for a few years, and you learn the ropes through emulation, feedback, and osmosis — not through deliberate practice." [1]

On Mental Models and True Expertise

While a fan of mental models, Chin warns against what he calls the "Mental Model Fallacy"—the belief that one can achieve mastery simply by reading about and memorizing a list of models.

The Mental Model Fallacy: "Successful, effective people make good decisions and achieve successful outcomes in life because they have better mental models. Therefore, the secret to achieving successful outcomes in business and in life is to distill their mental models into written principles, and then learn them. The second half of this assertion is false." [6]
The most valuable models are tacit: "The most valuable mental models do not survive codification. They cannot be expressed through words alone." [6]
Expertise is about building embodied models: An expert doesn't just see financial statements; they see "an embodied model of a company, a place that he can navigate in his mind as surely as you or I might navigate a room." [6]
Mental models are not optional: "Mental models aren't something that we can choose to use. They're not a 'thinking style'. They are at the very heart of how we function as human beings." [7]
The purpose of a mental model: A mental model is a "simplified representation of the most important parts of some problem domain that is good enough to enable problem solving." [7]

On Business Expertise and Decision-Making

Chin, drawing from the research of Dr. Lia DiBello, champions a "triad" model of business expertise, emphasizing the interplay between a company's internal and external realities.

The Business Expertise Triad: Good businesspeople have a working mental model of three core areas: Operations (how to make things), Market (how to sell things), and Capital (how to finance it all). [8][9]
It's about the interactions: "The best businesspeople understand the interactions between all three legs of the triad for their specific industry." [8]
Cognitive Agility is key: A critical component of business expertise is "your ability to update your beliefs in response to new information." [9]
Business is a verb, not a noun: Inflexible mental models can be disastrous when markets change. The ability to adapt is paramount. [9]
The reality of business: "In business, every situation you encounter is going to be somewhat unique. In such a context, the way concepts show up are going to be highly variable." [10]
The flaw in "playbooks": As CEO Frank Slootman says, "There are no playbooks. Everything is contextual." [10]
The purpose of business: Quoting Peter Drucker, Chin emphasizes, "the purpose of a business is to create and keep a customer." This is the foundation of demand. [11]
First-time vs. second-time founders: "First time founders talk about product, second time founders talk about distribution." This highlights the importance of understanding demand. [11]
On believability: When taking advice, seek out people with a track record. "Believability as as as sort of tightly defined is the person has three examples of successes in the thing that you're asking them for." [4]
Learning from the non-articulate: Pay close attention to the advice of experienced, "School of Hard Knocks" businesspeople, especially when they have skin in the game. Their intuition is highly valuable, even if they can't explain it perfectly. [4]

On Learning and Skill Acquisition

Chin's work is a practical guide for those who want to get better at what they do, especially in fields without clear-cut training paths.

The goal of Commoncog: "The primary recipe here is 'take interesting idea that seems to be useful, try it out in a real business, and then write up the results'." [10]
Learning from experts: The challenge is to extract the tacit models from the heads of experts and turn them into effective training methods. [9]
Naturalistic Decision Making (NDM): Chin champions the field of NDM, which studies how people make decisions in real-world settings, as a source of practical tools for skill acquisition. [2]
Applied Cognitive Task Analysis (ACTA): This is a specific NDM technique that can be used by practitioners to deconstruct and understand an expert's tacit knowledge. [2]
Focus on cues and actions: When trying to learn from an expert, "focus primarily on the cues and the actionable strategies that the expert uses" as these provide hints to their underlying mental models. [7]
The power of case studies: Experts "do a lot of their reasoning by combining fragments of prior cases they've seen. The more types of cases they've seen, the more prepared they are." [10]
Reading for calibration: Famous investors like Buffett and Munger read extensively "not to learn lessons: they're doing it to calibrate their expectations of what can happen — by looking at what already has." [10]
The learning process in messy domains: "You have not only to learn from experience but learn the right things from experience in the context of that experience." [5]
The value of immersion: Sometimes the best way to learn is through "total immersion" – just being around and observing experienced practitioners. [5]
On finding a mentor: You want to find an expert who can teach, but recognize that their explanations are just the start. The real learning comes from doing and getting feedback. [1]

On Data and Operations

Chin advocates for a more practical, operations-focused approach to using data, moving beyond simplistic dashboards to genuine process improvement.

The problem with variation: Most founders don't look at data because they "learn from talking to the customer. Because when you talk to the customer there's no problem of variation there's no wiggling. You get actual information that is predictive that is knowledge." [4]
A tool to see through the noise: An XMR chart is a statistical process control tool that "tells you when something that you've done X has actually changed the pattern of wiggling in your numbers." [4]
The power of knowing what worked: Having a tool that confirms a change has had a real impact gives you the confidence to "move on to the next experiment." This clarity is everything. [4]
Two weapons for learning: With statistical process control, "you don't just have to rely on qualitative interviews. You can also have an ability a tool that tells you when something has changed after you've made that change." [4]
Becoming data-driven: It's not about looking at dashboards, but about understanding routine vs. exceptional variation in your processes and knowing when an intervention has made a real difference. [4]

On Mindset and Personal Growth

Underlying all of Chin's work is a philosophy of intellectual humility and relentless, practical self-improvement.

The importance of humility: Recognize the limits of your own knowledge and the vastness of what can be learned from others, especially those with direct experience. [12]
Questioning conventional wisdom: Chin has built a reputation for "questioning conventional wisdom and offering grounded approaches to mastering business skills." [12]
The danger of knowledge shields: Be wary of early lessons that were useful but are now holding you back from reaching the next level of mastery. [13]
Cognitive transformation: The process of "re-encode[ing] old lessons after you got up in skill level so that you can let go of the things that you originally learned that were wrong." [13]
On being a "business biologist": Treat businesses like organisms and try to understand how their environments have shaped them and why they are adapted to their particular niches. [13]
The value of doing: Chin's own journey involved identifying his weaknesses (like marketing and sales) and deliberately setting out to learn them through practice. [9]
Selling to situations: "You're Always Selling to a Situation, Not an ICP (Ideal Customer Profile)." This focuses on the context and "job-to-be-done" rather than abstract personas. [14]
A vaccine for AI anthropomorphism: He advises resisting the urge to think of large language models as friends, sentient beings, or gods to be treated with undue reverence. [14]
On staying open-minded: Be willing to challenge your own deeply held beliefs, whether about business strategy or new technologies like crypto, to avoid becoming cognitively inflexible. [13]
The lifelong learner: Chin's career reflects a commitment to being a "thinker, doer, and lifelong learner committed to making business knowledge accessible and actionable." [12]

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