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12 Apr

The difference between experts and novices

There's a world of difference between experts and novices. And I'm not talking about the obvious difference in skill level or experience. There are some characteristics of experts that set them apart from the rest of us — qualities that, if you understand them, might help you become one yourself.

One key distinction between experts and novices is that experts have a knack for asking questions on the right level of abstraction.

They know how to zoom in and out, finding the appropriate level of detail for the problem at hand. They don't get stuck in the weeds, but they also don't float around in the clouds of high-level concepts without grounding themselves in reality. This ability to navigate between the abstract and the concrete allows them to see the forest for the trees, grasping the essence of a problem while staying connected to the details that matter.

Consider the example of a seasoned software engineer tackling a complex coding problem. An expert in the field might first analyze the problem from a high-level perspective, identifying the overall structure and organization of the code. They might ask questions such as, “What is the overall architecture? How do the different components interact with each other? Are there any obvious bottlenecks or inefficiencies?”

Once they have a grasp of the bigger picture, the expert engineer can then zoom in on specific areas of the code that need improvement or optimization. They might ask targeted questions like, “How can I refactor this function to improve its performance? Are there any data structures that could be better utilized in this situation? Are there any edge cases that have not been accounted for?”

In contrast, a novice programmer might become overwhelmed by the complexity of the problem and either get lost in the minutiae of the code or fixate on high-level concepts without ever diving into the details. They might spend hours poring over individual lines of code without making any progress or waste time debating the merits of different programming paradigms without actually implementing any changes.

The expert's ability to fluidly move between different levels of abstraction allows them to quickly identify the most important aspects of the problem and zero in on the areas that need the most attention. By asking the right questions at the right level of detail, they can efficiently navigate the complexities of the problem and arrive at a solution that is both elegant and effective.

A key question to ask here is, “How can I break this problem down into smaller, more manageable questions that I need to answer in order to tackle this problem comprehensively?” Experts are adept at decomposing complex problems into simpler components. Practice this skill by identifying the key elements of a problem and addressing them one by one.This is also how experts build clarity around the job to be done. They don't keep asking “Why?” and get stuck there. They ask, “For what purpose?”

This focus on the ultimate goal helps them prioritize which questions to answer first, ensuring that their efforts are aligned with the outcomes that matter most.

Another difference is that experts aren't overly precise where precision isn't possible.

They understand that in many domains, there are no perfect answers or formulas. Instead, they focus on developing a deep understanding of the underlying principles, heuristics or rules-of-thumb and using that understanding to make informed decisions, even when the situation is uncertain. This pragmatic approach allows them to adapt to changing circumstances and navigate the gray areas that are often present in real-world problems.

In this context, Charlie Munger, the vice-chairman of Berkshire Hathaway, and a highly respected investor and thinker, has often emphasized the importance of understanding the limits of one's knowledge. He often quotes the 19th-century mathematician and philosopher Carl Jacobi, who advised, “Invert, always invert.” By turning a problem upside down and thinking in negative space, Munger suggests that we can gain a better understanding of the limits of our knowledge, identify areas where precision may not be possible or desirable, and focus on minimizing bad outcomes instead of maximizing good ones.

Similarly, Nassim Taleb, the author of The Black Swan and Antifragile, has spoken extensively about the limitations of precise predictions and models, especially in the face of complex, unpredictable systems. He argues that it is more important to focus on building robustness and resilience in the face of uncertainty, rather than seeking false precision or relying on overly simplistic models. Taleb's concept of ‘antifragility’ emphasizes the importance of adapting and even thriving in the face of volatility, randomness, and uncertainty.

Both Munger and Taleb highlight the importance of recognizing and embracing the inherent uncertainty present in many domains. By doing so, experts are better equipped to make informed decisions and navigate the complexities of real-world problems, without falling into the trap of seeking unattainable precision where it isn't possible or advisable.

In fact, this is a heuristic I commonly use at Stoa during interviews to weed out the experts from the amateurs. By posing the candidate with a business problem with no clear answers and tough trade-offs, I try to see whether they ask follow-up questions to understand all the variables involved better or if they quickly jump to a cookie-cutter answer that might sound smart but doesn't fly in the real world.

The key question that an expert asks here that the novice misses out on is “What assumptions am I making, and are they valid?” Continually question your assumptions and be willing to challenge them. This will help you avoid falling into the trap of relying on contextless platitudes and truisms, and it will also encourage you to enquire further and not sound like the average business school bullshitter.

Experts understand the importance of trade-offs and resource constraints.

They recognize that every decision has consequences and that there are often no perfect solutions — only trade-offs between competing priorities and limited resources. This awareness of the inherent limitations and complexities of real-world problems enables them to make more informed, nuanced decisions.

This also helps them not be armchair experts who opine and suggest solutions with half-baked knowledge.

The expert starts by asking questions; the novice starts by suggesting solutions.

Finally, remember that expertise is not a static state, but rather a dynamic one.

The path to becoming an expert is not a straight line from abstraction to mastery. Instead, it's a winding, iterative journey that requires a willingness to dive deep into the details, to experiment and fail, and to constantly refine your understanding of the domain.

As you climb the ladder of mastery, your mental models will evolve, and your ability to identify patterns and draw connections will improve. But the journey never ends — there's always more to learn, more nuance to uncover, and more ways to deepen your expertise.

So if you aspire to become an expert, take a cue from those who have come before: embrace the complexity of your domain, be willing to get your hands dirty with the details, and never stop learning. In time, you may find yourself among the ranks of those rare individuals who can truly call themselves experts — those who have mastered the art of navigating the intricate dance between the abstract and the concrete, the theoretical and the practical, and who continually push the boundaries of what's possible in their chosen field.

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