In order to understand an idea, people need to work through the layers of understanding in a simplified, but similar way to how you first did when you discovered the solution. This allows them to test each step along the way until they reach a deeper proof that confirms the idea’s validity. This process is akin to constructing a logical proof, even if it’s done intuitively rather than formally. It is “standing on the shoulders of giants”.
When an answer seems overly simple, people may instinctively doubt it because they haven’t worked through the “proofs” that make the simplicity credible. As they reason through discussion, they’re effectively piecing together the mental steps that satisfy their need for validation. This pattern reflects the cumulative nature of knowledge—each new idea builds upon what is already understood, creating a foundation for accepting new truths.
Mental scaffolding and informal proofs of understanding can provide the structure that makes it easier for others to accept new ideas based on previously accepted knowledge.
To lead a person up to an idea (rather than presenting it outright as a solution) is to build up to it with a mental scaffolding, like an informal math proof, to lead the listener through the process you took to get to the answer.Formal math proofs build upon axioms, but in other areas of life, we don’t have the benefit of those axioms so we have to rely on other building blocks.
In some ways, all reasoning relies on a foundation of prior knowledge and collective beliefs. This concept of mental scaffolding and informal proofs provides us a mechanism to build complex ideas from simpler ones (like the process I’m doing right now in this book).
But mental scaffolding and informal proofs are just one way to help you disseminate your ideas and prevent initial rejection. Here are some other strategies counteract these biases:
Start from First Principles – First Principles thinking periodically breaks down ideas into their core components, questioning assumptions and working back from foundational truths (similar to Working Backwards or Reverse Engineering, which will be discussed later). By resetting to first principles, they can “replant” the Idea Tree when needed, creating space for innovation.
Build in Discussion and Dialogue – Discussing ideas with others can not only satisfy their need for understanding and ultimately accepting the answer, but it also aligns with one of the the 48 Laws of Power by Robert Greene, “Law 31: Control the Options: Get Others to Play with the Cards You Deal,” which emphasizes the importance of framing choices and influencing decisions before they are publicly debated or decided upon.
Seek Elegant Simplicity, not Complex Compromise – Encourage readers to actively seek solutions that are both simple and profound. Explain that simplicity doesn’t mean sacrificing quality; rather, it requires distilling the core of the solution. Recognizing elegant simplicity allows us to see the strength in straightforward answers.
The main idea is to occasionally reflect on how you engage with ideas. Challenge yourself and others to think differently about simplicity and to approach solutions with a mind open to the elegance within straightforward answers.
Have you ever had an idea rejected at first, only to have someone come back to it later and realize its truth? This can be due to The Simplicity Paradox or Initial Rejection Bias.
Initial rejection bias is the phenomenon where the first idea is dismissed by a person or group simply because it is first. And when coupled with the innate suspicion that something simple must be incomplete or inadequate, it further moves a person to reject it.
This can happen with a partner when choosing a name for a baby or with a group of people suggesting places to eat. Often the first thing suggested is rejected due to initial rejection bias.
“The tallest poppy gets cut down” is a proverb that describes the common psychological and social behavior that is often rooted in status quo bias, fear of standing out, or social conformity. Oftentimes the initial proposal is dismissed simply because it’s the first to “stand out.” Additionally, there’s anchoring resistance, where groups avoid the first idea because they worry it will set a fixed direction (a “trunk”) too early.
People often believe the “best” idea must come after careful deliberation. While this is sometimes true, this can lead to good ideas being thrown out in favor of further brainstorming, even when the first suggestion might have been sound.
Only when the initial rejection bias is removed is the group able to accept it, because they have understood what the solution means. Only through exploration and discussion can the group unpack the “deceptive depth” of the simple solution, revealing that its elegance actually stems from a well-rounded understanding—thus overcoming the initial bias.
Knowledge or understanding is often built layer by layer, drawing on foundational ideas that have already been established—similar to how formal proofs build upon axioms and previously proven theorems. In informal reasoning, people rely on a kind of mental scaffolding or internal “proof” process where they validate new ideas based on established beliefs, past experiences, or accepted truths.
Occam’s Razor asserts that simplicity often holds the best answer, yet highlights how simplicity must first prove its merit before being accepted. The idea is to reason to a solution through proofs in a “standing on the shoulders of giants” type of way. We’ll cover that in the next chapter.
Have you ever been part of a group that dismissed an answer because it seemed too simple?
While simplicity is often the hallmark of great ideas, it’s not always easy to recognize. Simple solutions can appear deceptively shallow, leaving us feeling that something so straightforward must lack depth. This bias against simplicity is powerful; in many cases, we reject the simplest answers before fully understanding their value. I call this The Simplicity Paradox.
Once an idea is accepted, it becomes entrenched, but, when ideas are still in their “seed” stage, they’re often brushed aside, especially if they appear too simple.
This phenomenon has been referred to in other areas as “elegant simplicity” or “deceptive simplicity”, which is similar to the heuristic, “Occam’s Razor”, which is where simpler explanations are often preferred, but only after fully understanding the complexities involved.
The Simplicity Paradox states that simplicity often masks the underlying complexity and effort required to truly understand and express something. The paradox lies in the idea that achieving simplicity often demands a deep, complex journey of learning and refinement.
A person with deep understanding can make even complex ideas seem straightforward in their essence. Albert Einstein: “If you can’t explain it simply, you don’t understand it well enough.” (SEE E=mc2.) Blaise Pascal, a French mathematician, physicist, and inventor once said, “I have made this letter longer than usual because I lack the time to make it shorter.”
Richard Feynman,an American theoretical physicist, also spoke about this idea, emphasizing clarity and simplicity as markers of genuine understanding. Feynman emphasized the importance of truly understanding a subject in order to explain it clearly, and he developed what’s known as the Feynman Technique for learning. He believed that if you can’t explain something in simple terms, then you don’t fully understand it.
In his teaching, Feynman encouraged people to break down concepts to the simplest language possible. He argued that, when you really grasp something, you can communicate it without jargon, in a way that anyone can understand. His approach was to keep digging deeper until every aspect of a concept could be explained simply, showing that true mastery means seeing through the complexity to the underlying simplicity.
I remember when I first started a job at a software company and I asked my manager what our software did. He simply said, “It’s field service software.” Not knowing what that meant, I asked him to explain it and then when I, explaining it to others, it would take me around 5 minutes to explain it until one day I too just began saying “It’s field service software.” This is because I finally had the depth of understanding as to what those words mean.
Language itself embodies this paradox, as each word seems straightforward but carries layers of meaning shaped by collective agreement and individual interpretation. It’s as if each word is a distilled vessel of thought, simple on the surface but rich in the depth and history of human understanding.
But what happens when you know you’re right, but your idea is still rejected outright?
Have you ever had someone who didn’t understand why something was the way it was so they wanted to rebuild it? The act of rebuilding it helps them understand it, and they end up building something similar. Oftentimes, as a business analyst I was asked to build something only to discover that it had already been built sometime in the past (I called that an “archelogical find”).
And the solution is temporary because the next person or group to encounter that problem or system will have to learn it too. If the first person or group had just learned or kept the original system operating, it wouldn’t have needed to be rebuilt. I call this the “reinvention fallacy”.
The reinvention fallacy is the act of reinventing something to understand it, which can often take the same amount of effort (or more). This is because they either won’t take the time to learn it or they have a bias that because they don’t understand a system, it must be wrong.
Here are a few cognitive biases and psychological tendencies that explain why this happens:
Ego-Centric Bias: The assumption that because you don’t understand something, it must be flawed or poorly designed. This bias leads to dismissing the value of existing systems in favor of creating new ones.
Not-Invented-Here (NIH) Syndrome: A tendency to distrust or undervalue solutions or systems created by others and instead prioritize rebuilding or creating something from scratch, even if the existing solution is adequate.
Curse of Knowledge (Inverse): This occurs when someone lacking knowledge assumes the system is overly complex or broken, rather than recognizing their own learning gap.
Action Bias: A preference for taking action (e.g., rebuilding a system) over inaction (e.g., learning the existing one), even if action isn’t necessarily the optimal solution. This bias can create a false sense of productivity.
Dunning-Kruger Effect: In its early stages, this effect could explain why someone underestimates the complexity of an existing system and believes they can create something better without fully understanding the original.
Reinvention Bias: This is the “grass is always greener” tendency to favor starting over rather than learning or adapting what’s already there, driven by the mistaken belief that rebuilding will lead to better outcomes or deeper understanding.
But what happens when an idea is first getting started? Oftentimes there is just as much resistance to an idea first getting established. We’ll cover that in the next few chapters.
This is chapter 2 of Think Again, available on Amazon Kindle.
Imagine a logo of one of your favorite brands. More likely than not, it has changed slightly over time, but maintained some elements about it, as if it is on an evolutionary path. Rarely, if ever, is the brand and logo wholly re-invented to look and feel different.
Now there are many branding and marketing reasons for this having to do with brand recognition and goodwill, but it’s a great metaphor for when this type of effect happens in other areas of our everyday lives.
Once an idea is first introduced it often mutates and grows from that first introduction and rarely if ever gets readjudicated or reasoned back from first principles to reimagine it. In this way, the idea is like a tree that once planted, only has one “trunk” and is rarely if ever “replanted”.
I call this “The Idea Tree”.
This concept is a form of idea entrenchment or conceptual path dependency. Both terms describe how ideas, once established, tend to grow and branch without returning to their roots for reevaluation.
Ideational inertia is another way to think of this concept, which borrowing from physics, when objects are in motion, they tend to continue along their established paths unless acted upon by a force (such as critical reassessment).
In either case, without “replanting” ideas, they often keep expanding from a single, possibly outdated “trunk”. This is why reimagining from first principles (and other heuristic thinking methodologies discussed later) are so valuable.
Idea Entrenchment
Idea entrenchment describes the process by which ideas become firmly established and resistant to change. Once an idea becomes entrenched, it’s often taken as a given and rarely questioned, leading people to build upon it without re-evaluating its initial assumptions. This can occur due to familiarity, tradition, confirmation bias, or even from heuristic shortcuts themselves.
In psychology and sociology, this concept is linked to cognitive rigidity, where thinking patterns become fixed. In organizations or societies, entrenched ideas might lead to institutional inertia, where the established ways of thinking or acting persist even if they no longer serve the original purpose.
The Remedy
So what’s the remedy for this? We can look to mental shortcuts, ideas from a heuristic way of thinking to occasionally reimagine from first principles – but another method is to occasionally ask yourself: what could we stop doing, start doing, or change?
This is often referred to as a “stop-start-continue” analysis. This framework is widely used in personal reflection, team retrospectives, and strategic planning. It prompts a person to reevaluate their current actions, identify new opportunities, and retain valuable practices, making it a powerful tool for breaking entrenched ideas and routines.
When paired with reimagining from first principles, stop-start-continue can help a person systematically identify areas for improvement or innovation, creating a balanced approach to rethinking entrenched ideas that have gained ideational inertia. It offers a structured way to question and adjust practices without the overwhelming task of reinventing everything at once.
Revisiting from first principles and the occasional stop-start-continue analysis can help teams and individuals see whether their initial “trunk” of an idea tree still aligns with current goals or whether “replanting” could yield something more impactful.
However, you may find that some ideas do not need to be revisited, but still do get revisited due to a lack of institutional knowledge or a bias against established systems and processes. We’ll cover that in the next chapter.
This is chapter 1 of Think Again, available on Amazon Kindle.
Rethinking, Refining, and Communicating Ideas That Stick: A Guide to Understanding, Shaping, and Sharing Ideas with Clarity and Purpose
What makes an idea stick? Why do some ideas grow and evolve, while others get rejected outright? And how can you communicate your ideas in a way that makes them truly resonate?
In Think Again, you’ll explore the life cycle of ideas—from their inception to their acceptance or rejection. Drawing on concepts like The Idea Tree, The Simplicity Paradox, and initial rejection bias, this book reveals the hidden forces that shape how we think about and share ideas.
Discover practical tools for rethinking entrenched ideas, reimagining from first principles, and overcoming biases that block innovation. Learn how to craft your ideas for maximum impact using strategies like stop-start-continue analysis, mental scaffolding, and Feynman-inspired clarity. Whether you’re solving a problem, designing a brand, or presenting a vision, Think Again provides the mindset and methods to refine and share your ideas with confidence and simplicity.
Perfect for creatives, leaders, and thinkers, this book is your guide to understanding the power of ideas and mastering the art of effective communication in a world where clarity is king.
Psychologist K. Anders Ericsson, a professor of Psychology at Florida State University, has been a pioneer in researching deliberate practice and what it means. According to Ericsson:
People believe that because expert performance is qualitatively different from normal performance the expert performer must be endowed with characteristics qualitatively different from those of normal adults. […] We agree that expert performance is qualitatively different from normal performance and even that expert performers have characteristics and abilities that are qualitatively different from or at least outside the range of those of normal adults. However, we deny that these differences are immutable, that is, due to innate talent. Only a few exceptions, most notably height, are genetically prescribed. Instead, we argue that the differences between expert performers and normal adults reflect a life-long period of deliberate effort to improve performance in a specific domain.[3]
One of Ericsson’s core findings is that how expert one becomes at a skill has more to do with how one practices than with merely performing a skill a large number of times. An expert breaks down the skills that are required to be expert and focuses on improving those skill chunks during practice or day-to-day activities, often paired with immediate coaching feedback. Another important feature of deliberate practice lies in continually practising a skill at more challenging levels with the intention of mastering it.[4] Deliberate practice is also discussed in the books Talent is Overrated by Geoff Colvin[5] and The Talent Code by Daniel Coyle,[6] among others.
Two recent articles in Current Directions in Psychological Science criticize deliberate practice and argue that, while it is necessary for reaching high levels of performance, it is not sufficient, with other factors such as talent being important as well.[7][8]
Behavioral versus cognitive theories of deliberate practice
Behavioral theory would argue that deliberate practice is facilitated by feedback from an expert that allows for successful approximation of the target performance. Feedback from an expert allows the learner to minimize errors and frustration that results from trial-and-error attempts. Behavioral theory does not require delivery of rewards for accurate performance; the expert feedback in combination with the accurate performance serve as the consequences that establish and maintain the new performance.
In cognitive theory, excellent performance results from practising complex tasks that produce errors. Such errors provide the learner with rich feedback that results in scaffolding for future performance. Cognitive theory explains how a learner can become an expert (or someone who has mastered a domain).[4]
Deliberate practice in medical education
Duvivier et al. reconstructed the concept of deliberate practice into practical principles to describe the process as it relates to clinical skill acquisition. They defined deliberate practice as:
repetitive performance of intended cognitive or psychomotor skills.
rigorous skills assessment
specific information feedback
better skills performance[9]
They further described the personal skills learners need to exhibit at various stages of skill development in order to be successful in developing their clinical skills. This includes:
planning (organize work in a structured way).
concentration/dedication (higher attention span)
repetition/revision (strong tendency to practice)
study style/self reflection (tendency to self-regulate learning)[9]
While the study only included medical students, the authors found that repetitious practice may only help the novice learner (year 1) because as expertise is developed, the learner must focus and plan their learning around specific deficiencies. Curriculum must be designed to develop students’ ability to plan their learning as they progress in their careers.
Finally, the findings in the study also have implications for developing self-regulated behaviors in students. Initially, a medical student may need focused feedback from instructors; however, as they progress, they must develop the ability to self-assess.
Practice as maintenance
Skills fade with non-use.[citation needed] The phenomenon is often referred to as being “out of practice”. Practice is therefore performed (on a regular basis) to keep skills and abilities honed.
A term taken from the science writer Steven Johnson, who took it from Stuart Kauffman, that helps explain the origins of innovation. Johnson notes that the next big ides in any field are typically found right beyond the current cutting edge, in the adjacent space that contains the possible new combinations of existing ideas. The key observation is that you have to get to the cutting edge of a field before its adjacent possible – and the innovations it contains – becomes visible.
I felt this book was a good example of that for me because I was just about to write something similar. It seems this is possible because Cal and I both have similar reading habits and a desire to find out how to do what we love. This book builds on principals from Seth Godin, Malcolm Gladwell, Derek Sivers, Daniel Pink, and Reid Hoffman. I will admit that I was a believer in the “passion mindset” and although I thought I was a hard worker, I tended to avoid the mental strain Cal talks about that’s so important to deliberately practice in order to build career capital (these are two terms Cal introduces). This book really does a good job of turning the passion mindset on it’s head while giving you solid, practical advice about how to get the things you want in a job: control/autonomy. The bad news is that it takes a long time, will hurt, and requires a lot of work.
Talk about CIV and UFO Defense
I’m on the cusp of formulating a new way to think about intelligence
I’m thinking about this in terms of a presentation, rather than a blog post, but the general idea is that one way to measure intelligence is a person or system’s ability to cross-reference ideas.
Logic Puzzles
When you were a child, you may have been asked to fill out simple logic puzzles in math class. They were simple rows and columns and a couple of sentences, which you had to fill in using logic.
Imagine if all ideas in the world occupied both all of the columns and all of the rows in a giant logic puzzle and the more ideas are learned, the more columns and rows are added to this puzzle. It is from this idea that I present the following stories.
The Rosetta Stone
Despite being discovered in 1799 by Napoleon’s troops in Egypt, it wasn’t until 1822 that a man named Champollion was able to decode the Ancient Egyptian hieroglyphs, the middle portion Demotic script.
He was only able to do this by cross-referencing not just the Ancient Greek, but also Ancient Coptic and other hieroglyphs found at that time. It was this cross-language connections that ultimately helped decrypt the language.
The First Web App
In 1995 Paul Graham, founder of Y-Combinator, wanted to write an e-commerce application, but didn’t want to write it for Windows. After seeing an advertisement for Netscape, he had an idea to try running his Unix application in a browser.
In order for Graham to create Viaweb as the first web app, Netscape, the World Wide Web, the Internet, and Unix all had to be in place first. It was from these technologies that allowed The Adjacent Possible to occur.
The Adjacent Possible
Innovation in any field are typically found right beyond the current cutting edge, in the adjacent space that contains the possible new combinations of existing ideas. The cutting edge has to exist in a field before its adjacent possible – and the innovations it contains – becomes visible.
This explains why things like the discovery of oxygen or DNA occur at the same time around the world because the tools available to do so become available. However, the existence of technology is not enough, the person has to have the intelligence to connect the pieces together.
The Wright Brothers
By the time The Wright Brothers started working on powered flight, “flight” by gliders was already a thing. The problem was not ‘lift’ – the mechanics of that were known. The problem was in maintaining flight and controlling the aircraft.
Because The Wright Brothers were avid tinkers and ran a bicycle shop, they were able to apply ideas from how a bicycle maneuvers through space and recent developments from lightweight aluminum engines to overcome powered flight.
What is Intelligence?
The ability to cross-reference ideas requires both the knowledge of the ideas and the ability to recall and compare those ideas to each other. The ability to do this as a human generally requires expert domain knowledge or the cross-pollination of ideas across domains in a more holistic view, but some level of depth is required in at least one domain.
Compare this to a computer program that could be programmed to compare ideas at a massive scale. Every time a new paper is published or a new gadget is created, the ‘rows’ and ‘columns’ get bigger and every previous idea can now be compared. The results from a computer program doing this task in a holistic way may result in ideas and outcomes that a human would never come to on their own.
Uploaded on Apr 14, 2008 Lawrence Barsalou PhD Emory University. The human conceptual system contains categorical knowledge that supports online processing (perception, categorization, inference, action) and offline processing (memory, language, thought). Semantic memory, the dominant theory of the conceptual system, typically portrays it as modular, amodal, abstractive, and static. Alternatively, the conceptual system can be viewed as non-modular, modal, situated, and dynamic. According to this latter perspective, the conceptual system is non-modular and modal because it shares representational mechanisms with modality-specific systems in the brain, such as vision, action, and emotion. On a given occasion, modality-specific information about a category’s members is reenacted in relevant modality-specific systems to represent it conceptually. Furthermore, these simulations are situated, preparing the conceptualizer for situated action with the category. Not only do these situated simulations represent the target category, they also represent background settings, actions, and mental states, thereby placing the conceptualizer in the simulation, prepared for goal pursuit. Because the optimal conceptualization of a category varies across different courses of situated action, category representations vary dynamically and are not static. Furthermore, different situations engage different neural systems dynamically when representing a category. Under some circumstances, the linguistic system plays a more central role than simulation, whereas under other circumstances, simulation is more central. Thus, the concept for a category appears to be a widely distributed circuit in the brain that includes modality-specific and linguistic representations, integrated by association areas. Across situations, these circuits become realized dynamically in diverse forms to provide the knowledge needed for cognitive processing. Behavioral and neural evidence is presented to support this view.
One of the biggest challenges in life is balancing the “big picture” with the details. You have to have a macro and a micro view of your life at all times.
In life as in film editing, when you’re working on some minor detail, you have to be thinking about how it fits into everything that has happened before and after.
Everyone intuitively understands that years are actually made up of days and days are made up of minutes, but those people who are able to take those minutes with the year in mind – those are the ones who are the most successful.
Jason Cobb said in his video, Your Ideal Day, “When you design that ideal day and you start living it out, you know what starts to happen? You start to have an ideal week. And then you start having a great month. And then you look back and you say, ‘Wow! Look at the year that we’ve had!’”
You have to be balancing that at all times and just try and keep perspective by going from micro to macro. The people who do that the best are the ones who are the most successful in life.
