Design and the art of motorcycle maintenance
There’s a book I once read: Zen and the Art of Motorcycle Maintenance by Robert Pirsig. And it just so happens that I ride a motorcycle, too. I started riding before I knew about the book; my dad recommended reading it, but being a 20-something peremptory jerk I called it pretentious, boring, and useless for my craft without even flipping through the few pages. Years later when I finally read it, I realized that most of the things I’ve learned about myself and the world through designing and riding motorcycles were in the book all along.
A friend who taught me how to ride once said, “When you’re driving in a four-wheel casket you’re relying on it to save you if something goes wrong. When you’re riding a motorcycle you’re relying only on yourself.” He said I should think like a paranoiac — as though everyone on the road is actively trying to kill me. There are many things that give the illusion of safety on the road, but riders can’t afford to fall for illusions. We have to be vigilant and constantly observe the ever-changing flow on the road.
There’s a lot of chaos on the road. Cars switch lanes, accelerate and decelerate, things are changing dramatically every split second. Driving patterns are highly unpredictable — you might’ve noticed this when trying to guess which lane is going to move faster in a traffic jam. Overseeing the chaos are few — if any — truly reliable laws or rules on the road. People do random stuff all the time. It’s scary. This is why so many people hate driving, right?
So I want to tell you a story about some parallels between riding a motorcycle and designing products: what I’ve learned about cognition, intuition, and evolution in this constant vortex of entropy we call life.
Internal combustion
I have a complicated relationship with chaos. I’ve grown up to be an insufferable perfectionist and a stickler for the rules. I just loved it when things were organized, when the world around me would neatly fit into a bunch of boxes and shelves in my head.
When I first started playing Dungeons & Dragons as a kid I instantly fell in love with its alignment matrix. It made so much sense! I thought I could instantly tell bad guys from good guys, villains from holy crusaders. Then I told my grandma about it. She read the book carefully through her thick horn-rimmed glasses, and said, “This is bullshit! How can one possibly be chaotic good? Chaos is bad, right? It’s evil!” I agreed with her back then, and I’ve spent the next 20 years organizing, structuring, defining, labeling and designing the world around me. As a designer, I was fighting the chaos by perfecting my craft — all the rules, tools, and best practices I’ve mastered over the years.
Then I started changing and I got on the journey to understand design ethics — learning how to make social good with technology. Society is slow, so making social good means understanding future consequences, not just today’s needs. It’s about predicting the future. And I’m learning that it’s possible, but only to a limit.
It turned out there are infinite futures stemming from every decision I make, and no amount of knowledge or intelligence can process them all. In fact, I started feeling the opposite: the more I’m structuring things, the more I’m desperately fighting the chaos, the harder it gets. All the rules and directions I was mapping for the future were making me anxious and impatient — I wanted THAT future to happen, because hey, I’ve already mapped it out! Things around me were changing really fast, and I was afraid my strategies weren’t up to speed. I was trying to fight chaos by making more detailed strategies, more rules, and guidelines, but that only led to more fear. I was afraid of the ambiguity and complexity of the world around me. I was afraid of chaos.
Chaos is unknown. That’s why my grandma didn’t like it. Known and organized is good, unknown and chaotic is scary and bad. Think about it for a second; what if “order” isn’t a thing? What if we’re evolutionarily programmed to seek patterns in everything for no reason other than it makes us feel safer? What if this entire concept of “order” is just an outdated alarm system, blaring in the solitude of our overgrown brains?
Our hairy ancestors were sitting by the fire, peeking into the pitch-black darkness and getting scared shitless whether there’s a predator lurking nearby. The funny thing is that if the predator would’ve stepped into the light, our ancestors would probably get eaten anyway. But at least they would’ve known! Somehow we’ve conflated “known” with “good”, and anything unknown is, therefore, subject to immediate analysis and categorization.
Our fear of chaos manifested in creating the concept of “order” — organized knowledge. We’ve started accumulating our memories and categorizing them into rules and laws. We slap labels on the scary universe around us to make it safer and more predictable. But it’s all in our heads. These labels aren’t real, they’re based only on our limited knowledge and do not account for chaos — the constant change in everything.
Laws of nature are human inventions, like ghosts. Law of logic, of mathematics, are also human inventions, like ghosts. They exist nowhere except in people’s heads.”
— Robert Pirsig, Zen and the Art of Motorcycle Maintenance
The real question about the laws, and rules, and ORDER as a whole is not whether they exist. The real question is how do we choose to apply them. How are we choosing to live because of them, and how are we affecting the lives of others?
Jennifer Dziura once wrote an amazing thread about the two types of personal morals that drive our decision-making. Basically, there’s a “progressive” or consequential type, where we’re making decisions based on the consequences of prior actions — essentially, reacting to the needs of the people around us. The other, utilitarian or “conservative” type tends to envision solutions, policies, and rules BEFORE arriving at consequences — and deems those irrelevant to the grand vision.
I was that guy for so many years. I thought I’d figured it out. I thought I could devise a plan or a strategy regardless of consequences because it’d work for most people. I’d often cite the 80/20 rule — i.e., my solution is perfect for 80% of people and is, therefore, just.
Take turn signals. Turn signals are “conservative”, they’re an immutable policy by design. It makes sense in theory, but because a lot of people don’t use them, they can no longer be trusted. This policy doesn’t account for consequences. If the car in front of you suddenly shifts lanes without signaling, it’s THEIR fault, right? The rule still makes sense! IF ONLY everyone would just follow it, goddamn it!
Whenever I’ve encountered anything unfamiliar my gut reaction was to classify and organize it. My brain was making sense of chaos by trying to recognize some familiar patterns in it, then ignoring the rest. The former is why we often see faces in the coffee foam — and make stereotypes and biases that often cloud our judgment. The latter is called the Troxler effect and is very dangerous both for designers and motorcyclists.
Fun fact: cars often hit motorcycles parked on large lots among other cars, because the spot appears to be empty. Drivers see an opening and rush to what seems to be an empty spot, and by the time they notice a bike, it’s sometimes too late.
Transmission Systems
Daniel Kahneman’s book, Thinking, Fast and Slow talks about the difference between our two “brains”: System 1 (the fast, intuitive, and highly stereotypical one) and System 2 (slow, analytical, and methodical, albeit very lazy). Our System 1 always kicks in first and provides familiar, yet incredibly oversimplified assessments and categorizations of the reality — all so that our precious System 2 would agree with it and could stay lazy a bit longer.
The categories and stereotypes System 1 comes up with are usually incorrect and biased because they’re based on a very limited dataset — our own knowledge and experiences. And when we’re using these categories we almost always end up overly generalizing and missing some very important nuance, or worse — discriminating, favoring some categories (or people) over others for no real reason.
Isaac Asimov once performed a gender analysis in Brothers’ Grimm fairy tales. There are 16 wicked mothers and stepmothers and only 3 wicked fathers. There are 23 evil witches and only 2 warlocks. 13 females kill or betray men who love them. And only one male character is equally despicable.
We put our stereotypes and biases into our information architecture, into our content strategy and database design, leading to gross algorithmic discrimination and hugely unethical products. But it really starts with us and our own arrogance and ignorance. As Kahneman puts it, our comforting conviction that the world makes sense rests on our almost unlimited ability to ignore our ignorance. Values, decisions, and decision-making processes are more important than the outputs of our design and can perhaps yield more value — adaptive and flexible, more suitable for the world of chaos. Imagine that instead of being information architects we could learn how to be information gardeners?
System 1 is our primary chaos defense mechanism. It prevents us from seeing the reality in all of its incredibly chaotic complexity by offering convenient labels and shortcuts. And it tricks us into believing that complexity can be simplified, chaos can be tamed into order, and everything can be consistently organized.
I think about all the documentation, tech specs, and manuals I wrote over the years. There was never enough! And yet, all of this stuff I wrote to support my beautifully designed artifacts became obsolete the moment I published it. Handoffs and documentation are driven by our desire to freeze time and pretend would stay exactly as it is, and everyone would follow along the Master Plan. If only other people could just follow instructions, damn it!
Most design systems fail because we build them as a tool to categorize the infinitely intricate reality of human experience into overly simplified design patterns and components. We desire consistency for consistency’s sake — because our Systems 2 are lazy, and we, along with them, don’t want to assess reality and deal with chaos every waking hour. We build design systems based on our perception of the past, our existing products and services, preconceived roadmaps and strategies, but we never fully account for the chaos.
How can we learn to create systems that embrace chaos and uncertainty? How can we create systems that inspire, enable, and empower people to be free and creative, rather than inhibiting their infinitely unique behaviors and limiting them to the rules and regulations we prescribe?
Every system we’re designing is predicated upon our prior knowledge — an ephemeral low-resolution snapshot with a very narrow field of view. But the world changes very fast, and our systems are rendered obsolete before we even finish them. Every system we create — every law, every rule, and every structure — inevitably creates unintended consequences. Every human-made system can be “gamed” or exploited.
In physics, highly organized structures make materials hard yet fragile. Hard solids like glass resist small damage and small attacks. But any significant force would smash the fragile system beyond recovery. On the other hand, a fluid system like water adapts, embraces and incorporates small attacks and is capable to recover, restructure, and reshape itself after a significant force.
How can we design more resilient and fluid systems that can react and adapt to the chaos around us, while proactively delivering value to the people?
It’s a first warm day in the spring, and all bikers are out celebrating the start of the new season. The young folks are prancing around on their sportbikes and doing crazy stunts, while the old bearded guys in black leather stand beside their choppers and have a slow relaxing chat. A young biker comes over and says “Hey, we’re all brothers and sisters, right? Let’s organize and get to know each other better!” An old biker sighs, looks him in the eye and says, “Why should we? You’re new every year.”
Traffic patterns
Riding a bike feels very dualistic, just like that. On one hand, I need to think really fast and react to the smallest changes in the environment around me. On the other hand (yes, pun intended), I need to have a goal, a destination I’m going to, and a strategy to get there. Riding a bike requires a constant reassessment of reality, being simultaneously proactive and reactive, it requires absolute mindfulness.
In a car, you can’t really see the road. Your field of view is limited to a small glass frame in front of you. The amount of data that you’re receiving is very limited and quite manageable, almost boring — that’s why we feel like we could use some distractions: some music, a podcast, or even the phone you’re hiding below the wheel hoping that the state trooper you just passed on the shoulder won’t notice. The only thing that matters is right in front, in the dead center of your viewport — the brake lights of the car in front of you.
On a motorcycle, I am the road. I can see, hear and feel everything around. The amount of data that enters my brain is impossible to consciously analyze. My System 2 is too slow for this. But I can’t rely on intuition, my System 1, either — because it’s based on stereotypes, on my prior knowledge about what usually happens on the road, and things could change any time. So what do bikers do? We build decision trees with smart defaults.
With so much stuff going on I have to look at all the things at once without focusing on something in particular. But my attention is finite, I can’t actually monitor all the things at once — I assign certain “attention triggers” or watchpoints to different information streams based on their importance. Instead of trying to analyze the whole thing, I’m relying on my intuitive brain to alert me when that stream yields a particular data point.
Imagine I’m riding in the right lane. I need to simultaneously watch the cars to my left — what if someone decides to switch lanes? I’m watching the car in front of me — in case it decides to stop abruptly. I’m watching the small streets to my right — in case a car suddenly pulls out. And I’m watching the light far ahead too — because when it becomes red, the cars are going to start braking in a chain sequence, and it’d take about three seconds for the car in front of me to start braking too.
But it’s not enough to just set triggers. Because everything is moving so fast, I need to have smart presets as well. If this, then that. If the light goes red, wait three seconds then start braking. If there’s no car on the left, remember there’s a safe spot. If there’s a car suddenly pulling in, AND there was a safe spot previously saved in memory, swerve left. Else, brake.
When I’m riding at 80mph on a crowded highway my brain rapidly calculates dozens of possible maneuvers. Should I switch lanes? Should I speed up or slow down? Each of these decisions has consequences which, in turn, lead to new options. If I speed up to pass this car, I’d have to swerve immediately after to pass that big truck. But hey, there’s a lot of turbulence on the side of that truck, I better grip the bars tighter. My brain constructs a tree of decisions.
Andrea Mignolo describes a similar concept in her Reflections on Business, Design, and Value. Our world consists of chaos. Or, as market traders put it, it’s VUCA — volatile, uncertain, complex, and ambiguous. In order to make better decisions in the VUCA world, traders avoid making too many decisions up front and instead build a binary lattice of iterative decisions.
What if we could predict our product design futures the same way? If we liberate ourselves from having to predict 100% of the future outcomes, we could increase flexibility, decrease risk, and embrace volatility.
All of this is very similar to the futures cone used in speculative design. There are infinite possible futures that are possible right now, and every step we take makes it even more infinite. And this cone thing helps visualize and process at least some of this craziness. Read about it if you haven’t already.
There are two interesting things about the futures cone. One is that it’s a cone, which means it always starts with a first step. Sure, there are infinite future cones that grow from every infinite decision we can make at the moment, but that is too much for us to process. We can only think about the future after we make the first step.
Another interesting thing about the cone is that it’s infinite. The future is infinite. UGH. We can’t deal with infinity. The cone only becomes useful once we define that little green spot. The preferable outcome. In order to process multiple futures, we need a way to tell which particular future is “bad” and which one is “good”. To do that we have to understand why — not even where — we are riding the bike today, what problem are we trying to solve. We need to define the desired outcomes.
A motorcycle ride can be very different depending on whether I’m planning to enjoy the scenic route, or whether I’m trying to make it to a hospital when my spouse is in labor. Similarly, in product design, carefully and iteratively designing the optimal experience, or rushing the development to get first to market sometimes could both be valid outcomes. The former should obviously happen more often — but hey, it’s not every day my partner goes into labor too, right?
Designing for chaos means choosing the problem to solve very carefully and prioritizing our attention.
I’ve realized it’s not worth spending time to think what I’m gonna do after the scenic ride while I’m surrounded by beautiful views that I’m making a point to enjoy. But I can and should plan at least some part of my route while I’m on it to make sure I maximize my desired outcome — in this case, enjoying the ride.
Trying to solve for long-term goals isn’t viable, because as the futures cone goes wider, chances are I won’t get the plan right no matter how hard I think. Solving only for short-term goals isn’t effective, because it might not help me move towards my outcome.
I’ve tried taking a scenic ride in a car with two kids. One minute someone needs to pee, then I have to stop to change the little one to avoid death by toxic suffocation. Then the older one wants to pick the beautiful red and yellow leaves for half an hour. Before I know it, we have to go back and we’re not even halfway through the scenic route. Sure, I could’ve still enjoyed it, but I chose to define the wrong outcome. If my outcome would’ve been “having fun together”, I would’ve nailed it. But if it was about “completing the entire scenic route, start to finish”, so I ended up being mad.
Shifting gears
Riding the chaos is between preventing risks and mitigating consequences. We do that by thinking fast and thinking slow. Thinking fast is reactive, it means making quick intuitive decisions and relying on pre-set cognitive and behavioral patterns. Thinking slow is proactive, it means carefully analyzing the options and calculating different outcomes. Neither way of thinking is sufficient by itself. Life goes too fast to afford thinking slow at all times. And life is too volatile and complex for us to always trust our intuition and prior knowledge.
A biker who only thinks fast is suicidal. A biker who only thinks slow would be better off in a car.
We balance these two things by focusing. When we make a decision, it commits us to a certain short-term branch of our futures tree. Once on the branch, we can start analyzing possible options and calculate the probabilities of future nodes, based on the outcome we want to accomplish. But it’s important to focus our attention only on the current branch because all of the “roads not taken” are no longer relevant — these are the futures that simply haven’t happened and won’t happen again.
The value of risk prevention decreases exponentially with each added node — the further we get into the future, the less sense it makes, and the harder it is to prevent any negative consequences. I’ve noticed that sci-fi increasingly makes no sense, and I can no longer enjoy it. With more and more chaos manifesting around me, it gets harder to suspend disbelief about cyberpunk dystopias and starship utopias alike, because it’s no longer possible to compute all the probability nodes that might lead to those futures.
It gets even harder when I’m trying to plan a shared future, and other people are expected to weigh in. When I’m devising a design or product strategy, I encounter more resistance the further I get into the future. People on my team, my stakeholders, and partners start pushing back on the probability nodes they haven’t computed yet. “Did you think of X? What if it doesn’t work during this step?” There’s a threshold where no amount of expert communication can help me mitigate those concerns and help people “catch up” with my strategy if it goes too far into the future.
We used to play a game when we were kids: motorcycle race on a grid paper. Each turn players draw short lines, representing the movement of their bikes. Each turn you can accelerate (make your line one square longer), decelerate (one square shorter) or maintain the same speed. If you accelerate too much, you won’t be able to fit into the sharp turn ahead and crash into the wall — then you’d have to accelerate from zero again. But if you go too slow, you won’t win the race.
The shape of the track changes every round, so there’s no time to compute the “perfect” algorithm ahead of time — not to mention it’s hardly possible within our average cognitive skills. Most players calculate near-term algorithms just to make it through the nearest turn. Best players would think at least one turn ahead — what if I could still be ahead of everyone even if I accelerate too much, crash, and then re-accelerate again?
Ryan Singer proposes an excellent approach in his book, Shape Up. Think about your design or product strategy as a series of continuous mid-term bets. Short-term bets (e.g., two-week sprints) might not be enough to get anything meaningful done. The bet needs to be long enough to finish a whole project, start to end — but short enough to see the end from the beginning. It is about maximizing the options in the future. You don’t know what will happen in the next six weeks. You don’t know what brilliant idea will emerge or what urgent request might appear. And if you’re making mid-term bets against your previously defined outcome, you can keep moving without losing momentum.
Counter-steering
I spend a lot of time and effort in my design work trying to redefine or challenge the problems I’m facing. This is yet another chaos defense mechanism: it’s easy to believe that if only I could spend enough time understanding the context and the constraints of the problem, it’d make everything easier and I’d end up with a completely different, much more manageable problem. But what if the constraints are too hard and cannot be tackled directly? Some martial arts, like aikido or judo, emphasize using your opponent’s force as a multiplier against them while preserving your own mental and physical energy. Let’s call this one a principle of counter-steering.
Steering the bike is very different from steering a car. What do you do to make a car turn right? You turn the wheel clockwise — or, rather, pull it gently to the right. But when you’re making a high-speed turn on a motorcycle you can’t pull the handlebars — if you do, it would send your bike flying through the air. Instead, bikers (and bicyclists!) use this technique called counter-steering — in this case pushing your right handlebar away from yourself (counter-clockwise) while leaning your body to the right, so that the bike’s angle and the centripetal force would make the turn for you.
What really happens is that bikers give up control to increase traction. This same idea can be useful in design leadership or, more broadly, in any collaborative work involving multiple people. Instead of doubling-down on your ownership of the strategy and control over the execution, just let go. Facilitate, empower, amplify, and catalyze, let the group come up with ideas on their own — even if you might’ve thought of them already. Prioritize influence over control. Sometimes we just need to wait.
Wandering Albatrosses abandon their excessively fat nestlings for several months so that they could starve down to a normal size and be able to get out the nest.
My wife hates following me in a car when I’m riding. The car can never catch-up and follow my maneuvers because bikes turn and switch lanes much faster. But it’s my fault; as a biker in the lead, I have to account for momentum and accommodate a slower-moving vehicle, while still moving in the right direction.
In science, this phenomenon is called hysteresis: a dynamic lag between an input and an output, when the input happens too fast. No amount of preemptive communication can prevent this — I can’t convey all of my future maneuvers, all of the speedups, slow-downs and lane shifts for even a 10-minute drive ahead of time! Pavel Samsonov makes a similar example of managing the momentum. Consider going more slowly or waiting for your slow buddy and anticipating a lag after some fast maneuvers.
Oda Nobunaga, Toyotomi Hideyoshi, and Tokugawa Ieyasu, three famous Japanese shoguns, once saw a bird that refused to sing. Nobunaga warned the bird, “Sing or I’ll kill you.” Hideyoshi coaxed the bird by saying “I’ll teach you to sing.” Meanwhile, Ieyasu sat back and thought “I’ll wait for the bird to sing.”
Stoppie 180
Creative and critical thinking often come hand in hand. Deciding on whether I should spend time and effort analyzing the existing problem constraints or steer around them is very hard. Much like with everything else, there’s hardly a golden rule to follow. If I have enough time, I’m trying to think outside the box first. If I’m wrong, I’d end up validating the initial constraints, but if I’m right, I could end up with something truly innovative.
There are a lot of great stunts on a motorcycle. My favorite one is called Stoppie 180 — when you use your front brakes abruptly, lift your back wheel in the air, spin 180 degrees on the front wheel, then immediately start moving in the opposite direction.
Sometimes by inverting the problem, I can find a solution to something more important than the initial task at hand — because deciding on a problem to solve is what matters the most. To think completely outside the box, I try flipping the problem statement on its head and trying the most counter-intuitive solution first. After all, the easiest way to get stuff outside the box is to simply turn it upside down.
Incandescent light bulbs have the energy conversion efficiency of ~10% — they only convert 10% of energy into the visible light and the rest into heat. This is a pretty horrible efficiency, right? That’s why we’ve switched to LEDs and CFLs. But if we’d simply change a name and call it a heating bulb, all of a sudden it’d have an amazing 90% energy efficiency.
When looking at the problem statement at hand it’s incredibly important to consider what’s NOT in it? Design works best within the hard constraints, and the more strict, direct and rigid the requirements and regulations are, the easier it gets to find an opportunity hidden in plain sight.
The creators of 1976 Mohammad, Messenger of God movie faced a seemingly unsolvable problem — how to film The Prophet when you’re not actually allowed to depict him? The director decided to use a GoPro-like first-person setup to film the events from Mohammad’s point of view.
It’s also important to remember that any requirements and constraints are somehow communicated, and human communication is always chaotic and prone to mistakes and misinterpretation. Too often the constraints become unmanageable simply because they were stated incorrectly. When I feel stuck, I try changing the language I use to define the problem and see if it helps everyone move forward.
During World War II Americans were airdropping thousands of propaganda leaflets over the Japanese forces. The leaflets had one big header: “Surrender”. But it didn’t work, because surrender means eternal shame for a Japanese soldier. After U.S. Army realized it, they’ve changed the message to “saving your family”, “ending the war” and “bringing peace”.
Here’s a great inversion example from Aaron Lewis. Our work calendars are all fucked up, we’re drowning in meetings because the digital calendar apps were designed as white and blank by default, as though our time is unaccounted for. No wonder that everyone tries to “drop something on my calendar” or “put some time in”. What if our calendars would appear as completely full by default — so that everyone would understand they’re taking time away instead?
Brute-forcing
Whenever I’m fixing a bike it’s almost always faster to just try a few options, one after another, instead of spending an hour to Google it or searching through the hefty manual. While patience and strategy work most of the time, brute force can sometimes be more effective — as long as you’re being mindful and balance your slow and fast thinking. Let me tell you a story.
One Laptop Per Child organization did an experiment in two remote Ethiopian villages: they dropped boxes containing tablets with preloaded programs, taped shut, with no instruction. They thought the kids would just play with the boxes. Within four minutes, one kid had not just opened the box — he had found the switch and turned it on. Within five days, they were using 47 apps per child, per day. Within two weeks, they were singing ABC songs in the village, and within five months, they had hacked the Android OS. Someone from OLPC decided to disable the cameras on all the devices, but the kids had figured out what camera does and hacked the Android system to turn it on.
The entire point of various methodologies like design sprints or old-school brainstorming is to iterate through as many ideas as possible before I commit to the most optimal one. Iteration is an amazing technique in both slow and fast thinking modes — depending on whether I can still learn as I’m iterating.
Put a fly and a bee in a glass jar, then lay the jar on its side with the bottom pointed toward a light. The bee will keep flying toward the light, believing that it is the “correct” way out. It never adapts or re-adjusts, and it will die trying. And the fly would just bump into walls randomly until it finds a solution.
A very common misinterpretation of every iterative method is assuming it’s an all-or-nothing process. But it’s obviously not true — we can learn something with every attempt, every step of the way, therefore exponentially increasing the success of each ongoing iteration. Imagine your desired outcome can be visualized as an image. The moment you can see what’s on the image, you’re there. Now think about iterations as gradually increasing the image resolution. If you have just 20 pixels (or 20 ideas), the image doesn’t make any sense — it’s just a bunch of squares. ; if you have 80 pixels (ideas), a shape starts to emerge. And once you reach 200 ideas you start visualizing something real.
Not every brute-forcing is truly iterative; you won’t necessarily learn something every time. But it could still be an effective approach.
Are you rolling your eyes yet? Ok, bear with me. So many times in my life I’ve worked on some content management system or a database, and one of the fields had to be updated throughout the system. 99% of engineers I’ve seen would spend half an hour discussing possible automated solutions, then spend another two hours writing a custom script just to fill out those data fields, this one time. Filling out a field in a consistent data set takes a minute, at most. It means that for any data set with less than 150 elements it’s actually faster to fill it out manually. And I did — and almost every time it was faster than automating it.
Slow drag
Everyone who rides a bicycle knows that it tends to fall down only when it’s moving slowly. It’s much easier to move fast — my momentum and the gyroscopic effect are working for me. But once I’ve inevitably slowed down — the gravity starts reeling in, and I have to work really hard to maintain balance. It is exactly like this in design: much easier to produce tons of siloed work fast in the safe confinement of my team’s design sprints than to slowly and sometimes painfully collaborate with dozens of non-designer stakeholders. I’ve learned to hold my ground and to maintain balance.
There’s a game — or, rather, an exercise — that is practiced by bikers all around the world. I’ve seen people do it in the U.S., in Europe, and even in Africa. It’s called the slow drag. A few bikers start moving in the parallel lanes. You put your feet on the ground, you lose. You finish last, you win.
You can’t win this game if you’re impatient. And you can’t win if you can’t control your bike perfectly — when you don’t know how to apply just the right amount of effort into your throttle and brakes. How to master the ultimate balance between fast and slow, proactive and reactive, thinking fast and thinking slow. Bikers practice this game their entire life — with or without the competitors. Every time I’m approaching a red light I’m trying to slow drag it all the way to the line, so that when green hits I can start moving immediately without putting my feet on the ground.
This stuff is hard, and I was pretty bad at patience and balance myself for many years. When I was buying my first motorcycle, my friends said I should get the red one — so that I’d be more visible on the road. Safer that way. Obviously, I had to get a matching red helmet, then the jacket, backpack, boots, and t-shirts — all red. Before I knew it, I was looking like The Flash — and was acting like one too. I was impulsive and impatient, I could only think fast without thinking slow. When I realized the problem, I decided to try an experiment and started wearing green instead. Maybe it was naive, maybe it was a placebo effect, but hey — it’s working. Now every time I look in the mirror I feel calm and peaceful — and no longer feel an urge to move at 100 miles per hour.
Jared Spool talks about two final stages in our maturity as designers (or, perhaps) wisdom as people: conscious competence and unconscious competence. Too often we get in our own way by dogmatizing the existing best practices and methodologies. We keep arguing about tools, methodologies, and definitions on Twitter, and we keep following the process that might’ve previously worked as a Bible — without realizing that in this volatile and chaotic world things might never work the same way twice, and we should never stop improving ourselves and our partners to make better design decisions.
Flexibility is more important than knowledge.
The key value of a motorcycle is not it’s top speed but rather acceleration and agility, how nimble it is, and how quickly it can react to sudden changes in the environment. And I think we need to learn it ourselves, we have to evolve, as people and as designers, we need to become more adaptive, more creative, and more mindful.
The Rider
We have two systems inside that big head of ours — intuition and cognition, System 1 and System 2 — and they are far from being equals. One is in charge of another, and it’s up to us how we want to change that.
My intuition is a fast motorcycle that roars through the vast plains of chaos without a goal or a purpose. I am the rider.
My self-identity is my conscience. The “I” in me is my mind, my System 2. And it only works when I’m allowing it to. When I’m being mindful. Otherwise, the motorcycle runs free, all by itself.
It’s hard to be mindful. Learning how to think differently — and especially, unlearning what I thought was right before — is extremely hard. Changing myself is hard. It’s not for everyone, and it’s not for every waking moment of my life, which is already filled with tons of problems, sorrows, and stress. Sometimes staying in the slow lane of my life in a comfy car is perfectly fine. Improving myself is a journey into the chaos, into the unknown.
I don’t believe there’s a limit to our self-improvement, how mindful, brave and kind to others we can become. And yet, because the infinity scares us, we diminish ourselves to a combination of knowledge we’ve acquired and the skills we’ve mastered. We are not our skills. We are not our jobs. Our knowledge and our skills become obsolete really fast in a world of chaos.
Everything we can still learn, all of the things we can evolve into are infinitely more valuable than what we know and what we are today.
We are all infinitely creative. If you’ve ever watched Arizona Dream by Emir Kusturica, there’s a fish that doesn’t think, because the fish knows everything. Ironically, we think only when we don’t know. Creative thinking is the only kind of thinking there is. There is simply no other way to think. Only when we don’t already know, we come up with something new. It doesn’t matter if you’ve been a designer for 20 years, or if you just got out of college — we all have the same potential to think, be creative, and evolve ourselves.
The most important thing about designing and living in the world of chaos is always being creative, constantly challenging our reality without relying on the immutable laws and rules that we believe are guiding it and are going to stay the same forever. We don’t even have to memorize things anymore, because we can find an infinite amount of stuff on the internet. Instead, we should prioritize the ability to adapt and synthesize new ideas based on observation.
Creativity, much like riding a bike, is about attention management. Our cognitive brain has a near-infinite capacity to generate new ideas, but it’s very lazy and tends to defer to our intuition and biases whenever we stop being mindful. To be mindful, we need to be very disciplined and remove distractions as much as possible.
What helps you think? Some think better under pressure, some need solitude, and most of us can’t think when we’re hungry. Beethoven poured cold water on his forehead; Agatha Christie did the dishes.
Me? I pace around or ride the bike.
There’s nothing weird in being mindful and maximizing our creative power. Philippe Starck, a famous French industrial designer, likes to say that his creativity comes from being on the autistic spectrum. Being on that spectrum myself I think anyone can be creative and mindful — as long as you keep patiently practicing your ability to focus and ride your thoughts without distractions.
Japanese people embrace wabi-sabi, an acknowledgment that nothing lasts, nothing is finished, and nothing is ever perfect. In the world of chaos, we can never achieve some grand absolute perfection in our life and our work. Instead, we can seek satisfaction and fulfillment by trying to make our every thought and every step the very best they could.
The word “technology” comes from the ancient Greek word techne, which meant both art and craftsmanship. To Ancient Greeks there was no difference between crafting a sculpture, a painting, or a bowl of soup. To them it was never about the perfection of those objects, it was always about perfecting our own selves. They called it aretê — our duty towards ourselves, towards living up to our full potential.
But as designers, we have a duty not only to ourselves but to our entire progress as a human race.
In his TED talk, Philippe Starck visualized humanity as a bunch of people walking on infinite road ridden with holes. When we’re not being mindful, we’re looking straight down and keep falling into those holes. But by practicing mindfulness and creativity we can raise our angle of vision and see the road ahead of us.
We can’t get off the road, but we can see it now. We made powerful tools to ride this road faster than ever. And we can prevent others from falling down — as far into the future as we’ve trained our brain to go. When we design we always come up with two products: our design itself, and everything we’ve learned, everything we’ve evolved into.
It is our duty as designers to keep thinking, to keep raising our angle of vision, and to never stop improving ourselves while helping the humans around us to do the same.
Thank you for being a mindful and patient reader, and making it to the end.
Bibliography:
- Daniel Kahneman, Thinking, Fast and Slow
- Robert Pirsig, Zen and the Art of Motorcycle Maintenance
- Ryan Singer, Shape Up
- Дмитрий Чернышев, “Как люди думают” (not yet available in English)
Thanks to Jess, Steph and my wife for helping me write and edit this. And thanks to Kevin, Jesse, Peter, Pavel, Maxim, and many others for our conversations, your opinions and your tweets that helped me think better.
