Algorithmic Thinking for Top Performers
Algorithmic thinking involves breaking down problems into manageable parts and implementing solutions methodically, akin to how computers operate with algorithms. Morning routines exemplify this approach, offering a structured way to start the day with productivity and clarity. By applying algorithmic thinking, individuals enhance problem-solving skills, increase productivity, and achieve peak performance and self-mastery.
Algorithmic thinking is a mental model that every peak performer and individual who seeks to become self-mastered should include in their cognitive toolbox. From designing a productive morning routine for success to following a recipe, all the way to breaking down a problem in smaller parts… algorithms are in our everyday lives.
We have written before in the past on How To Algorithmize Peak Performance, but it is not exactly the topic we want to write about in this essay. In the above essay, we showed the science and biology behind purposefully shifting our decision making from the prefrontal cortex to the basal ganglia by repetition.
To do so, we engage in the power of habit and purposeful planning and organizing to make sure our habits are forced until they don’t have to be, that way allowing us to make fewer decisions throughout the day, and focus more on what matters.
In this essay, we do not dive deep into the science and biology behind our brains. We shift our focus towards algorithmic thinking for peak performance, which consists of adopting a systematic way of thinking about problems and creating solutions for them. Like an algorithm for a computer.
So, without further ado, what is algorithmic thinking?
What is algorithmic thinking?
Algorithmic thinking is a systematic way of thinking through problems and solutions in a way that is similar to how a computer would run (1). Computers have different ways of solving complex problems than we do. They are very good at operating with iteration, repetition and simple problems. And very good at following instructions: algorithms.
An algorithm is simply a finite series of steps which, when repeated, help solve a problem with the same rate of success every iteration (2).
Algorithmic thinking is approaching problems like how computers approach them, which is the following algorithms. Algorithms are merely a set of steps that, when followed, reach to a solution.
As mentioned above, algorithms are everywhere. Don’t you follow a finite series of steps to baking a cake? If you repeat these steps many times, doesn’t the end result always end up in a cake?
If you like to bake cakes, you are following an algorithm. Maybe you do not like to cook, but that doesn’t mean you do not follow algorithms in your day to day life.
Ever followed the instructions to set up an IKEA table? Ever played with LEGO? Ever followed a method to solve addition or division problems? Ever folded your clothes? All are examples of the following algorithms that are present in our day to day lives.
Computers are very good at the following algorithms. They are given a small number of steps and instructions, and they will repeat them endlessly and successfully every time. What is interesting about algorithmic thinking is the idea that complex problems can be broken down into smaller parts. Solving them individually leads to the problem effectively solved too.
Learning how to break down complex problems into smaller ones, solve each one, and effectively solve the larger problem is at the core of what peak performance and self-mastery is about.
How Algorithmic Thinking Looks Like
Algorithmic thinking is a very simple concept to understand. We engage with it daily in our lives in some form or way. What is difficult is to purposefully apply it to achieve peak performance, but more on that further down the essay.
Here are a few simple steps to what applying algorithmic thinking to solve complex problems looks like (2):
- Define the problem clearly
- Break down the problem into small parts
- Define a solution for each one
- Implement the solution
- Make the process efficient
The first step is only logical. To solve a problem, you first must understand it and define what success in solving it must be. Breaking it down into simple and smaller parts is what computers excel at, but we can also apply it in our day to day lives (which we already do).
For example, in our How To Manage Your Energy For Productivity essay, we broke down the problem of how to manage our energy in hopes of maximizing our productivity into smaller parts: identifying which where our energy levels throughout the day and organizing ourselves around them.
Once we identify the different times of the day when we are more and less energetic, we organize our day to include complex and deep work when we are more energetic, and repetitive and easier work when we are less energetic.
Once the smaller parts are identified and the solutions are defined, it is all about implementing the solution. Once we do solve each smaller part, we can focus on making the process we have followed more efficient with each iteration.
For this last step, it is essential to understand how feedback loops work, as every iteration of the process (the algorithm) we designed will provide important data that allows us to fine-tune it. These are only two examples of applying algorithmic thinking to solve complex problems and to refine our own algorithms with each iteration.
In regards to peak performance, we have found that algorithmic thinking can be applied to the concept of morning routines (which are also algorithms we follow).
A purposefully designed morning routine for success can include best practices that only make our lives easier and decrease our cognitive load and attention on minutiae. This way, we can free up space in our minds for the complex, creative and deep tasks that do need our full attention.
Morning routines are algorithms
The topic of morning routines has increased in popularity over the years, and for a good reason. A productive morning routine for success has positive effects that carry over to the rest of the day and can lead to an increase in productivity and energy.
However, we have read and heard of morning routines from others in articles and interviews which are a fancy way of procrastinating. A morning routine that is three hours of meditation, two hours of skincare, and one hour of heavy breathing is not a morning routine.
While it may be exaggerated, the point we are trying to make is those morning routines for success should serve a specific purpose and shouldn’t be too long. The point behind them is to start the day on the right foot, by making sure we are energetic, our mind is clear and sharp and we can be productive and efficient with our time.
Every individual has a different morning routine, and everyone has different needs, habits, and work to do. We cannot provide for a one-size-fits-all morning routine, it is up to you to design the one that makes the most sense to you and is in tune with your personal goals.
There are morning routines designed for better health, morning routines for happiness, productive morning routines for success, etc. However, most morning routines include a few, core underlying ideas in common, which are what make them successful morning routines.
A morning routine is a set of steps and actions we take in the morning with the idea to start the day on the right track. They are an algorithm we follow to achieve a personal goal, most of which are related to health, productivity, and energy.
Applying the mental model of algorithmic thinking, we can design a morning routine to achieve our goals. This doesn’t mean that morning routines have superpowers or that they are the key differentiator between peak performers.
No, morning routines are one tool in the toolbox, and it all depends on how it is used. While we will illustrate how to use algorithmic thinking to design the best morning routine for success, algorithmic thinking can be applied to many areas in life, and many problems that we can solve this way.
Designing a productive morning routine with algorithmic thinking
Let’s remember the five steps of algorithmic thinking: 1) define the problem, 2) break it into smaller parts, 3) define a solution for each part, 4) implement the solution, & 5) make the process more efficient with iteration.
With this simple mental model, we will design a morning routine to achieve a goal, which in this example will be to increase productivity.
First, we define the problem. We want to be productive in our days, because we are waking up tired and with low energy, we want to enter the flow state quickly when working on complex tasks and complete them in the right amount of time, instead of having them drag on endlessly.
So, the first step is already achieved: we want to increase our productivity so we can have a better day and peace of mind, instead of being stressed out and taking too long on tasks which can be done quicker.
Once the problem is defined, we can go onto step two and break it into smaller parts. In this example, we can look at the different sources of the problem:
- lack of organization
- lack of physical energy
- lack of motivation or purpose
There can be many different sources to the problem of poor productivity, but we are choosing the above three because they are both connected and different enough that to solve them it needs to be done individually.
Once we have the bigger problem of poor productivity separated into three smaller problems, which are a lack of organization, a lack of energy, and a lack of motivation, we can now design a solution to each one.
The solution to a lack of organization is to organize and plan beforehand. Simple and easy. For some, you will need to plan the day before; for others, you plan a week before. No matter when you plan it, if you suffer from a lack of organization, the solution is to plan your day, week, or month beforehand.
The degree of details to which you plan ahead is up to you and your personal goals, though it makes sense that if you plan for the next day, it will be more detailed than if you plan for the next month. Read Why You Should Choose a North Star Metric if you want to go more in detail on how to organize and plan according to your different goals.
Solving the lack of physical energy is also simple to understand. Physical energy is tied to our diet, our sleeping habits, and our exercise. If you are not sleeping enough, sleep more. If your diet is unhealthy, fix it. If you do not exercise, start exercising.
While the above solutions are simplistic, they are the only way to fix them. There is no thirty-page essay that you need to read to know that to solve lack of exercise is to do exercise, to fix an unhealthy diet is to eat healthier, and to fix your lack of sleep is to sleep more and better.
For the last part, lack of motivation or purpose, a solution can be to find your purpose, which we have written more extensively in The System of You and What I Talk When I Talk About Purpose? Funnily enough, solving the first two problems also leads to solving this one.
So we have identified the problem, separated it into three smaller parts and found a solution for each one, what now?
This is where algorithmic thinking comes into hand, and why purposefully designing a productive morning routine for success is a great way to achieve peak performance. Rather than go and solve each problem individually, the different solutions can be linked together in a step by step process, saving time.
Here is one example of a morning routine that could solve all of the above and provide for a productive and successful start to our morning that will carry over to the rest of the day:
- Wake up
- Do some stretches and light exercise
- Plan for our day
- Have a light breakfast with more protein and fats instead of a high carbohydrate one (or even fast)
- Shower
It seems simple, right? Well, morning routines should be simple, and the one above is just one example. It can be done in one hour, and we are solving all of the above problems.
By doing some light exercise and stretches, we are effectively “waking up” our body and getting some blood flow going on. By having a light breakfast with high protein and fats, or even fast, we avoid the heavy digestion that comes with large meals or the crash that comes after having a carb-heavy meal. When we plan for the day beforehand, even five or ten minutes can help increase clarity in our mind, thus avoiding procrastination or lack of motivation.
And in the space of less than an hour, we have used algorithmic thinking to design an algorithm, a morning routine, which solves our big problem of lack of productivity. It also solves our smaller problems of lack of organization, lack of sleep and lack of purpose, by following a few, short steps.
While morning routines are only one algorithm we can design with algorithmic thinking to achieve peak performance, purposefully designing algorithms and processes we can follow to avoid excessive cognitive load is one of the keys to achieving peak performance and self-mastery.
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Hey, I'm León Castillo
I'm an entrepreneur, investor & university professor obsessed with peak performance & entrepreneurship.
6 years ago I founded Selfmastered to help 1 million entrepreneurs unlock peak performance, so they can build their dream business without compromising their time, health or relationship.
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