Shorts are small essays that I publish every day. They usually only take 2-5 minutes to read, and touch on all the same topics that my blog covers.
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Should you be a specialist, or a generalist?
Should you go as deep as possible on one topic? Or learn as broadly as possible?
There's no easy answer. It’s different for different people.
Personally, I don’t have the patience to become a specialist.
I’m too curious about too many things to ever be happy working in one field, on a specific topic.
There is one concept that has always appealed to me though.
There are lots of names for it: polymath, generalized specialist, deep generalist, t-shaped marketer.
The idea is that you learn deeply in a couple areas.
You combine that expertise with some general knowledge to form a unique bank of knowledge and skills.
You may not be an expert in each area, or any area, but the combination makes you unique.
A key part of this idea is the amount of time required to develop expertise.
While it may take a lifetime to reach the top of one field, you can get close to the top in two unique fields in a much quicker amount of time.
The concept of a t-shaped marketer is similar.
You’re expected to have a broad knowledge of all the skills required for marketing, and then specialize in one area.
You can do all kinds of things when required, but can go back to a specific area as your team grows, for example.
There's no easy answer for the question of how specialized you should be.
Some skills take longer than others to master.
It’s difficult to evaluate what percentile of a field you are in, or what’s necessary to move up.
Some skills and knowledge will become obsolete.
But for someone like me, who may never be a specialist, the idea of the deep generalist provides a useful framework for evaluating my own skills.
And ultimately, it helps me position myself in the modern professional world.
The modern work day wasn't built for knowledge work.
Knowledge work means different things to different people.
I think about it as problem-solving: identifying problems, coming up with a solution, and implementing that solution.
It’s the work I like doing most.
Unfortunately, the modern work day doesn’t fit well with this kind of work.
The best problem-solving starts with a period of exploration.
You stumble upon something interesting, and it triggers a moment of realization.
You find the source of the problem you’re trying to identify, or you come up with a great idea for a solution.
That discovery triggers a burst of motivation, a rush of excitement to get started solving the problem and testing your solution.
In an ideal world, you put your solution in place, and then document it to revisit later.
The reality is not so nice.
Most of the time, there’s a period of intense planning to begin a quarter.
You build a week-by-week plan with aggressive deadlines.
You’re also trying to finish the work of the previous quarter, so the exploration phase is cut short. Regular meetings cut into the periods of concentration you’d need for it anyway.
By the time the next quarter rolls around, you have to start working the plan. There isn’t time to reassess or verify the data.
We’re bad at estimation and so deadlines slip. Documentation gets cut because it’s not considered essential.
And by the time the end of the quarter is nearing, the planning starts all over again.
There’s little room in this cycle for alternation between exploration and bursts of execution.
There’s a better way.
Shaan Puri calls it “working like a lion”: extended periods of rest, thinking, and exploration, followed by a burst of energy to execute on a project.
The problem is, it requires acknowledging that we don’t know what we should work on.
It requires acknowledging that our motivation levels vary.
And it requires avoiding a fixed plan.
None of these are possible in the modern workplace.
But they are how I prefer to work.
The most important part of work isn’t the work itself.
It’s the people.
Learning and autonomy are the two components of work I value most.
But the experience of work itself is determined by the people around you.
I’ve worked in a lot of different environments: Coast Guard, small startups, medium-size startups, accelerators.
There were high-performers in each. Some were already extremely successful, by any measure.
There is a stereotype that exists in the world of money and high-pressure environments.
The stereotype of the hard-driving, arrogant boss, who works people hard and pushes them to their limits.
Their abuse and criticism is tolerated because they get results, and because employees believe it makes them better.
That stereotype still exists in some circles, but it’s fading.
But I’ve seen enough high-performers to know that this kind of behaviour isn’t necessary.
Do high-performers have high expectations? Of course.
Do they often give blunt feedback? Certainly. Feedback like that is a gift, as it gets you closer to the truth.
But being a high-performer doesn’t require treating people poorly.
Good criticism is about the work, or the skill, and not the person.
High-performers are often very good at one thing, and bad at many others. The best are aware of their limitations.
So I have little tolerance for working with bad people, or those that treat others poorly.
If you work with good people, almost any work can be enjoyable.
The reverse is true as well: if you work with bad people, prepare to hate your work.
Learning is always my top priority when it comes to work.
Learning fast requires the time and flexibility to follow areas that are interesting.
Take a couple steps forward, and then one back. Time for mistakes and self-correction.
In short, it requires autonomy—my second highest priority behind learning.
Autonomy does not mean no supervision. It doesn’t mean no manager or criticism or feedback.
Feedback and criticism are key components of my first goal: learning.
Good managers and peers provide feedback and ask questions that help with learning. They’re crucial in making work enjoyable too.
Autonomy instead means the freedom to explore different areas. The freedom and encouragement to make mistakes and improve.
It means less micro-management, and more support.
A key part of what I like to do—solve problems—involves choosing which problems to tackle first.
In tech and startups, where I like to work, there are too many problems to tackle at once. So choosing the right ones is critical.
And to choose the right problems requires some autonomy too.
It means periods of exploration for problem definition, data investigation, and proof-of-concepts.
But not all will lead somewhere. That’s part of the process. And it requires autonomy to execute well.
Learning first. Autonomy second.
Two key components of the work I like most.
I value one thing above all else in my work: learning.
Learning isn’t only about absorbing new knowledge.
It is putting into practice that knowledge, and deliberate practice of new skills.
Spending all your time reading and gaining new knowledge isn’t learning. It’s procrastination.
In fact, the fastest way to learn is to start, and then learn things as needed.
The only downside to this approach is you may not know all the options, so it’s sometimes useful to skim through an overview of things first. Then you’ll know when it’s time to go back to the learning material.
Balancing execution with learning can be difficult.
Too much learning, and you’ll make no progress.
Too much execution, and you’ll move forward much slower than if you’d stopped to think about what you’re working on.
Execution in the wrong direction is bad. Grinding out work when a you could build a system isn’t efficient.
The fastest learning occurs when you have time and space to focus on one project.
Enough empty blocks of time to concentrate, and enough freedom to switch back and forth between knowledge acquisition and application.
A project is a great way to learn. You have a concrete end goal and a method of application.
Projects fit well with the variety I like in my work too. I get bored doing the same thing over and over again.
New projects provide an opportunity for learning, but also for a change.
Whether it’s a new project, a new team, a new focus, or a new experiment, learning is always my top priority.
It’s often why I choose to change jobs, or how I choose between them.
Learning above all else.