Jack of All Trades, Master of...What Exactly?
“What are you actually good at?”
As a kid, I was always excelling at… well, everything. No subjects were difficult, because I could work harder than anyone else if needed. Things I did not fully understand, I would learn by heart. If that failed me, I might have somehow lured people into thinking I actually understood. STEM, History, Economy, Literature, from my childhood to young adulthood, I tackled it all.
Later on in life, it dawned on me—am I a scam because I am not truly an expert in anything?
When I started my IT career, the world was full of specialists—engineers, designers, data scientists, operations. The word “generalist” was not in anyone’s vocabulary. You were expected to become an expert in something very niche—or go home. Everyone wanted people who executed—not those who saw all the pieces of the puzzle, but without the depth.
So I did what I could—tried to learn as much as possible from each domain—and like an octopus in the marine world, I would mimic their behaviour so I would not get found out—because getting found out felt like death.
This brought its own set of problems. A constant imposter syndrome and feeling like I am almost good enough—but never the best in anything. Organizations just seemed to acknowledge and reward the specialists more visibly—maybe because it is much easier to fit you in a box with a label.
And then I stumbled into something rather unexpectedly—Product Management. The position was not even available at that company at the time. I basically just dreamt it and built it up.
I had a decent overview of development, design, architecture, and on top of that, I could tune into people and their needs. That’s when constant context switching became a feature—not a bug. Knowing just enough to ask the right questions and translating it into the correct language proved to be exactly what I was good at—despite not being able to execute it.
But PMs do not build the parts—we build alignment.
The years and years of diving into different skills and domains bore fruit—I could see patterns where no one else could and was able to make a decision with incomplete information. Specialists go deep. Generalists go wide enough to see the system.
But as with everything, there are costs that might have a huge impact on your life and self-esteem.
As a child, it is very difficult to explore your talents, because anything you do is just going to work at this stage. And the odds are you might enjoy it. However, once you reach the decision point about professional sport, your university subjects, and others, it is going to be very hard to decide—and a bit later you might realize, you are actually not great at it.
I went to study at a very mathematically oriented college. I struggled immensely. I was good to a certain level, yes—definitely not the worst— but I could be great at something else.
Your career would progress much, much slower then that of a specialist. The reason is that you would have the same difficulty describing what you are really good at as your employer understanding it.
Your imposter syndrome would be the one thing you can rely on in your life:
- Sitting in a room with the developers: They are so smart—what am I doing here?
- Chatting with business domain experts: How can I beat 20 years of experience in an industry?
- Designers: They are so fast in bringing my ideas to life!
And the risk of losing your voice while trying to fit everywhere is… paramount.
It took years for me to realize—I do not have to be like everyone else.
Being able to adapt and keep the breadth of my expertise is actually my biggest strength. You throw me in a new industry? Fine! I’ll come back with just enough knowledge not to cloud my decisions. Explaining a solution to a client? No problem—I will describe everything in simpler terms.
I strongly believe that the time has come for generalists to shine with AI.
AI is compressing the value of execution. What becomes more valuable is deciding what should be built. What the trade-offs are. And who connects the dots between the business, user, and tech context. AI is turning many specialist skills into commodities. They are not worthless—but more accessible, therefore the gap between “knows a bit” and “can execute” is shrinking significantly.
The difference between:
- “I kind of know how this works.”
- and “I can actually produce something useful.”
- …is getting smaller by the day. And that changes the game.
However, what remains important is:
- Frame the problem correctly.
- Break problems into meaningful pieces.
- Use AI + human input in the right places.
- Validate and challenge the outputs.
Of course it does not mean that now we do not need to learn anything to do our job well.
But we can leverage what we have already been doing: critical thinking, ability to recognize bad outputs, and using just enough depth of knowledge to communicate with AI (or humans) efficiently. A shallow generalist with AI is just going to be faster at being wrong.
Maybe the problem was never how I think.
Maybe it was how I talk about it.
If you are struggling with who you are, try to reframe it in your mind and your vocabulary.
Do not say “I know a bit of everything”. Say “I can connect X, Y, and Z to increase your user base.”
Do not say “I can talk to everyone in their own language”. Say: “I can be technical enough to explain the functionality to the developers, and use simple enough language to show our clients how valuable it is to them”.
Do not say “I am a fast learner”. Say: “I see patterns across all domains that help me grasp a new industry in record time.”
Maybe I was never “not enough” because I wasn’t a specialist.
Maybe I was just early in a world... that is now starting to value the ability to connect the dots—at scale.
And remember—if you feel like you don’t fully belong in any room—you might be exactly where you’re supposed to be.
With love,
Zuzana
I drank 4 coffees while writing this post - support my habit by scanning the QR code/click on the link :)