Every young Nigerian on a tech journey is familiar with the term, ‘Upskilling.’ At the workplace, in the media, at every tech conference or conversation the topic of upskilling is one that is always echoed.
Attached to this phrase is the urgency to upskill so that you aren’t left behind in the tech race, at the end you are left with a long list of courses you want to take which you eventually don’t take at all and even if you do, you never get to complete them.
The Real Problem With How Upskilling Is Sold
Instead of being guided through a realistic, step-by-step process, you are handed urgency and a destination. For instance, master Python in 30 days, become a data analyst in 8 weeks; with very little acknowledgment of what the journey actually looks like.
Social media makes it all worse because you get to only see the end product of a process that took tons of hours to accomplish. So, you are anxious, and the delusions that you are doing nothing increases. Once again, you try to hasten your learning pace, but again you fall flat to your face.
What Is the Compound Effect?
The concept of the compound effect was succinctly and efficiently explained by Darren Hardy in his book the compound Effect. In his own words, “The Compound Effect is the principle of reaping huge rewards from a series of small, smart choices. What’s most interesting about this process to me is that, even though the results are massive, the steps, in the moment, don’t feel significant. ”
What this means is that your small choices, including consistency and time produces significant results.
What does that mean for a techie on a journey to upskilling?
In simpler terms, it means you don’t have to start by looking for ways to short circuit your learning duration which is something that is frequently advertised. For instance instead of looking for YouTube tutorials that promise mastery of Data analysis within one month, you could start by making your learning a daily practice and In the initial period your process may seem invisible, but you are building momentum.
How Learning Momentum Works in Tech
If you’ve ever tried to learn a tech skill; Python, frontend development, data analysis; you’ve already felt it: that frustrating, slow, almost discouraging start where nothing seems to click.
At the beginning, it feels like trying to start a stubborn generator. You pull once, nothing. Pull again, still nothing. You check YouTube, adjust something small, try again. It sputters, but doesn’t quite come alive.That’s what the early stage of learning tech feels like.
You spend hours installing tools, fixing errors you don’t understand, and following tutorials line by line. You write code, run it, and it breaks. You tweak one thing, and something else breaks. At the end of the day, it feels like you’ve made no real progress. But if you stay with it, something subtle begins to happen. A concept clicks. Your code runs, just once, but it runs. You begin to recognize patterns. The same errors that confused you yesterday start to look familiar today.
You’re still putting in effort, but now the system is beginning to respond.Soon, you’re no longer just copying code. You debug with a bit more confidence. You open documentation without immediately feeling overwhelmed. You start connecting ideas: how one concept leads to another, how tools fit together.
Then, almost without noticing exactly when it happened, you cross a threshold. You can build small things on your own. You understand your errors more than you fear them, you start questioning tutorials.
Learning becomes less of a chore and more of a rhythm. From the outside, it looks like you’ve suddenly become “good at tech.” But what’s really happened is simpler: momentum has taken over.Now, every new skill builds on the last. You learn faster. You recover quicker when you’re stuck. Even when you take a break, it doesn’t take much to get back into flow.
That’s the power of momentum in tech.
The truth is, learning a tech skill isn’t difficult because it’s beyond you. It’s difficult because most people quit before things start to move. They mistake the slow beginning for a lack of ability, not realizing it’s just the natural resistance that comes before progress.
The ones who succeed aren’t necessarily smarter, they just stayed long enough for things to start working in their favor.
A Simple Daily Learning Framework for Tech Upskilling
Applying the compound effect does not require long, exhausting study sessions. It requires showing up consistently.
Most advice you will find online suggests a clean, structured routine: wake up early, study for an hour, build something, repeat. That sounds great in theory. In reality, you have a job, family obligations, NEPA taking light, data running out, or simply a day where motivation is nowhere to be found.
So here is a framework built around your actual life, not an ideal version of it.
On a good day, aim for 45–60 minutes or even 2 hours
- 10 minutes: Review. Before learning anything new, spend a few minutes revisiting what you covered last time. Re-read your notes, re-run your code, or just try to recall the key concept from memory.
- 25–30 minutes: Learn one thing. Not one course. Not one module. One concept. Watch a short tutorial, read a documentation page, or work through a single exercise. The goal is depth over speed
- 10–20 minutes: Apply it immediately. Write the code, sketch the wireframe, run the query, build the small thing. Even if it breaks. The moment you try to use what you just learned is the moment you find out whether you actually understood it.
On a hard day, aim for just 15–30 minutes:
Do not skip entirely. Open your laptop, re-read yesterday’s notes, watch one short video, run one line of code. It does not have to be productive in the traditional sense. The goal on a hard day is simply to maintain the habit signal, to remind your brain that this is something you do, not something you used to do.
On a completely lost day
Missing one day does not break momentum. Missing a week starts to. Missing two weeks and you are essentially starting over emotionally, even if the knowledge is still there. The recovery cost of a long break is majorly about rebuilding the psychological habit of showing up.
Track your consistency somewhere visible. Not to be rigid about streaks, but because seeing a pattern of effort is its own quiet motivation to keep going.
Is the compound effect still relevant in the age of AI
Yes, and here is why. With the current irresponsible use of AI producing garbage-in, garbage-out content, it is easy to doubt the necessity of a slow, disciplined approach to learning when you can retrieve any piece of information in seconds. AI promises to increase productivity and accelerate the learning pace. So why endure the slow grind of building skills from scratch when AI can hand you the output in seconds?
The answer is simple; what you need to compound has shifted, not the principle itself.
AI doesn’t replace thinking. It doesn’t replace judgment, discernment, or the ability to evaluate what is true, useful, or well-reasoned. If you haven’t built momentum in understanding fundamentals and critically assessing outputs, you will hand a powerful tool to an incompetent operator, and the results will show. The people winning with AI are not those who use it the most. They are those who have compounded the right foundations, curiosity, critical thinking, domain knowledge, and the discipline to go deep.
The Compound Effect is not less relevant in the age of AI. It is more important than ever because the gap between those who have built real understanding and those who haven’t is now wider and more visible than at any point in history. Compound wisely. The returns will speak for themselves.
And here is the exciting part, now that you understand the power of compounding the right things, our next article is going to show you exactly how to put AI to work for your growth. We are talking Prompt Engineering; the skill that turns AI from a fancy search engine into your most valuable learning companion. See you there.
