3 years of systematic work to live freely for 30 years

The Problem We Don’t Notice

You can spend weeks grappling with algorithms, chewing through binary trees, and then you open LinkedIn and see that your classmate is already at Meta, someone else is launching a startup, and a third is building pet projects with perfect UI in React. Add to that Instagram with endless views of Bali, MacBooks, and slogans about Ferraris at 25.

And the question arises: maybe this isn’t for me? Maybe I’m too slow? Why do I need this math if AI will soon write everything for me?

Familiar?

But here’s the truth: you are not standing still. You’re just looking in the wrong direction and measuring the wrong things. You are growing, but it’s not visible because you’re used to comparing yourself to someone else’s finish line, forgetting where your own start was.

Why We Don’t See Our Progress

The Illusion of Instant Success

Sam Altman became a genius “overnight” with the release of ChatGPT. But behind that overnight success were seven years of daily work when no one believed in him. No magic, just a cumulative effect. You invest day after day, don’t see results, endure. And then, suddenly, it becomes visible. Not because you “got lucky,” but because your work finally caught up with your expectations.

We Compare Others’ Highlight Reels with Our Own Mundane Days

You see a post: “Got an offer at Google!” but you don’t see the four years of practice, 200 rejections, burned-out weekends, and the thought “I’m done, I’m quitting.” You’re comparing their finish line with your starting point. This is a recipe for burnout and feelings of worthlessness.

We Don’t Measure What’s Growing

Try this: open code you wrote three months ago. If you think, “Good grief, did I write this?” — it means you’ve grown. But we don’t record this, we don’t write it down. Without facts, the brain reduces everything to feelings, and feelings are deceptive. We don’t notice growth because we don’t look at it systematically.

The Truth About Growth in IT: What Actually Works

Truth #1: AI Won’t Replace Those Who Understand the Fundamentals

Recently, I conducted an experiment: I tested all modern code generation tools: Cursor, Lovable, Claude, ChatGPT. Here’s what I concluded: if you don’t understand how architecture, patterns, and what each line of code does works — AI will generate something that will be harder to untangle than writing it from scratch.

A Typical Scenario:

1. AI generates a bunch of code
2. You: “This is too complex, extract it into separate components.”
3. It extracts, breaking half of what was working.
4. It adds stubs “just so something works.”
5. It spends all its tokens “thinking.”
6. It outputs non-working code.
7. “Your funds have run out.”

And then I make one line of changes… and everything works.

Conclusion: AI is a tool that accelerates those who already know how to do it. It won’t replace understanding of architecture, patterns, and HOW it works.

Therefore: why do you need algorithms and data structures? So that a year from now you’re not typing in a chat: “AI generated a project for me, and now I can’t figure out what’s wrong.”

Truth #2: The Ability to Read Code Is More Important Than Writing It

When I joined Google, I was given a pipeline that had been written over 10 years by different teams. It was supposed to run once a day, but it ended up taking more than 24 hours to execute. The result? Every day the pipeline failed, it was killed, and restarted. Thousands of machines wasted.

Two years I spent deciphering this legacy code. I looked for people who had worked on it 7 years ago. I analyzed every line: why was this done? Could it be removed? What would break?

In the end, I rewrote it all from scratch and saved the company $10 million a year on infrastructure.

Lesson: the ability to read code is more important than the ability to write it. And this only comes with practice. There are no magical repositories for this. And this skill will be useful in any language. At Google, I programmed in 14 languages. How? You look, you analyze. All languages are fundamentally the same.

Truth #3: 3 Years of Effort vs. 30 Years of Career

Let’s be honest: each of us has at least another 30 years of active life ahead. If you spend 5 years reaching great positions, you’ll have 25 years left to enjoy the results.

My friend Damir left Google a month ago. For personal reasons, he decided: “Why do I need this? I won’t work for a year.” And he travels for a year. Because after Google, you can do that. The market will devour him when he returns — he built infrastructure for AI agents.

This is the end goal in terms of career. When you are competent enough to allow yourself to choose.

A System for Sustainable Growth: How to Actually Learn

Okay, understood. Long-term perspective, cumulative effect, don’t compare yourself to others.

But what to do CONCRETELY?

Step 1: Stop-Loss Rule for Learning

Stuck on a task for a week? Here’s a simple system:

1. Two hours of independent work
Work seriously. Not just “looked and didn’t understand.” The brain must strain.

2. Use AI correctly
Ask AI: “Explain it to me like I’m 12.” ChatGPT starts using analogies, talking about tomatoes, imagination kicks in, and the material is absorbed better.

3. Analyze every line of AI-generated code
AI generated code? Don’t copy it immediately. Ask it: “Why this line?” “Can it be done without it?” “Why did you use this approach?”

Step 2: Measure What’s Growing

Keep a Weekly Report. Every week. What to write down:

— what you learned this week
— where you got stuck and how you solved it
— how much time you spent on each task
— what you changed in your approach
— what progress you noticed.

Example:

— “This week I reduced reel consumption from three hours to one hour a day”
— “I understood how binary trees work! Now I can explain them to friends”
— “Got stuck on recursion for four hours, then asked AI ‘explain like I’m 12’ and understood in 20 minutes.”

These are factual results. You can be proud of them. The chances of returning to old habits are lower.

Writing it down is harder in the first few weeks. Then it becomes automatic.

Step 3: Eliminate Distractions 

Everything that distracts steals your growth. I use a black-and-white phone. Screen time dropped to almost zero. I don’t watch reels. Only what my wife shows me, about 10 times a day. 

Look: where does your energy get drained the most? Social media? YouTube? Games?

Start small: remove color from your phone. Delete Instagram on weekdays. Replace reels with podcasts. Track screen time, record results in your Weekly Report. A small change = huge return.

Step 4: Long-Term Thinking 

You still have 30 years of active life ahead. If you spend three years growing, you can then choose. Bar today or Google London in three years? Think about it. Mom is upset? Later you’ll buy her an apartment.

You need to understand the long-term nature of the path. Then all the small daily things become insignificant.

Concrete Plan: What to Do Tomorrow

1. Start a Weekly Report

— where I am now: what I can do, what I can’t
— what I want to learn this week
— how much time each task will take

2. Define Your “Stop-Loss”

— stuck on a task? Try yourself for two hours
— didn’t work? Ask AI to explain like I’m 12
— still unclear? Ask for help

3. Remove One Distraction

— how much screen time on your phone?
— choose one: Instagram, YouTube, something else
— delete or limit to 30 minutes a day

4. Create a Long-Term Goal

— where do you want to be in three years?
— write it down. Hang it on the wall
— when the temptation to quit comes, look at the goal

Every week:

Update your Weekly Report:

— what you learned
— where you got stuck and how you solved it
— what progress you noticed
— what you changed in your approach
— measurements: sleep, screen time, study hours

It will be hard in the first few weeks. That’s normal. The brain struggles, it expends energy, you need to grow neurons.

In three years:

If you grew every day, you will reach any height.

In calculus, there is a theorem: if a function is increasing, it will eventually reach any height.

This works for careers too.

Simple math.