From Tutorial Hell to Tech Jobs: The Shortcut That Actually Works

Eight months in my bedroom

In 2019 I was working in venture capital. It was a decent corporate life, but I was inspired by founders and I did not want to just fund things, I wanted to build them. So I quit to learn to code full time. I locked myself in my bedroom in KL and ground through tutorials, YouTube and blog posts for about 12 hours a day: Vue, React, Node, Express, Hasura, Supabase.

At first it was fun. Hit run on someone else's code and watch a project come to life. After a few months the harsh reality set in: despite completing hundreds of tutorials, I could not build anything of my own. Every time a course got hard, I switched to Python, then Ruby on Rails. Then digital marketing, crypto, UI/UX, product management. Tutorials were junk food: they felt good, but I was eating chips and getting zero protein.

After eight months I hit one of the lowest points of my life. No income, burning through savings, isolated, and deep in imposter syndrome. Some nights I stared at the ceiling wondering whether to crawl back to corporate life.

The practice interview that changed everything

Then a friend with a first-class IT degree, far more qualified than me on paper, almost sheepishly asked if I could help him prepare for the coding test at a global tech company. What could I possibly offer him? But we got on a call and worked through practice problems, and he struggled badly, even on basic problem-solving. I found myself guiding him: try thinking about it this way, what about this approach, have you considered the time complexity of sorting first? By the end I had essentially solved every problem.

When the call ended I sat back and thought: how is it that I, the self-taught newbie, could handle questions an IT graduate could not? I was not as clueless as I had been telling myself. Months of grinding had built real fundamentals. I also realised that everyone, degree or not, has to go through the hard process of learning to think computationally. The paper does not do it for you.

You often underestimate how much you have learned until you are forced to use it. It is like training in a gym without a mirror: you do not see progress until the day you lift something that used to feel impossible. If you are doubting yourself right now, read am I smart enough for tech?

Real projects with real stakes

Encouraged, I decided to test myself in the real world. Through networking I landed a small freelance job building a simple web application for about US$3,000, which felt like a fortune after eight months unemployed. I pulled it off. The client introduced me to someone else, which led to a US$10,000 project, and then a US$40,000 one, all within a couple of months.

The money mattered, but the validation mattered more. And I learned something important: paid projects teach you faster than personal ones. On your own project, when a feature gets hard, you quietly decide you do not need it, so you never learn to solve that problem. A client does not let you skip it. You have to get it done, by hook or by crook. That is where most of my real learning came from.

It was not smooth sailing. By the US$40,000 project I was in over my head as a one-man army, so I tried to hire junior developers to help.

What I found when I interviewed over 100 graduates

Over a few weeks I interviewed more than a hundred candidates for junior roles, mostly fresh computer science graduates with decent CVs and some internships. Interview after interview, the same problem: they could not code. Not advanced things: basic logic, explaining a simple algorithm, structuring a basic web app, designing a database for a simple online store. Some recited AI-sounding answers. By my rough estimate, only about one in ten had the skills we needed.

Months earlier I had been the one feeling unqualified. Now I was in the interviewer's seat wondering how people spent three or four years at university and came out not job-ready. My friend was not an exception; he was the tip of the iceberg. Many programmes produce graduates who know theory and pass exams but have never built and troubleshot a real application end to end. And AI makes it worse if people skip the struggle that builds the programming muscle. We explore this in vibe coding vs fundamentals.

Pad champions and forever students

Looking back, much of my time in tutorial hell was procrastination driven by fear: of failure, of discovering I was not good enough, of the unknown. It is safer in the kiddie pool where someone tells you exactly what to type.

I see the same in many aspiring developers. They collect courses and certificates like Pokemon cards. "One more course and then I will be ready." Years pass and they have more PDFs but the same skills: forever students, always learning, never doing. I even delayed freelancing for ages because I felt I needed to know more. When I finally jumped in, I learned ten times more on the job.

A martial arts analogy from a mentor stuck with me. In boxing there are pad champions: beautiful form on the pads and heavy bag, but the first time they get punched in a real spar, it all goes out of the window. Coding tutorials never hit you back. Real projects do. When your code breaks and there is no walkthrough, that is a punch in the face, and in the right dose it is exactly what makes you better.

The shortcut

It is not a secret framework. It is a combination that compresses years into months:

Where AI fits in now

Is becoming a developer still viable when AI writes code? I believe it makes sense to learn coding arguably more than ever. AI is an amazing tool, and we use it heavily: to check students' code, give hints and act as a pair programmer, and we teach students to use tools like Copilot and Cursor to speed up their work. The key phrase is speed up, not replace.

I describe AI as a dream developer with infinite speed and questionable reliability. It will happily produce code, but you need to be the senior developer in the room who knows what should be built, what to merge, and what to fix. With no coding knowledge, you will get something, but you will not know whether it is any good until it breaks. Companies tell me they are desperate for developers who combine solid fundamentals with AI fluency; those who use AI without fundamentals produce poor output because they take it as gospel.

That gap between what traditional education teaches and what industry expects is why I started what became Sigmaschool: practical, project-first learning with mentors and a cohort, now built around AI as a multiplier. If you want to take the shortcut with support, see the AI-Native Software Development Programme, or start building today in the free trial. For the full escape plan, read how I escaped tutorial hell.