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Why Learning AI by Building Beats Watching Tutorials

Baljeet Singh Khiva

Baljeet Singh Khiva

Founder, TEN Labs · 2 June 2026

Every few months, a new AI tutorial series promises to make you an expert in a weekend. Watch enough of them and you will start to recognize the pattern: a polished demo, a copy-pasteable notebook, and a feeling of understanding that evaporates the moment you try to build something on your own.

That gap between watching and doing is the reason we built TEN Labs Academy around real ventures instead of recorded lessons. When you are building an AI loan advisor for MARG or an energy dashboard for HESEOS, there is no script to follow. The data is messy, the requirements shift, and the only way through is to actually understand what you are doing.

Tutorials optimize for confidence. Projects optimize for competence.

A tutorial is designed to make you feel capable in the moment. A real project is designed to make you capable, even when that means getting stuck, debugging for an hour, and rethinking your approach twice before something works. That discomfort is not a bug in the learning process. It is the entire mechanism.

This is why every learning path at the Academy, whether it is development, product design, marketing, finance, or data, ends the same way: with a capstone module where you apply everything to a live challenge from one of TEN Labs' portfolio companies. Not a simulated one. A real one, with real users on the other end.

What this looks like in practice

  • You work with real (anonymized) data from an actual company, not a sanitized Kaggle dataset.
  • You get feedback from mentors who are actively building these ventures, not just teaching about them.
  • You ship something you can put in a portfolio, such as a working prototype, a campaign, or a model, not a certificate of completion.
  • You learn to handle ambiguity, because real problems rarely come with a clean spec.

None of this means tutorials are useless. They are a fine way to get oriented. But orientation is not mastery. If you want to actually be able to build with AI, not just talk about it, you have to build. That is the whole idea behind the Academy, and it is why we would rather hand you a real challenge on day one than a syllabus.

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