HomeJournalLearning
LearningSkillPractice

Learning by Doing Is Getting Rare — and Expensive

The fastest way to learn anything is to do the thing, fail at it, and try again. AI lets you skip the failing part, which feels like a gift and acts like a debt. This post argues that "learning by doing" is becoming a premium skill in 2026, explains why watching tutorials and reading AI explanations cannot replace it, and gives you a concrete weekly practice that keeps your real skills sharp while you still use AI for everything else.

Siddharth PuriMarch 24, 20267 min read
Skill Loss & Learning

Learning by Doing Is Getting Rare — and Expensive

March 24, 2026 · 7 min read · Siddharth Puri

The fastest way to learn anything has always been the same: do the thing, fail at it, figure out why, try again. AI lets you skip the failing part. That feels like a gift. It acts like a debt.

What failure was actually teaching

When you tried to deploy your first backend and it broke in six ways, you did not learn six facts. You learned a map. You learned which pieces touch which other pieces, which errors come from which causes, what the shape of "something is wrong" feels like. That map is the thing senior engineers have that juniors do not. It cannot be read. It has to be earned.

When an AI fixes your deploy in nine seconds, you get a working deploy and a smaller map. Both are real. One of them is invisible until you need it.

Tutorials were never the bottleneck

Before AI, people who watched fifty tutorials and built nothing were already failing at learning. Tutorials give you confidence, not skill. Doing gives you skill. The only reason "learning by doing" is now a premium skill is that AI made the "doing" easier to fake.

If you cannot tell whether you understood something without AI help, you did not understand it. That used to be obvious when you had to actually build the thing. Now it takes deliberate effort to notice.

The weekly practice that keeps real skills sharp

  • Once a week, build a small thing end-to-end with zero AI assistance
  • Keep it small enough to finish in one sitting. A tiny CLI, a one-page site, a utility function with tests
  • When you get stuck, struggle for 15 minutes before you look anything up. The struggle is the point
  • After finishing, write a three-sentence "what I now understand differently" note
  • Four weeks of this compounds more than four weeks of AI-assisted features

Why "use AI for everything else" is fine

This is not an anti-AI post. I use AI every day. I rely on it for the 80% of my work that is boilerplate, translation, first drafts, lookups. That is fine. But I protect a slice of my week where I do the thing alone, because that is the slice where real skills keep compounding.

The goal is not to use less AI. The goal is to not lose the muscles that make AI useful in the first place. A senior engineer with AI is unstoppable. A senior-looking engineer who never built one of anything is a liability.

The career implication

Over the next five years, "I learned by doing" will quietly become a paid qualification. Companies will care less about which bootcamp you took and more about what you have shipped without help. That is already starting. Protect the habit now, not after the market forces it.

If you cannot tell whether you understood something without AI help, you did not understand it.
All postsSiddharth Puri

Keep reading

View all →
AI & Future of Work

Claude 3 vs GPT-5: What Changed and Why It Matters

March 26, 2026 · 9 min

Claude 3 vs GPT-5: What Changed and Why It Matters

They both claim to be the smartest thing ever built, and both demos look suspiciously similar. This is a ground-level look at how Claude 3 and GPT-5 actually differ in reasoning depth, long-context reliability, code quality and tool use — plus a blunt cheat sheet for which one to pick for which job. Written in English, without the benchmarks theatre.

AI & Future of Work

Will AI Really Replace Developers or Just Upgrade Them?

March 18, 2026 · 8 min

Will AI Really Replace Developers or Just Upgrade Them?

The internet has been burying developers every year since 1998 and we keep showing up for breakfast. Here is the honest split — which parts of the job AI genuinely eats (boilerplate, docs, test scaffolding, Stack Overflow archaeology) and which parts quietly get harder and more valuable (product judgement, architecture, ambiguity). Short answer: it replaces the parts of your job you hated, and the parts that pay you get more fun.

AI & Future of Work

Jobs That Will Survive the AI Revolution (And Why)

March 8, 2026 · 9 min

Jobs That Will Survive the AI Revolution (And Why)

Forget the "creative vs repetitive" framing — the real line is "work customers trust a machine with vs work they do not." This post maps three tiers: jobs that will stay deeply human (health, founding sales, investigative journalism, skilled trades), jobs that will transform rather than disappear (design, engineering, teaching, support), and jobs that are quietly becoming the best bets of the decade. A calmer, less LinkedIn-flavoured take on the next ten years.