More STEM graduates than almost anywhere on earth, and very few companies building the infrastructure layer. The gap starts at 17.
India graduates more engineers than almost any country on earth, and has built a genuinely world-class software products industry. What it has far less of is companies building the underlying infrastructure — chips, energy systems, aerospace hardware, frontier AI. The gap is not talent. A large part of it is exposure: most students commit to engineering at 17 without ever having spoken to someone who builds things for a living.
India's software product ecosystem is real and globally competitive. Companies founded here sell products worldwide rather than staffing someone else's roadmap, and that shift — from services to products — took two decades of accumulated capability. It does not get said enough.
Look at the categories that will define the next decade and the distribution looks different. In the Hurun Global Unicorn Index 2026, the United States counts 806 unicorns and China 381, with India fourth at 61. In artificial intelligence specifically — the fastest-growing category, and the largest single share of global unicorn value — the US has 132 and China 47.
China's largest unicorn categories are semiconductors, AI, life sciences, new energy and robotics: infrastructure layers, almost all of them. India's strength sits higher up the stack.
This is changing at the edges. Skyroot Aerospace became India's first space-technology unicorn in May 2026. That it was notable enough to be a first is itself the point.
Both are legitimate. One is a very good outcome. The other is the one still mostly happening elsewhere.
It is not the engineers. India produces STEM graduates at a scale few countries match. The more uncomfortable question is what those graduates were optimising for when they chose.
Most students pick engineering at 16 or 17. They pick it because it is safe, respected, and approved of at home — and because the alternatives were never made concrete enough to weigh against it. Very few have spoken to a researcher, a hardware engineer, or anyone who has built something that did not exist before. They are choosing a label, not a working life.
A pipeline optimised for safety produces exactly what you would predict: excellent execution, cautious ambition.
A seventeen-year-old cannot want a career they have never seen. Deep-tech work is largely invisible to school students — it has no equivalent of the doctor or the software engineer in the family. The result is not that students reject it; it is that it never enters the choice set.
This is a solvable problem, and it is different from the capital problem or the policy problem. Those matter too. But funding does not create founders who never considered the field, and a student who has spoken to someone doing the work evaluates the option differently — sometimes choosing it, sometimes rejecting it for better reasons.
The wider framework for that decision is in how to choose a career after 12th, and the map of options most students never hear about is in career options after 12th.
Probably all three, interacting. Capital follows founders; founders come from people who once chose a direction; that choice happens at 17, usually with almost no information. Fixing the funding environment matters. So does the question of who a student got to talk to before deciding — and that is the part almost nobody is working on.
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