I was in OpenAI’s first intern cohort. Here’s what it taught me about becoming an AI-native engineer

TL;DR: AI is making it easier than ever to build software that looks impressive in a demo. But after working in OpenAI’s first intern cohort, I learned that the real challenge is not just speed. It is judgment: knowing what to trust, what to test, and when a human still needs to stay in the loop.

AI has made it easier than ever to create software that looks impressive.

A prototype can be built faster. A codebase can be explored faster. A test can be generated faster. A confusing document can be summarized faster. For engineers, this is an enormous shift.

That was one of the biggest lessons I took from my time at OpenAI. I was part of the company’s first intern cohort, and the experience changed the way I think about software engineering in the AI era.

Before that, I thought a lot about becoming a stronger programmer. Afterward, I started thinking much more about becoming a better judge of systems: what works, what fails, what only looks correct, and what can actually be trusted.

I was born in Cairo and moved to Canada when I was 10. For a long time, I thought I would pursue medicine or forensic science. Computer science became interesting to me when I realized software was becoming one of the highest-leverage ways to build products, solve problems, and participate in the future of technology.

Once I made that switch, I tried to put myself in environments where I could learn faster.

My first software internship was unpaid. It was not at a famous technology company or a well-known AI lab. It was with a very early software project led by a Waterloo senior. I could not get a paid software role at first, so I took the opportunity I had and tried to turn it into the next one.

That path eventually took me to Whatnot, then Verkada, and finally OpenAI.

At the time, OpenAI was preparing its first intern cohort. I applied the day applications opened after a friend sent the link in a group chat. Because the cohort was new, there was no established playbook. Nobody could tell me exactly what the interviews would look like or what kind of background they wanted.

I expected the interviews to focus heavily on artificial intelligence. Instead, most of the process tested core software engineering: algorithms, system design, speed, clarity, and judgment.

The bar was not just whether I could solve the problem. It was whether I could think clearly, communicate well, and move quickly under pressure.

That ended up matching the culture I experienced inside the company.

At OpenAI, the pace felt faster than what I expected from a large technology company. I shipped c