sarmadgulzar

Joined 4 years ago

Karma
40
Submissions
42
Member since
Jul 14
I build fast and efficient software, mostly using Rust.

X: https://x.com/sarmadgulzar GitHub: https://github.com/sarmadgulzar Email: [email protected]

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Recent submissions

Comment · 16 hours ago
You haven't posted on YouTube in a year or so. Working on any long-form videos we can expect to see anytime soon?

Anyway, loved your "GPT from scratch" video btw!

Comment · 16 hours ago
Wow, this is genuinely so good. I just browsed it for a few minutes and the difference between this and the YouTube homepage is astounding.
Comment · 2 months ago
I wish more people understood that prototype != product
Comment · 2 months ago
Exactly, I absolutely agree that AI supercharges seniors with judgment and conviction. They’re no longer constrained by how fast they can type.

But this is about what comes next i.e. seniors of tomorrow

If AI gets so good at software that vibe coding is the new norm and as Elon Musk says that AI will generate the machine code directly without any intermediate compilation or interpretation then we wouldn’t need seniors or juniors but I don’t think that’s coming any time soon, if at all!

Comment · 2 months ago
Sure you can do it but I think you’ll agree with what I said about ownership. Whenever I ask AI to audit my codebase, it always plays it safe and gives me a few options to choose from. It just won’t give me a concrete answer unless I insist it to give only one but then I wouldn’t trust that answer that I basically forced out of it.
Comment · 2 months ago
Agreed. I’m not insinuating that colleges should teach all of these extremely domain-specific things. Most of the stuff would indeed be unnecessary for most students depending on what they do in the future. But that is my original point that you learn this on the job while making a mistake and being corrected by a senior mentor. AI wouldn’t call this out by itself unless you give it a very specific prompt which you also can’t write if you don’t know that these kinds of problems happen in the first place.
Comment · 2 months ago
Precisely my point. But unfortunately companies are rushing to get the features out. No cares if you’re learning and augmenting your own understanding or not.
Comment · 2 months ago
> Shouldn't this be a pretty fundamental part of a degree? If you're in school right now for a CS or SWE related degree, I would imagine you're learning how code actually works, how the math actually works, etc.

I’m sorry to say but colleges don’t teach the kinda stuff you’re gonna use day-to-day. They’ll focus on architecture, data structures, algorithms, databases, OS internals theory that only a minuscule number of systems engineers would get to work on. They won’t teach you that in your /login endpoint, if a user is not found, you should verify the password against a pre-computed dummy hash so the response delay matches a real user account workflow to avoid timing attacks. You only learn this on the job under the supervision of a senior mentor.

Comment · 2 months ago
Stakeholders are not technical enough to understand that so CEOs won’t do it. We are already seeing it play out. Entry-level hiring has been consistently down ever since AI got mainstream.
Comment · 2 months ago
This all sounds good on paper but I have an honest question: How do you develop judgement as a junior or mid level engineer to critique AI if you yourself never learned that skill by making mistakes in the first place?

I’m not saying that all code should be typed by hand in 2026 but there are certain subtle things you learn only when you get into nitty gritty details especially related to security.

Also today’s AI is notoriously bad at ownership. When you ask it to give you a concrete answer, it will still give you options with pros & cons of each so that ultimately you own the decision and not it. So how do you decide between the two (or more) when you never learned to do it yourself?

Comment · 3 months ago
> AI has, multiple times already over multiple different era's definitions of what counts as "AI", been used to invent new things that humans have not been able to.

Can you give a few specific examples?

> They can be superhuman one moment and amateurish-to-childlike in the next.

Even the smartest humans are like that. No one is best at everything. Which brings me to another question: Is a know-it-all ASI actually possible? If so what's the bottleneck? The current approach, the data or the compute?

PS: These questions are kinda pointless. I understand that we don't know how to answer them yet hence I'm not expecting them to be answered. Just your general thoughts.

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