9 ms·

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

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?

throwatdem12311 1mo ago
You hire juniors but don’t let them use AI tools for a year :)
- sarmadgulzar 1mo 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.
  - throwatdem12311 1mo ago
    The competence crisis in a few years is going to be apocalyptic.
- xmcqdpt2 1mo ago
  I wish but at $work the push has been the opposite. I'm still allowed to write code, but interns and juniors are being told that they need to prompt all the time. I think upper management are hoping they can replace a possibly reticent or AI skeptical "old guard" with AI native Gen Zs. In practice, the young out of school kids are much less excited about AI than the 50 year olds, so I don't know how well it will work.
  - throwatdem12311 1mo ago
    It is going to backfire spectacularly. It’s actually mind boggling to me how stupid business idiots actually are. https://futurism.com/artificial-intelligence/zoomers-ai-sabotage https://futurism.com/artificial-intelligence/zoomers-ai-sabo...
ryanSrich 1mo 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? 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. If an LLM makes a mistake, you should be able to call that out. You might be arguing that a junior engineer may not have the RWE to make those judgements, but by the time you've completed a 4-5 year degree, you should have done the following: - Completed coursework where you've learned the fundamentals of programming and software engineering - Have done dozens of projects (building everything from basic web apps to more advanced pieces of software) where you've seen what works, what doesn't work, etc. This also gives you real world exposure to the latest and greatest frameworks, tools, etc. - Have done several (at least 2) internships where you've worked at a real company writing real code, and have seen/been mentored into what AI is good at, where it fails, etc.
- sarmadgulzar 1mo 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.
  - ryanSrich 1mo ago
    > I’m sorry to say but colleges don’t teach the kinda stuff you’re gonna use day-to-day. This was not my experience in college. A lot of it was VERY applied. Granted, that was 13 years ago. But even so, if you're at a college where you feel that you're not getting enough exposure, that's why I also called out "Have done dozens of projects" and "Have done several (at least 2) internships".
bonoboTP 1mo ago
So, how is this different from years ago when there were software libraries but in class we still rolled our own implementation to understand the algo. For example in machine learning, yes you could just use a Matlab toolbox or libsvm or scikit-learn. But then you wouldn't learn the SVM training algorithm, so we had to implement it ourselves. We knew that we wouldn't roll our own SVM at a job, in production. The goal of the exercise was to learn the algorithm and how it actually works. Today we have AI, which is basically like having infinite libraries available that do what you ask for. But you will not learn if you just take that code, similarly to how you don't learn if you just call scikit-learn to train your SVM. And of course students grumbled back then also and said why do we need to do this when all those libraries exist? Learning often requires not taking the most efficient path for every project.
- sarmadgulzar 1mo 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.

throwatdem12311 1mo ago

You hire juniors but don’t let them use AI tools for a year :)

sarmadgulzar 1mo 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.
- throwatdem12311 1mo ago
  The competence crisis in a few years is going to be apocalyptic.
xmcqdpt2 1mo ago
I wish but at $work the push has been the opposite. I'm still allowed to write code, but interns and juniors are being told that they need to prompt all the time. I think upper management are hoping they can replace a possibly reticent or AI skeptical "old guard" with AI native Gen Zs. In practice, the young out of school kids are much less excited about AI than the 50 year olds, so I don't know how well it will work.
- throwatdem12311 1mo ago
  It is going to backfire spectacularly. It’s actually mind boggling to me how stupid business idiots actually are. https://futurism.com/artificial-intelligence/zoomers-ai-sabotage https://futurism.com/artificial-intelligence/zoomers-ai-sabo...

ryanSrich 1mo 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? 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. If an LLM makes a mistake, you should be able to call that out. You might be arguing that a junior engineer may not have the RWE to make those judgements, but by the time you've completed a 4-5 year degree, you should have done the following: - Completed coursework where you've learned the fundamentals of programming and software engineering - Have done dozens of projects (building everything from basic web apps to more advanced pieces of software) where you've seen what works, what doesn't work, etc. This also gives you real world exposure to the latest and greatest frameworks, tools, etc. - Have done several (at least 2) internships where you've worked at a real company writing real code, and have seen/been mentored into what AI is good at, where it fails, etc.

sarmadgulzar 1mo 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.
- ryanSrich 1mo ago
  > I’m sorry to say but colleges don’t teach the kinda stuff you’re gonna use day-to-day. This was not my experience in college. A lot of it was VERY applied. Granted, that was 13 years ago. But even so, if you're at a college where you feel that you're not getting enough exposure, that's why I also called out "Have done dozens of projects" and "Have done several (at least 2) internships".

bonoboTP 1mo ago

So, how is this different from years ago when there were software libraries but in class we still rolled our own implementation to understand the algo. For example in machine learning, yes you could just use a Matlab toolbox or libsvm or scikit-learn. But then you wouldn't learn the SVM training algorithm, so we had to implement it ourselves. We knew that we wouldn't roll our own SVM at a job, in production. The goal of the exercise was to learn the algorithm and how it actually works. Today we have AI, which is basically like having infinite libraries available that do what you ask for. But you will not learn if you just take that code, similarly to how you don't learn if you just call scikit-learn to train your SVM. And of course students grumbled back then also and said why do we need to do this when all those libraries exist? Learning often requires not taking the most efficient path for every project.

sarmadgulzar 1mo 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.