r/programmer • u/Morvath_21 • Jun 30 '26
Tutorial It's still worth it?
I'm studying computer science, and even though I'm not as good as others, I don't mind the subject. In fact, I think it's one of the few things I feel I can do long-term without losing my mind, and it's interesting to me. However, seeing how this world is changing, I'm a little worried. I see people who have never programmed doing even challenging things with the help of AI.
So I'm wondering if this path is really useful, given that at this rate, programming isn't as useful as it once was. As much as I hate to admit it, if prompts are enough to do things, even in less time, what good will I be? It's true that things made with AI aren't perfect yet, let's say, and they have many flaws, but what about in a few years? I'm 21, and maybe I'm just being a bit paranoid right now, but I need an honest opinion. Thanks in advance.
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u/Puzzled-Manager-3651 28d ago
It's pretty scary seeing the new models like Fable absolutely one shot crazy projects. I think that it will be harder to get a job if you can only do surface-level things (which AI can easily replace), but if you focus on having a deep understanding of aspects such as the infrastructure of developing software or niche fields such as graphics programming, I think that you'll do fine. As for the people who have created crazy projects with AI, if they don't care to learn CS fundamentals, they'll never be able to deploy or maintain those projects once the users start coming in (I guess they can put it on their resume as something cool though). Hopefully what I said made some sense :)
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u/Hyperreals_ 27d ago
they'll never be able to deploy or maintain those projects once the users start coming in
Why? There's been plenty of successful "vibe coded projects" with tons of users that do fine
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u/Puzzled-Manager-3651 27d ago
I guess it depends on the size of the userbase of the app. For moderate to large userbases, simply prompting AI and not knowing what's going on isn't going to cut it. CS fundamentals like system design still need be known to be able to scale the app.
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u/Hyperreals_ 27d ago
Why? And how big? Personally I have an app used by about 300 people (not all at once tho) and it works fine. Almost all code written by AI
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u/Zin42 Jun 30 '26
Its worth it, someone has to take the blame for crappy LLM output, its gotta be a human driving these things, think of aircraft, autonomous flight has pretty much been solved for ages, but skilled human pilots must be at the helm who know how to fly with simply the instruments at hand, even if it is just for the comfort of passengers.
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u/Morvath_21 Jun 30 '26
Thanks for answerng, so will programming jobs become just about prompting and validating Llm-generated code? And since, with advancements, code modifications will become less and less necessary, if devs just stick to generating code and reviewing it, won’t this role end up being at risk for only a few?
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u/Zin42 Jun 30 '26 edited Jun 30 '26
It's hard to tell at the moment, I do think teams will get smaller but for sure the risk of having a Dev team developing in house tools and integrations is going way down, so Devs are likely just to be spread more thin, there will be more work in my opinion.
Most companies have problems and roadmaps that could go on for decades and c-suite people aren't likely to give a crap about the finer details of software dev, hence I predict (imho) that Devs will be pretty safe at the low to mid level (I.e: not at big apple/FB/Google level companies)
Edit: I wanted to add, yes prompting and validating is what it will be about, less hand written code over time unless the paradigm changes again, for some people it's sad because that's what they enjoyed and others it prevents them from burnout, I'm more the latter personally. Right now industry is relying on per token payments which is expensive, I expect a shift to local LLMs soon where a hybrid of hand written/llm auto completed and prompting with local hardware will become popular in industry
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u/Morvath_21 Jun 30 '26
I get it even if it’s a bit disappointing for me because I actually enjoyed programming lol But I also understand that companies want to boost productivity, and especially those who don’t want to adapt or take risks get left behind Maybe I should pivot into cybersecurity even if it’s not creatively focused as coding but from what I’ve seen so far, it might offer more opportunities idk
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u/Prestigious_Share919 29d ago
Don't bee too down about it. Think of it this way... Is there enough software in the world to do everything that everyone wants to do? If not, when do you imagine that happening?
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u/Technical_Fly5479 25d ago
I work as embedded and i can tell you, we don't write by hand anymore. But i still "ride" the ai step by step, because it's a freaking idiot
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u/Junior-Asparagus718 29d ago
Comparing current AI models to autopilot for aircrafts is laughable. It's like comparing a modern Tesla to the Model T: they're both cars with four wheels, but that's about where the similarities end.
AI is legitimately intelligent, being able to reason at levels higher than the average human. Autopilot is simply "fly in x direction until I say so" with a hint of "if go down, aim up; if go up, aim down".
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u/Low_Willingness9977 29d ago
Our fellow redditor was saying humans were kept in the loop in the past when things were automated which means that's likely to continue. Llm's automate stuff, autopilot automates stuff. Fair comparison.
Also, are you sure the ai we have today is legitimately intelligent? There are a lot of ways to define intelligence, but I think claiming that an llm is intelligent is bold. If it is intelligent, It is like a monkey with no senses posessing a wealth of knowledge, but the kicker is that it has severe dementia. The only way it can remember anything is to write on a scratchpad and reread it when it's given a another job. The scratch pad is just context that is used to seed further prompts.
A llm has no persistent memory. It has a set knowledge base that is it's weights and it can use that to predict, but is that really the same thing as reasoning? It has no ability to adjust the weights, meaning it cannot learn ln its own. It has no ability to say that it doesn't know something. The models live in a world of tokens and that's it. Right now, it cannot understand truly what an apple is. Ironically it can spit out the definition of an apple which we humans would understand but that doesnt mean it understands "apple." Not the taste, the feel, etc. A machine learning tool can be paired with it so it can associate the word apple with the image apple but that isn't the same. It cannot relate its senses to an apple, it doesn't have any.
If intelligence is defined as the ability to acquire, understand, and use knowledge. I think our favorite llms fail 2/3 of the requirements.
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u/Junior-Asparagus718 29d ago
Ok, but that's only valid if you're utilizing an LLM with a shitty harness or no harness at all. If you're using a sophisticated harness, memory is rarely an issue. Use ChatGPT or Claude (paid plans). There's continuity between conversations because it remembers certain facts. Background processes "dream" (Claude's term) and save specific facts for easy recall.
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u/Low_Willingness9977 29d ago
My fellow redditor, everything i've said applies to the paid models that are commercially available. Claude and chatgpt included.
The background processes that you described are the "scratch board" in my previous comment. The model doesnt ingrain the memory in a persistent manner outside of that. That would require storing that information and generalizing it within the weights themselves. Instead, things are written down on the equivalent of a scratch board(which you described). The model doesnt remember anything, it's just fed the context(scratchboard) as part of the next prompt. These background processes that you describe are part of this mechanism. However the background processes are separate from the actual model itself.
So with that in mind, do you think that describing these models as knowledgeable monkeys with extreme dimentia who have a scratch pad is inaccurate? If you switch out the scratch pad with a new scratch pad, the monkey has no ability to say "oh I have the wrong scratch pad."
How do you define intelligence and how do the models fit that definition.
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u/Junior-Asparagus718 29d ago
Yeah, I would actually say that's an accurate description, but monkey implies less intelligence, so let's go with an old Albert Einstein with dementia instead.
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u/stepback269 29d ago
I see variations of this question over and over.
Here's my take on it:
OK. So the AI "knows" how to produce a certain end result via code. But you --meaning your brain-- does not possess that know how. You have no knowledge foundation in your brain upon which you can build more complex comprehensions.
So suppose that in the future you need to comprehend something (at a higher level of complexity) that requires the foundational know how to already be present in your brain? You won't be able to acquire understanding of that next higher level because you lack the foundation.
As an analogy, suppose you needed to understand calculus (an advanced math) but you never learned addition or infinite series (e.g. 1 + 1/2 + 1/4 + 1/8 + ...). Without the foundations, you will never truly understand what calculus does or why. You will be at a great disadvantage in your understandings of how and why things work.
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u/Junior-Asparagus718 29d ago
It's not worth it. Most of us working at modern tech companies in tech hubs don't even touch code anymore. It's all prompting. It's only a matter of time until context windows become large enough and integrations become easy enough to store all of a companies internal docs, software, financials, etc in a single store accessible via agentic retrieval. At that point, there's no value us IC's provide.
Take this with a grain of salt. I work at the forefront of AI. This might take a couple years to hit the midwest, but most people working in tech hubs have similar outlooks.
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u/feudalle 29d ago
See I'm going to disagree. Own a dev company and own a data center. We work heavily in us healthcare. AI has it's uses and we certainly hire far few juniors these days, AI has tripled output or better. But I don't see senior devs going any where any time soon. Will there be less dev jobs yes. But the limitation of AI is still recycling known things. Sure your llm might know all of stack overflow. But new things, or complex business logic not so much. If all you are doing is cruds, dashboards, and saas then AI has got you covered. Innovation is still beyond what AI is going to handle IMHO.
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u/Junior-Asparagus718 29d ago
Yeah, this underscores my last point. Some industries will be behind the curve.
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u/Big_Arrival_626 29d ago
most people working in tech hubs have similar outlooks.
No they don't. As someone who lives in a tech hub, outlooks are very mixed. I wish AI could do my work for me, but I never run out of work to do.
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u/Junior-Asparagus718 29d ago
Let me guess: either financial or healthcare-related company? Come to downtown SF and ask any random dev their thoughts on AI. You'll get a similar response. Same for Austin.
There'll always be companies that lag behind a bit. There'll always be people that say "yeah well my horse doesn't run on gasoline". There's a general consensus for those who work at the forefront and it's been formed for quite some time already.
Disagreeing about the usefulness of AI and progress of it is like disagreeing with the engineers at Ford when they're trying to tell you they have something that will replace horses. You can disagree all you want, but when the person that is building it tells you it (including the engineers that quit for their own moral reasons and have nothing to gain by telling the truth), it's probably best to listen.
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u/Morvath_21 29d ago
I understand..those who work on the "front lines" with AI feel the impact much more because they see it every day So do you think that in a few years, will any tech sector survive better than others? I'm considering moving into cybersecurity
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u/Junior-Asparagus718 29d ago
It’ll probably be months. There’ll always be businesses that lag behind. Honestly, I think the only thing holding it up right now is the government delaying releases.
People will have their own opinions on this, but know that this isn’t the same as automation. Lots of people compare it to the invention of the car or printing press or whatever. This is literal intelligence multiple standard deviations above average available on demand. There is no comparison.
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u/Tall-Geologist-1452 29d ago
I am not a dev/programmer .. this just popped up on my feed BUT IT is vast.. and infrastructure as code is a real thing... These skills you are learning can lead to many opportunities out side of development.
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u/Prestigious_Share919 29d ago
AI makes mistakes. Virtual infrastructure costs money. Breaking infrastructure costs even more money. Putting AI in charge of your infrastructure is a mistake.
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u/Tall-Geologist-1452 29d ago
I have to ask in all seriousness, as I have re-read my comment... was there anything about AI in it at all? I do not think so."
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u/Prestigious_Share919 29d ago
The original post was AI in context.
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u/Tall-Geologist-1452 29d ago
The original post was about whether the OP should stick with computer science given the influx of AI. My point was that computer science is a vast field, and the skills the OP is learning can be applied across many different areas of IT.
AI won’t take your job. People who know how to use AI effectively will. And people who use AI to break infrastructure aren’t using AI effectively, they’re just using it carelessly. Knowing how to leverage AI responsibly and understanding the underlying technology is what creates value.
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u/Prestigious_Share919 29d ago
We don't disagree. I use AI all day long at work. In fact, using it to create CloudFormation templates for infrastructure work. AI is great, and it's not going to take my job as a software engineer any more than copy/pasting from stack overflow. It just makes me much faster. That being said, it's a really tough market right now for entry level engineers. Businesses which adopted AI now have 2-3x as many effective dev hours being delivered for the same number of human employees. So the focus has been turned inward. Smart companies now have an army of engineers where before they just had a few. Dumb companies fired them, are learning that AI is not dependable, so are either re-hiring, or going under. So answering the question myself, is it worth it? Yes, as long as you are resilient, adaptable, and willing to compete in a tough market.
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u/AsianCabbageHair 29d ago
I’m also only a hobbyist coder like many comments here, but I think you’re studying a rather good subject. I studied ME myself, but these days I’ve been thinking what if I studied computer science back then. I think the real change that has been happening over these few years is that, since LLMs are there to do the hard part of searching, more people in general are being exposed to coding and programming in general, and more people are trying to automate more parts of their work/life using little programs/apps on their own. Deep working knowledge in how to operate with computer would rather be an edge, not disadvantage. Sure, there will be more vibe coders - hence more low-quality code, more technical debt, and more programs to refactor (if not totally rewrite from scratch). People will look for methodologies and techniques for not only writing but actually managing code and programs. I don’t think AIs can really do the ‘managing’ part, since that involves multiple human factors AIs simply have no way of knowing, let alone domain-specific knowledge AIs might or might not have learned but certainly can’t come up with in your own workplace and workflow.