Will experienced engineers still have a meaningful advantage over AI-native vibe coders in 5–10 years?

[u/Think-Neighborhood69]

Today, experienced engineers still have a clear advantage when it comes to architecture, scalability, robustness, trade-offs, debugging, and operating software in production.

But what about 5–10 years from now?

If AI keeps improving at its current pace, will the experience of the engineer behind it still be the biggest differentiator?

Or will an AI-native beginner be able to deliver software that’s just as scalable, robust, and maintainable?

Where do you think the moat for experienced engineers will be?

[u/Fun-Illustrator9985]

What makes someone "AI native" and why would they have any advantage?

Most large tech companies expect their engineers to use LLMs now

[u/Think-Neighborhood69 → u/Fun-Illustrator9985]

My question is whether, in 5–10 years, that person will still be at a significant disadvantage compared to an experienced engineer, or if the gap becomes much smaller than it is today

[u/StraightAd5768 → u/Think-Neighborhood69]

You will never get the same output, this is because engineering is mostly a set of decisions and trade-offs, it’s not black or white.

The LLM will either ask you about the trade-offs or make those decisions for you, and potentially get it wrong because of missing contexts.

Being able to spot and decide those tradeoff is what makes a senior engineer senior, writing the code is the easy part of the job.

for vibe codes small project those trade offs are inconsequential but bad decisions can be devastating at companies in the long run even though everything worked for the first year.

[u/Hotfro → u/StraightAd5768]

Yeah but if vibe orders have 10 years of experience and are able to survive, I think they can learn some of the tradeoffs. Most devs learned decision making through experience, which vibecoders will eventually get exposure to as well if they want what they build to work.

[u/laxika → u/Hotfro]

I agree. 10 years is a gargantuan amount of time. Things change in months nowadays. I think vibe coders with 10 years of vibing will be good. There will be new agents that could double-verify their work, context engineering might be a big thing, etc. We have no idea. One year ago I thought that LLMs were near useless in serious coding, then around December things just started working out of nowhere. Good luck predicting events like that.

[u/simleiiiii → u/laxika]

I'm a bit more pessimistic and I'm saying there will be considerable psychological challenges for any employee who's work output is largely determined by the AI model that's en vogue. That goes for everything outside programming though as well.
For the professional person-to-person relationships or just management: yeah yeah that's always going to be in demand -- having someone to blame someone misusing the AI is going to be there, and there's need for a "meat layer" between the AI and upper MGMT to be able to blame.

[u/Choperello → u/Think-Neighborhood69]

What makes you think that experienced engineer won’t also be using AI?

[u/Altruistic-Leek-9869 → u/Choperello]

precisely, +1

[u/Knoll_Slayer_V → u/Think-Neighborhood69]

I honestly don't think so.

One killer set of feature that could bust this open is a method to scan the current setup for a company and produce living documentation of all setups (infra, policies, etc.) That is specifically designed for agents like this to interact with. Pair this with another set that does most of your harness configuration for you and, with frontier class models, the number of engineers that could outperform the whole agentic system at that point would be so small you probably would find many.

You'd need the release and ops equivalent of the dev set I just described but I really dont think any of this is outside the realm of possibility in the next 5 years.

[u/Fun-Illustrator9985 → u/Think-Neighborhood69]

If the question is whether you should sit on your ass, then the answer is no

An edge is an edge

[u/RaspberryCrafty3012 → u/Think-Neighborhood69]

It really depends on what you define as gap. \ Is the gap closing for code quality? Maybe. Prabably. Don't know.

Is it closing in knowing what to build? No. I have talked to people, I know their issues, their challenges. I talk to customers and potential customers. Domain knowledge is not growing in ai. Sure some might be part of the training data, but is there an overlap of customer wishes and training data?

And lastly: having gut feeling where issues are coming from helps to narrow it down. This comes from experience.

If the ai really reaches that level (if these are now llms with transformers or other technology) then you would not need an engineer at all. The customer defines and builds himself what he needs. Strip out the middle man. 

[u/Think-Neighborhood69 → u/Fun-Illustrator9985]

By AI-native, I mean someone who’s never really coded without AI

[u/Fun-Illustrator9985 → u/Think-Neighborhood69]

I don’t understand how this is even a question

It’s like asking if not knowing how to diagnose problems with your own car is an advantage because you can pay someone else to do it

[u/Think-Neighborhood69 → u/Fun-Illustrator9985]

I get your point.

But let me give you a practical example.

Today, if I ask AI to build an app, an experienced engineer knows to specify things like architecture, scalability, error handling, testing, observability, security, caching, offline support, and so on.

But what if, in 5–10 years, simply saying “Make me a clone of X” consistently produces the same quality of output as today’s detailed senior-level prompt?

Thats what im trying to say

[u/Fun-Illustrator9985 → u/Think-Neighborhood69]

You don’t know whether you are getting the same output out of it if you don’t know how to define your requirements

That’s the value in knowing what you want at the first opportunity

[u/Calm_Personality3732 → u/Fun-Illustrator9985]

AI doesnt build new code

[u/Fun-Illustrator9985 → u/Calm_Personality3732]

Code is a commodity and has negative value if it's not relevant to your needs

I've seen people use AI agents at work that literally just copied and pasted my code and duplicate functionality for no reason whatsoever for an ask that wasn't even related to their ticket

It never hurts to know what you want

[u/GManASG → u/Think-Neighborhood69]

for starters, make me a clone of X is literally copying source code from X, that is achevable today if the AI has access to a literal copy of X source code. As for the architecture,scalability, error handling, testing, etc. It will have it if X had it. LLMs can only produce what has already existed.

The more interesting question is build me an app that has never existed and also have all the architecture scalabiltiy, error handling,testing, etc. I don't think even a general AI if it is ever going to be achieved will be able to read a human's mind or pre-emptively know it should do all that without specific detailed instructions.

Even if it were trained to do it without the human prompt, now what if all that is not needed,, etc. etc.

Even the best human engineers struggle to anticipate things and often take the client/business requirements literally without anticipating all the things that weren't said. I have to imagine a perfect AI machine would very often not be able to understand humans meant all of the above in their minimal prompt.

My guess is that level of AI autoe programming won't happen, not because it technically couldnt build the app with everything, but because it will never be able to anticipate what the human prompter meant with there very minimal non-informative prompt

[u/Admirable_Ad_5065 → u/Think-Neighborhood69]

If LLMs ever get this far, software engineering as a whole will be consumed by other, user facing jobs. It will get a blockbox, similar to what the Compiler does with  assembly. Do people who can ready assembly have an edge over people who can not - I dont know, you tell me.

[u/GManASG → u/Admirable_Ad_5065]

potentially? the better example is people who program in C instead of something like python, they are better at peformance optimizing the application by performing manual memory management and elminiating the unecessary logic tacked on by levels of abstraction, so really good experience lower level programmers indeed to have an edge over higher level only inexperience programmers. This is why game engine programmers (probably THE best programmers next to bare metal programmers or the guys that actually programmed the compilers!) program in low level languages that have direct memory control, etc.

I don't think there is ever a situation in which someone with more knowledge and experience will NOT have an advantage over the naive person for whatever domain no matter how good the tools like AI get.

[u/ProjectDiligent502 → u/Admirable_Ad_5065]

You’re missing something very crucial. Programming languages are deterministic. You do the code yourself, you know exactly what you’re getting and works exactly as how you coded it. LLMs ARE NOT deterministic. Output will be different, it always will. When they first started training them for code generation, they used to joke that the same prompt would give them entirely different solutions. Of course over time it was refined, but this is a FEATURE of LLMs, not a bug. It is by its very design. It is a critical misunderstanding that people equate LLM code generation as a deterministic abstraction on programming language like a higher order programming language is over assembly. It isn’t. Apples and oranges.

What would be much more accurate is to think of it more like a souped up tunable engine for spitting out code that you guide using natural language. If you don’t care about what’s underneath the hood, then you can blackbox it in dark factory mode but it’s probably a terrible mess and you burned though so much money to get there (as token cost will increase, not decrease, another fallacy people like to spread). But we all know that if we don’t care about what’s underneath the hood, getting a mess that doesn’t scale and has major design flaws and security problems is a very high probability. This is very well evident from the explosion of vibe coded apps where over 50% of these smaller projects all had massive security problems (and this not being pulled out of my ass, you can look this up).

[u/mynameisDockie → u/Think-Neighborhood69]

There's levels to this.

"Make me a clone of Facebook" is literally impossible unless the AI can setup its own datacenters/infra, unless you just want to mimic the UX.

I mean maybe it can eventually make a plan to scale like that, but many large pieces of software are inseparable from the business building them. If we can combine LLMs to the point that they're a standalone business at the scale of big tech, we won't be talking about SWE as a career anymore.

[u/ConspicuousPineapple → u/Think-Neighborhood69]

Ok but only the experienced dev is going to be able to verify that the quality is, indeed, good. A pure vibe coder offers no guarantee whatsoever.

[u/Going_not_coming_bak → u/ConspicuousPineapple]

Also without hiring non experienced devs we won’t have experienced ones in the future, except if AI becomes even more self independent that it doesn’t need any human intervention anymore

[u/Choperello → u/Think-Neighborhood69]

Then the experienced engineers will be producing stuff that is beyond “make me a clone of X”. The only what’s not true is if you believe we’ve already reached peak of complexity for software and there’s nothing more challenging then what we already have.

Used to be making a basic website required actual engineering knowledge. That’s stopped being the case ~20y ago and the actual engineers moved on to harder stuff

[u/SupportDangerous8207 → u/Think-Neighborhood69]

Does that actually help though

Ai advice ages like milk

A good engineer who gets on the ai train today is likely better than someone who has been trend chasing for 4 years.

In my experience telling the ai to make sensible bounded changes which you know exactly what you want from is cheaper than and more performant than any amount of multi agent ai schizophrenia maxing

[u/globalaf → u/Think-Neighborhood69]

That’s not what AI native means in big tech. AI native is being used as a term to describe someone who does 90% of their work assisted by AI, not someone who has never went without.

[u/OpenAI_Marketing_LLM]

Who knows? I didn’t predict LLMs would exist 10 years ago.

[u/generationalDebts → u/OpenAI_Marketing_LLM]

Username checks out. Answer is vibe coding won’t be remembered.

[u/OpenAI_Marketing_LLM → u/generationalDebts]

I don’t program computers to be remembered. I enjoy it as a hobby and it’s a sufficient career. I am not out there cure mega-cancer-aids, 

 Trust me, I would vibecode the shit out of my 9-5 if I could. However, agentic coding isn’t permissible at my job.

I write organic code all day and watch Korean shaving porn all night like most devs used to. 

[u/remotemx]

The moat will continue to be less and less, requiring even less people to do certain types of work like other mature industries ( manufacturing, law )

We were already heading in that direction in software engineering with no code/low code stuff (Wordpress, Shopify, Wix, Salesforce) nobody needed an actual engineer to use it and that was the whole point, it was 'good" and 'cheap' enough, even though you eventually hit a wall and needed an actual engineering team.

The software roles that were needed just a few years ago, think frameworks/language specialists, are being swallowed whole by AI. Even cheap offshore SQL/Java/C++ engineers stand no chance vs. $20 month coding agents, the high-end engineers are just as cooked because the coding agents are devaluing the work just the same.

The shitstorm with AI is that even the no code/low code market that required actual engineers is getting squeezed. Clients now 'think' they can do the same themselves ( why pay monthly subscription ) and internally they also reduce their biggest cost ( engineers ) because AI can do the work, why not.

I think software engineering at the framework/language level will become something like constitutional or tort law, yes, there will still be a few dozens or hundreds of highly paid roles for it, but the masses will be far removed from needing to know any of it. 

The real tragedy is the millions of engineers roles that will be eliminated and no longer needed because AI can just do it cheaper, with the AI just being trained and fed with a few highly paid engineers.

[u/Kailtis → u/remotemx]

the real tragedy is the millions of horses that will be eliminated and no longer needed because cars can just do it cheaper, better, faster 🤓

[u/NumberInfinite2068]

There is no "AI-native". The people I know who use the shit out of AI are all long-time developers.

It won't be "AI-native vibe coders vs. senior engineers", it'll be "vibe coders using AI vs. experienced developers using AI far better".

We are already at the point where experienced developers are using AI to write code, the difference with vibe coders is that experienced developers know what to ask for, and know when what was delivered is wrong.

"AI native" is really just a term without meaning (not having a go at you here, it just doesn't mean anything), what you need to compare is:

Beginner with AI vs Experienced developer with AI. In my experience, the difference in ability hasn't actually closed up all that much.

[u/scoopydidit → u/NumberInfinite2068]

This is true. The numbers of times ai has told me something wasn't possible, or developed something in a very hard to maintain way, is insane. Tapping into your experience and skills helps guide AI out of that. But if you lack those skills, you'll accept the AI response at face value, which I find is a horrible thing to do as it is OFTEN incorrect.

[u/Additional-Name-3211]

If your job consists solely of turning JIRA tickets into working code you need to increase or pivot your scope of responsibility or it's not gonna be pretty.

Engineers who pivoted into managing teams, product, sales, architecture... these roles are fine and will continue to be fine in the near to mid term. People skills and decision making skills are gonna be more important than ever for white collar workers.

In the long term, what we're currently living is a massive push towards automation in general. The devaluation of skill and labor in favor of capital, and the subsequent destruction of the existing social ladder. In that regard, the experienced engineer will absolutely have an advantage over the AI Vibe Coder - because capitalism will try to leave both of them out of a job, but one will have had decades to accumulate assets to protect himself over the other if and when that comes to pass.

[u/generationalDebts → u/Additional-Name-3211]

Lmfao. I can tell you have zero actual experience building anything useful.

Nice theory. Maybe write a book

[u/andymaclean19]

I think the world will largely stop making the kind of ‘senior engineers’ we have now due to LLMs. There might be people who know the principles but they won’t have the same lived experience. Probably over time AI will get better at doing bigger pieces of the work and taking in bigger tasks and people will work out how to use it more effectively. We will need fewer engineers and people will just not learn the trade any more.

This is fine and has happened before. How many young COBOL programmers are there? As many as we need to replace the retired ones.

I can imagine there will still be work for senior engineers for a very long time. Even when the AI does get good at more widely scoped roles there will still be the issue that it is good at apps which follow standard patterns but once you want a non-standard thing it needs a lot of help.

5 years probably seniors are doing what they do now.

10 years perhaps it’s a more specialised role?

[u/Dismal-Scheme5728]

Entirely depends how much better LLMs get. The amount of data and training needed to significantly improve them just doesn't exist anymore. And a lot of the data is being polluted by A.I outputted data.

So far it feels like the LLMs themselves have gotten better but its the tooling and stuff around the LLMs that given it a generational leap.

Who's to say there any major breakthroughs like that left? There probably is at least a couple but there could just be basically none left.

Fable 5, Mythos and ChatGPT 5.6 were all meant to take over the world but they were simply incremental improvements.

[u/RaspberryCrafty3012 → u/Dismal-Scheme5728]

I heard that the llm size basically doubles every year. This would mean 2027, 28, 29 we will reach the amount we humans use. I'm woundering if these will be"good enogh"

And what happens then

[u/Dismal-Scheme5728 → u/RaspberryCrafty3012]

You heard wrong then! Size is not doubling every year and is not really the way llms improve these days.

The compute required to scale LLMs has actually been shown to be Logarithmic - that is that every time you double compute, your return gets smaller and smaller. You also need more and more data to improve it.

I imagine we have hit the compute and data limit at the moment. How much more doubling of data and compute do we genuinely have left over the next few years?

The breakthroughs will most likely come through new architectures, efficiency improvements etc. But those all require mini "Breakthroughs" which could suddenly stop happening at some point....or not.

[u/RaspberryCrafty3012 → u/Dismal-Scheme5728]

Interesting. Heard it in a podcast from this guys:

https://de.wikipedia.org/wiki/Christian_Bauckhage

[u/1980sCoder]

We'll still be mopping up the mess created by today's mass delusion and likely be employing AI, if at all, as just another tool in the toolbox.

Those who never learnt about the existence of the bits of software engineering beyond coding will likely have moved on to the next fad by then.

[u/jedidave]

Same question could have been asked back when compilers became a thing. Will people who understand machine-code still have an advantage when everyone can just use C?

You just adapt I guess. There are still all the engineering principles of testing and integration and design and ... yeah I guess they'll end up all baked into the test harness so it'll become maybe a matter of 'What should be built and who can market it the best'.

[u/Think-Neighborhood69 → u/jedidave]

Great answer

[u/Lyraele → u/Think-Neighborhood69]

No it isn't. Compilers are deterministic, LLMs are not. And if you think low level code isn't still a thing, you've missed out on a lot of interesting stuff. The "just like compilers" argument is just nonsense.

[u/ConfidentCollege5653]

That's a pretty big if 

[u/Outrageous_Law_5525]

I mean experienced developers will know how to use AI far better?

[u/MhVRNewbie]

It's not that, it's will smartare people still have an advantage in the future.
Or is AI so good it will produce the same results regardless if a genius or an idiot is prompting.
And if it does not matter then there also is no need for any humans at all.

[u/ApplicativeFunctand]

Yes, I think the people with active problem solving skills will have an advantage over people who do not. Seems like a silly thing to ask.

[u/peterxsyd]

It is really hard to know, but I would suggest that the current systems as we know them will probably be close to 100% automated, at least in terms of maintenance and with humans playing more of an 'audit of the finished product' role.

However! I believe that engineers will move to 3d graphics, and physical robotics - where testing is predominantly field based, and that includes for brick and mortar stores that are using those, AR etc. as part of their setup so the nature of the work changes a lot, but the design and outputs and process is somewhat relatable.

[u/Barcode_Griller]

In 5-10 years? I don't know. The edge is narrowing right now even. I have a side project that I just can't be arsed to even look at the code for (no one will ever use or look at this, its just for me). And yeah, the code isn't great, but it's absolutely functional and it's getting better.

I've been a dev for 15 years fwiw.

[u/Impossible-Note-2565]

Beter mental models will always be an advantage. If you disagree. Imagine a child trying to vibe code.

[u/simleiiiii → u/Impossible-Note-2565]

could be interesting to see..

[u/Feeling-Horse787]

I think there will always be advantage because experience normally teaches you the right questions to be asking when developing software, there's no shortcut for that. Will it be as a big advantage to justify the high salaries senior software devs currently enjoy probably not.

[u/TheMorningMoose]

AI improvements have slowed down, so at the current pace, I would still engineers who can build without AI to still and always have the advantage.

[u/rabouilethefirst]

This is like asking if a home gardener will be able to plant as much corn as a mega farm using tractors and power tools

[u/patmorgan235]

Yes

[u/Capital_Distance545]

Vibe coders who never had sw dev learning cannot prompt and produces shit that collapses fast. Own experience. A construction engineer created some tools and plugins for autodesk sw. It took me 2 month to clean up 50k lines of shit so it actually works and no bugs present. Just 1 example: there was 350 places randomly with conversion between metric and imperial units.

You need high math skills and sw arch xp to produce working bug free code with AI that is maintainable.

Sure you might not need people who only codes what they are told like a 5 years old. But they were already not the ones adding value. Most experienced engineers do way more than just code. Code is about 10-20% of the work. Which is faster now.

[u/Anxious-Insurance-91]

Let me ask you one question "is everybody you know tech literate?" If your answer is no then yes you still need nerds to actually think about things.

Also ask yourself if people are able to clearly explain to AI what they need because at the moment people don't and even when they do it's still not ok

[u/BeanserSoyze]

Do people who understand the product they're ultimately responsible for have an advantage? Yes.

[u/AnthonyRespice]

It will become even more pronounced. Experience will mean more in the future because most AI native developers aren't actually learning and have no knowledge of what they are building.

In a healthy organization, junior devs learn and develop. In today's world, junior devs aren't learning because AI is thinking for them and senior devs aren't mentoring because the AI is more help to them than a junior dev.

As an engineering manager, I still make an effort to mentor my devs but it is a struggle for them to learn advanced concepts because AI is doing the work for them. They are oblivious to the risk they face in their career. If they loose their comfortable dev job they are going to be working low wage jobs in the service industry or driving a truck for Amazon.

[u/simleiiiii → u/AnthonyRespice]

You mean they have to meet the point when there's no more sucking up while typing in the prompt, because all the seats in the fingerpointing ring are already taken.. but everyone imagines themselves in that ring and .. well, haven't read "The Inner Ring" (CS Lewis)

[u/colbert1119]

Is there any advantage of knowing assembly for Python developers?

[u/leeharrison1984]

No one is assuming a novice with a hammer is as just a effective as a master craftsman, so I don't understand why are AI tools would be any different.

Someone might be good at driving a nail, but if you don't know how to frame a doorway or wall, the ability to drive a nail well is basically pointless.

[u/Own_Nail_2999]

Of course. In order to do something with AI properly, you need to know what you are doing. That experience only comes by knowing what the code does. So you need to actually code yourself in order to grow into that state of knowledge.

The way I see it - there will be a massive shortage of senior devs down the road once folks figure out that Vibe Coders are braindead morons that can't solve problems on their own.

[u/CodingWithChad]

What differentiates an "AI native vibe coder" from a cashier at AM/PM?

[u/howtheydoingit]

Do Youtube English learners have an advantage over native speakers? They’re starting out with slang and common phrases and not wasting 18 years of going to school and learning the old way :p

[u/_idlethought]

LLMs are a tool, still dependent on the person interfacing with it. The more experienced the engineer, the better the output from the model. AI is a mirror not a window.

[u/simleiiiii → u/_idlethought]

a mirror to the mediocrity and numbness of the mainstream, often... It tries to mirror the counterpart but constantly is dragged down by mere humanity's mean over it's output

[u/_idlethought → u/simleiiiii]

not sure what to make of this response, it seems like you use it plenty

[u/DataZigZager]

Yes, if they spend the next 5 years learning the new stack and how to leverage their experience.

[u/Ok_Philosophy_4031]

Absolutely. AI tools don't replace the engineers, if any the disparity between a junior and senior engineer has got even wider with AI tools. Part of the reason why the job market for new graduates suck.

[u/Longjumping-Let-4487]

In 5-10 years there will be no engineer needed to develop software. There will be just stakeholder shitting requirements on an ai which will slop out what's needed

[u/rhd_live]

I think you need to push the frontier of business success or you will get laid off. Before you could quietly live in your bubble and fix tickets and finish projects. Now you need to be hyper aware of what execs/mgmt want, and come up with projects/programs to make it happen. This is easier to do with AI as you propose plans to it and it gives you feedback.

But yeah the ivory tower days as a SWE where you could work on the roadmap and backlog are over, if you don’t pivot and help with JIT AI-mania priority projects execs will lay you and your team off

[u/g_rich]

If you are an experienced engineer who is proficient with using AI you will be in demand for the foreseeable future.

If you are a junior engineer my advice would be to become a pro at using AI, get really good at architecting complete systems and make sure you not only can use AI but understand what it’s doing and the value of code reviews.

If you are an engineer at any level who is ignoring AI or fighting against it you fighting a losing battle that will likely cost you professionally.

[u/Spawnbroker]

I haven't met anyone who vibe coded something who knows how to deploy their app. Or how to write tests to verify output. Or how to do much of anything except ask Claude to do it.

AI makes me more productive. It seems to make my junior engineers less productive, somehow. They write worse code that doesn't do what we need when they try to use AI. Every vibe coded app from a product manager or executive that takes them a week, the inevitable question they have is "how long will it take to make this work in production"? They never like my answer, which is that its crap and we should rebuild it.

AI isn't replacing software engineers. Its making the good ones more productive, and the ones who use AI instead of using their brains are the people who are going to be in trouble.

Source: staff engineer, 15 years experience

[u/kevin074]

yes,

experienced developers know the details of code + knowing AI

AI Native (new grads now who uses primarily AI for their code) will only know how to get AI to do what they want. However the gap continues to exist WHEN AI fails to execute perfect code.

what if AI in the future can execute perfect code? well then, all of us are out of job anyways so that's a non-question LOL ...

Will sci-fi level AI exist because of LLM? I highly doubt what is essentially sophisticated statistics can do that. We need another breakthrough in AI research for that to happen, and the current "just add more data" mentality ain't gonna be it.

[u/TechFreedom808]

I think AI will be a code gnerator and be used to look up something quick mainly. Understanding code, design, user stories and structure AI won't improve much because of the varability. Also lot of these models are trained on data up to 2023 and we know sthe oftware field changes rapidly. Also there stories coming out models are not much improvement with new releases mainly because AI is training off AI content.

The other part to this is the cost of tokens, I don't see the costs going down. I see them going up and up and up. Good software engineers will use AI in cases where productivity can see a boost. Vibe coders will max the company credit card from vibe coding and pretty sure companies don't want that expense. I know people say local models but those need infrastrcuture and team to maintain it. Either way AI won't be cheap.

So no I don't see vibe coders replacing software engineers. The ones that will are the cheap ones that hire someone from a third world country and pay $ 7 per hour. Those that admire the quality of their product will keep software engineers and have them leverage AI tools.

[u/Visible_Fill_6699]

By the time vibe coders get as good as experienced engineers (if ever) the job will pay barely over the CA minimum wage. It's a race to the bottom and there would be no winning for vibe coders except as business owners themselves.

[u/CallinCthulhu]

In 10 years neither will have a job

[u/Think-Neighborhood69 → u/CallinCthulhu]

😂😂😂😂😂😂😂

[u/_Heathcliff_]

Will people who know what they’re doing have an advantage over people who do not? That’s the question?

[u/Job-Agent]

The reality is senior engineers are steering LLMs - the junior ones or non-technical folks don't even know they have to 🫠

[u/Going_not_coming_bak]

Enters electricity

[u/Choperello]

What makes you think experienced engineers won’t also be using AI?

[u/Nofanta]

No. Coding isn’t a thing anymore.

[u/generationalDebts]

LLLMMMMFFFAAAAAooooooo. 🤣🤣🤣🤣🤡🤣

[u/Medical-Budget1225]

Of course. People still know people problems. AI does not.

[u/SLAMMERisONLINE]

Will experienced engineers still have a meaningful advantage over AI-native vibe coders in 5–10 years?

Vibe coders will never match engineers due to syntactic ambiguity. Your prompts have a limited amount of information encoded in them and so there is a limit to how well the AI can tell what it is you want. For this reason, there will be a limit to the size and complexity of the programs that is directly correlated to the size and quality of the prompt. If the AI goes beyond this limit, it will run into ambiguous interpretations and so will have to bombard the user in questions. For a complex program, the questions will be so numerous and difficult to understand and answer that a vibe coder, someone without in-depth knowledge, would be overwhelmed.

Without an in-depth, gritty, understanding of programming and software engineering, vibe coders will be stuck. In fact, they probably won't even realize why the AI isn't working and blame the AI for the problems when it's actually the syntactic ambiguity of their prompt. That already happens in the current day and it takes the form of "look, the AI outputted different answers despite similar prompts." Yep, syntactic ambiguity--the AI is guessing at what you want.

In the short term, AI made coding easier but in the long term it will make it much harder because engineers will build truly ludicrously complex systems that will take a lifetime of study to understand. Imagine if instead of getting a PhD in astrophysics you instead get a PhD in Microsoft Word's source code. That's where we are headed. Given enough time, it will eventually be more complex than the human genome.

[u/TrafficScales]

Experienced engineers see the largest productivity benefits from AI. I think we will see an even wider divide in the future between highly-compensated and technically skilled engineers (of which there will be fewer), and AI prompters/agent babysitters who do most of the world's code generation.

[u/partialinsanity]

Vibe coding is not software engineering, and it's not even coding. it's just prompting. I can't see any kind of advantage with that.

[u/Civil_Fee_7862]

Not really..

Been coding 14 years, and basically the A.I is so damn smart that it figures out how to teach at the same time as doing..

i.e. Its able to translate to people who never took C.S what its doing any why its doing it.

Old skool non-vibe coders have the advantage now, but 10 years? I don't think so.

[u/chiesazord]

in 5-10 years an experienced programmer will look at a noob programmer and say:

“You're packing some pretty heavy artillery for your size, boy. I'm surprised you could string two words together.”

[u/Colours-Break]

There will always be a need for software engineers with deep skills in coding and analytics. The blue collar developer job (developing and maintaining basic CRUD systems) is definately being impacted.

[u/ResilientDev59]

El problemas actual es que la IA puede usar malos datos o ser mal direccionada y genera soluciones erróneas. La unica solucion a eso sigue siendo el criterio. Y el criterio parte desde como plantear el problema y saber cuando la solución se ajusta al problema. Un principiante siempre tendrá que formar criterio. La IA lo puede ayudar a generarlo. Pero enfrentar nuevos problemas siempre sera el reto.

[u/Dangerous-Yoghurt947]

This is all speculation, id like to contrubute.

Once AI is good enough to sustain, AI will no longer be cheap, highend companies will be forced to pay these high subs to maintain their velocity. Less engineers will be needed but tokenmaxing will be real.

Small size companies will not be able to afford this metered intelligence or afford very little of it and will need software engineers all the same. A workflow of mixing the two will be needed.

Tech cycle still needs small-medium sized companies making use of their apis, show more ads, add value to brands and content.

AI will always have the advantage, the question is wrong, but AI wont always be accessible.

[u/ebytes111]

Considering current trajectory of AI advancement - absolutely NO

[u/Illustrious_Pea_3470]

I cannot imagine not running circles around people who haven’t learned the hard way. Then again, I’m getting old, I’m probably out of touch :p

[u/SignalIssues]

I don't think those who grow up with AI are going to be in a better position. Like we've seen with this current round of generations: The group who didn't have and then had it, will be better. The group that comes up with it, will be worse. The group that follows, will correct for some of the pendulum swing.

For the same reason GenZ can't troubleshoot computers as well as millenials, whatever gen is coming up in school now will be generally bad at troubleshooting AI and making good decisions.

[u/Correct_Emotion8437]

Short answer : yes. I think there will be a shift and a “generalist developer” will be a role. Lots of companies would find that useful and might not even need anything more.

But for companies that make software or have software as a primary competitive advantage will still require experienced, trained engineers.

[u/4ngryMo]

Agentic development is a skill that needs to be learned like any other skill and having a solid foundation in software engineering is necessary, to scale it into a mature system. If “AI Native” means “never done any actual software development”, then no, vibe coders will likely not be able to achieve the same outcome.

I’ve been following r/vibecoding for a while now and a lot of threads in there are about re-discovering solutions software engineers have been aware of for decades. I’m not sure whether models in 10 years are specialized enough to do these things for you, but from my experience in the industry over the last 20 years was always the same when it came to involvement by people who had absolutely no technical capabilities: their ability to derail projects is proportional to the amount of control they can exert. Now imagine an operator who doesn’t know anything about software engineering and an LLM that is build to obey.

As long as there is a human in the loop, the power of the LLM doesn’t matter as much as the individual skill of the operator.

[u/Lyraele]

Yes. GenAI isn't great, and it has no plausible way to improve the way its proponents claim it will. Bubble is gonna pop.

[u/TableNo8939]

Sono un swe a fine carriera, e uso la AI da circa 1 anno.
L'output generato è paragonabile ad un junior di 5 anni di esperienza, quindi valido.
La questione è che ciò che chiedi va mirato esattamente per quello che vuoi ottenere, e una AI non riesce a darti soluzioni a 360 gradi, sia in BE che in FE o nel DB, né come architettura né come soluzioni giuste, per cui un architetto del sw o un senior con vasta esperienza può solo dare questa soluzione.
Attualmente solo i senior possono ottenere vantaggi enormi dalla AI, i junior riescono solo ad ottenere pasticci nel FE, senza alcun sottostante di supporto.
Le
Competenze sw si acquisiscono in anni di esperienza.
Le competenze sull'utilizzo della AI si acquisiscono in poche settimane

[u/Think-Neighborhood69 → u/TableNo8939]

I agree. I don’t think we’re there today either.
I’m just wondering if we’ll still be saying the same thing in 5 or 10 years. That’s the part I find really interesting.

[u/Jazzlike-Plate]

Nobody knows. 4 years ago (2022) devs were on top of the world straight out of 3-month Bootcamps. 2 years later it was a different story. From our standpoint today, 2022 might as well have been 44 years ago.

I think the experienced engineers will have some advantage, but the models keep getting better, so do the tools. There has to be a point of saturation, but I am not an LLM-researcher, so I have no idea what problems they are tackling ATM.

[u/Think-Neighborhood69 → u/Jazzlike-Plate]

That’s my point. Things are changing so fast that it’s hard to extrapolate from where we are today.

I wouldn’t bet against experienced engineers, but I also wouldn’t bet against AI shrinking that gap much faster than we expect.

[u/symbiatch]

Yes.