Build full “product skills” and you'll probably be fine

It might sound really crazy and stupid today, but when SQL came out, it's advertised as one of "program-generating" languages and was supposed to reduce the need to code.

https://en.wikipedia.org/wiki/Fourth-generation_programming_...

(I mean, in some sense it's true because it's much less code than writing our own database...)

And even if AI is able to do that... Well, then anyone out there could become a UberCycle CEO. Which means: customer requirements will be much more complex by then and coming up with an entire product in 1h won't be enough anymore.

Why not let the people on the floor complain to a AI manager, the people on the floor know exactly what is killing their productivity. Like "yo ai manager, manually filling in those data field is taking quiet some time to check someones credit score is it possible the IT department can automate that process it might save 2 min a form" then AI manager can prioritise stuff like this.

I always found that overwhelming majority of professional academic educators are particularly bad in anything that has to do with the practical side of their domain. That is especially true for software engineering.

University lecturers are very detached from our field and it shows in how badly fresh grads are prepared to do any dev work. For that reason I almost always ignore their projections.

I feel like there's currently a movement towards slightly lower abstraction, or at least simplified, consistent APIs, less magic. The rise of Go and Rust are examples of this. Typescript could be another, although the abstraction isn't really lower, it is once again an attempt to coerce JS into something workable. I get really frustrated writing Python or Rails these days due to the sheer magnitude of hidden magic that sometimes works and sometimes doesn't.

To tie this thought in with generative AIs: Currently they seem to be much better at programming with relatively simple syntax. By far the largest success so far I had with shell. Basically I tested assisted writing the same tool in Python, Perl and shell, and the results in shell were close to perfect. ChatGPT was even able to accurately limit commands to specific OSs and shells, and was able to accurately summarize the functions of other shell scripts.

So my prediction is that we will see a movement towards simpler, lower abstraction languages while Coding Assistants rise to take away the boring stuff from programming like looking up syntax, writing boilerplate, structuring files. Programmers will then have more time to think about delivering value to product, maintainability, and efficiency and correctness.

One last addendum: ChatGPT is really incredible at assisting with sys admin stuff, my guess for why would be that there are a gazillion obscure forum entries going back to the 80s explaining basically everything there is to know, but these are hard to find or comprehend for humans. With an AI assistant, self-hosting becomes much easier, and another development could be for startups and smaller companies to move away from AWS et al, especially now that money is more expensive.

The model I have is closer to “how many people can program using Excel vs how many can program in a ‘traditional ‘ language?” The difficulty in specifying exactly what you want is still there in Excel, but there’s far more people who can get started and they can make changes when they see it’s not doing what they want.

It doesn’t have to one shot “hey, implement these 59 Jira tickets for me” to be disruptive (in a good way). It’s extremely rare for something to get much cheaper and for there to be less demand for it. If you’re the top half of a field that’s in a lot of (and growing) demand, I think you’ll do fine.

Are we sure that an AI could not engage in enough back and forth conversation to firm up the spec? You’re kind of assuming that systems will be generated from a one-shot prompt, but it seems more likely that an interactive AI will identify the gaps in requirements and ask for clarification.

Alternatively, if the prompt-generate-evaluate loop is short enough the user can simply play with the running system and provide feedback to alter it.

This is essentially what developers do when they present a “weekly build” or whatever in an agile environment.

The process of solidifying requirements, stating them clearly and translating them into machine-executable formats are all language tasks and these models are really fucking good at those.

I’ve noticed in discussions like this that many software folks are assuming that AI capabilities will plateau soon, or will merely be extensions of what we already have (a better autocomplete, etc). I submit that we may reach a point where the AI is so compelling that we’ll reorganize teams/systems/businesses around it.

Here's my concern:

1. AI assistance thrive on structured data

2. Computer programs are some of the most structured data. And it's available abundantly out in the open.

3. Yes, you can't generate an Uber for bycycles with a single prompt, but you can fire half your development team and increase the productivity of the rest of your dev team with an OpenAI subscription.

Managers exist mostly cause ppl are not machines. Given enough time they want to go off and do things that have nothing to do with what everyone else wants. Its the same reason you still need a farmer to run the dairy even though everything is mechanized cause cow cant run things.

Ppl are too full of shit. The attention economy amplifies this poor to mediocre mental masturbation thats going on everywhere. And Americans have a track record of too much mentally masturbation too much way above their pay grade. Its like watching Alex Jones falling into the trap of taking what comes out of his 3 inch chimp brain too seriously. The only right thing to do is tell Alex to chill the fuck down and go milk the cows.

For the tinkerer, no-code tools are (probably) great, but if successful, even tinkerers will hire managers who will hire translators.

https://en.wikipedia.org/wiki/The_Last_One_%28software%29

> The Last One is a computer program released in 1981 by the British company D.J. "AI" Systems.[1][2][3][4][5][6][7][8][9] Now obsolete, it took input from a user and generated an executable program in the BASIC computer language.

It was THE LAST ONE because it was the last program you'd need to buy. FOR-EV-ER. While its baseball-eating ability was unknown, it was "all the programs you'd ever need for £260" and it apparently focused on ETL jobs; that is, extracting data from files, transforming it, and loading it into some other file. Talend for the Doctor Who set, in other words, and it was set to EX-TER-MI-NATE programmers. Maybe it did; after all, we don't very well write programmes, now, do we?

https://modeling-languages.com/last-one-code-generator-basic...

https://archive.org/details/PersonalComputerWorld1981-02

It certainly got a lot of hype at the time but, like all Coming Things, it's hard to tell where it Went.

By all means, that is part of everyone's job. Sometimes I really can't remember how to do some specific thing. I know precisely what I want, but I don't remember the proper way to do it. I would have resorted to a web search until last year, now I ask chatGPT. It is faster, more concise, and surprisingly accurate. And when it's inaccurate it's easy to either refine my question or cross reference what it generated with online sources.

But I think it's a bit silly how people are treating it as if it was some kind of General AI. It is not, it can only give out known answers to known problems based on language statistics. As impressive as it is, it can't reason logically about problems without known solutions, it can't identify faulty, incomplete or inaccurate information, it can't evaluate on drawbacks and tradeoffs of different approaches.

ChatGPT made like 20% of my work a lot faster and less cumbersome. I like it enough that I pay for premium access. But even the notion that prompt engineers might replace software engineers is silly. I imagine people repeating this nonsense are either not engineers, or extremely junior in the profession to the point where their work is only writing code for clear specifications, no questions asked.

- gpt doesn't need you to be exact

- one day gpt will be able to ASK YOU question to refine what you need

It may take years, but at some point, it will be able to do 80% of my job.

Not a big deal though, cause people will still hire me to do the remaining 20%, and pay me even more money because not a lot of devs will be able to do it.

Sure one class of job has taken a huge hit (sys admins, supposedly ops), but it's been replaced by another that needs intimate knowledge of the tooling required to do what was being done previously (just in a more "scalable" way). DevOps have been demanding a premium for years now.

And there are still sys admins out there doing what they've always done..

The equivalent assumption would be that ChatGPT and MidJourney can't work because you have to specify every paragraph and every shape.

Clearly that's not true. Just because every object and every texture had to be defined rigidly by hand in 3ds Max or Blender by highly skilled designers doesn't mean that's how it works today.

In fact AI is the stage of software where abstraction itself is automated. The current Gen 1 AI tools do a little of this, but as Gen 1 they're just getting started.

They're going to be in a very different place ten years from now. And so are we.

But aren't managers there to coordinate software engineers. So if software engineers are out of a job, so will the managers. Assuming AI replaces software engineering, the ones left may be the product people and the founders, perhaps rolled into one person in several cases?

Which aligns somewhat with what Carmack is suggesting.

> Instead he made this prediction because he saw the rise of no-code tools replacing software developers

I think that people who make these predictions are not very good at actual programming (taken in the more wider meaning)

The latest fad I remember (before ChatGPT) was that with BDD testing non-technical people would be able to write tests and we all see where that went

But most fundamentally, the non-technical people don't have the time nor the expertise to learn all the details needed for shipping software (and why would they? their job is to look at other aspects of the business)

That might actually be what development is, teasing out the requirements by iterative entering them into a machine that does exactly what you told it to, and comparing the outputs to expectations.

This. I started programming in Machine Code, where the "editor" was a pad of graph paper.

I've watched management- and business-focused people sneer at us geeks for my entire career, and watched them drool over the thought of finally getting rid of us.

Hasn't happened yet.

> I'd be surprised if the next step is "Hi, I'm an ideas guy, please give me an app that does Uber, for bicycles, but better."

I get that, from "idea people," on a regular basis. They have nothing but contempt for us "Make It Happen" folks. They treat us as if we grow on trees, and are suckers, to boot.

Inevitably, the above, is followed by something that translates to "Of course, you will do all the work, but I'll get all the money, because the idea is what's really valuable."

If I follow up on it at all, I'll be asked to sign an NDA, and meet in some clandestine place, so they can whisper to me about their AI-powered cheese straightener.

The best thing I find as a developer that it unblocks the resistance we have in starting up with something new. For instance, I just built my first Chrome extension [0] to make video players more accessible on webpages with keyboard shortcuts.

I had built a desktop app on similar lines long ago, but could never push myself to built an extension. Last night I gave my requirements to GPT and it guided me through the whole process – from creating manifests and js files needed, to the JS code (granted that I'd to fix/extend the code) and even how to install/enable the extension.

Within few hours I have my working extension without needing to go and read any extension docs.

0: https://github.com/varunkho/RamaPlayer/tree/master/Chrome

Doomsday prophecies are not limited to religious cults, you see them all around. It’s safe to say, from experience, AI is not going to outdated programmers but it’s going to make the mythical 10x engineer a common reality.

Some people can take a business goal and figure out how to turn it into a clear spec.

Sometimes these people are programmers.

However I know programmers who suck at this and I know non-programmers who don't.

The same thing applies to trying to get business people to write "executable specifications" that can be used, if not to generate the code, to at least validate that the final system does what it's supposed to.

They always complain that the "tools are too hard" but the real problem isn't the tools but that they are unable / unwilling to precisely specify what the system should do. They just want to hand wave vague phrases and have their system magically perfectly defined. It's just not going to happen.

On an aside, this is the kind of bussiness idea a chatbot could generate now.

But I don't think it could have generated the idea for Uber when Uber* was the first...

* if you know the history of ride apps better, replace Uber with whoever was indeed first.

How does this manager-engineer look like now? Managers specify what they need in plain language, and both parties go back and forth with increasing complexity to create based on the shared vision. Managers can already pull off a similar dance with ChatGPT: give it a plain English prompt, it’s responds with what it thinks you want, and you refine until it’s got it. GPT4 can do this with website sketches, and who knows how much finer you could get from there by specifying your prompts and feedback more tightly over less than an hour. Remember: copywriters and brand marketers and marketing creative makers have a similar role of turning complex requirements into designs that sell (and their roles are dying fast).

A software engineers job is to realize products into software. ChatGPT is pretty much as capable as a high school programmer that moves really quickly and takes feedback to heart - and that can handle a good chunk of the software engineering job for a huge fraction of the price. Your job isn’t as bulletproof as you think, and especially not your amazing salary. I’m speaking as a software engineer turned vc backed founder, so I’ve seen both sides of this relationship.

    Educators, generals, dieticians, 
    psychologists, and parents program. Armies, 
    students, and some societies are programmed.

Managers, CEOs, Department Heads...are already 'programming'. As the abstraction moves higher up, some people that have excessively narrow expertise will be made redundant.

You can't do that today because fixing the specification after the fact means waiting 6 months and paying 60+ man-months. Once fixing the specification means waiting 10 minutes and paying $10 for inference compute, the idea guys can afford to learn by doing.

That said "software is a tool" is a good frame of mind. You shouldn't position yourself as a 'coder' (those are hired en masse from poor countries) but a problem solver who uses tech.

"Ideas guys" and "coders" being seperate only exist, imo, when development is viewed through the junior lens - once you progress you'll end up wearing all the hats from ideation to QA at different points.

Do I program when I retouch photos in Photoshop? It's a no-code environment that an artist can easily learn and use with no programmers needed.

What's new here is that you DO NOT NEED TO BE EXACT with AI. AI knows human nature and human speech and it can infer what you say and what you need, if you're approximately close, and then make the exact code to do what you need.

Even if you need programmers, you now need 1/100 of the programmers you needed before. What happens to the other 99?

Does it matter whether programmers are 99% unemployed or 100%? Same deal.

You may have seen that there's now a load of drones flying around, doing things that were never possible until now. Dropping bombs on soldiers in trenches, giving support for assaults, targeting artillery.

The fact is war changes with technology. Spearmen and cavalry are obsolete now. Maybe pilots will be soon as well.

But the generals are not. There's always a need for someone to say "given the position we're in, and the logistics we have, and the resources we have, and what we know about the enemy, we should do this..." and this role is still recognizable through history.

Whether computer jobs become obsolete depends on whether you're closer to the general end or the footsoldier end.

I think it’s more probable that managers get replaced by AI first.

While absolute rigor in programming is a hard thing to find in reality, I don't think people understand the difference at all.

Won't that create stronger competition for fewer roles?

This means that an AI capable of completely replacing programmers is by definition an artificial general intelligence. I don't think we're at that point and I don't think we will be for a long time, but if we were there would be no point in worrying about our own joblessness. AGI would spell the end of the economy as we know it today, and it would be very hard to predict and prepare for what comes next.

However, as Carmack says, many developers lack product skills, it’s not just the managerial class that lacks them.

So I think the correct advice is not “engineers don’t need to worry at all”, it’s “make sure you are learning how to build a product not just write code”. For many that’s trivial advice, but not for all.

We have systems, today, that take a specification and generate code from it (and will even do so in a provably correct manner). There are scalability issues with such systems, but they exist and have in some form for decades.

None of these systems have taken the world by storm.

If what ChatGPT and their ilk do is make it easier to spew out bulk spaghetti code that is essentially unverifiable, I don't think that's going to transform the industry nearly as much as anyone thinks it will. For boilerplate code, sure—but that's exactly where we should be using better abstractions anyway. For small code which you can verify by hand, sure. But for anything larger than that, we're just watching a trainwreck in slow motion.

Large code bases written by humans are already hard enough to understand. How much more difficult will it be when your AI can spit out a million lines of code in a second?

Without specifications, it's all worthless. But the specifications are the hard part.

Think about the difference between Assembly and Python. Programming will continue to get higher level. Perhaps it won’t be so foolish to ask a truck driver to “learn to code.”

But here is an even more interesting comparison: the salary of someone writing assembly 30 years ago and someone writing Python today. Higher level != paid worse.

One day a corporate genie appeared to a middle manager and granted him one wish. The manager wished that their business logic could be edited by a graphical tool and that programmers were no longer needed. "Granted", poof!

The next day the manager came to work, all the programmers were gone, fired by upper management. The manager sat down and opened the new graphical tool that had magically appeared on his computer. The interface was beautiful, except for what appeared to be a hairball drawn in the middle of the screen. The manager asked his manager about the hairball, "oh, that's our business logic, you have to zoom in to see the individual rules". The manager zoomed in and surveyed 180,000 business rules, intertwined in a complete graph.

"How am I suppose to work with this?" the manager asked his manager. "You just click and move them around, it's easy", replied the upper manager. "Also, I've been meaning to ask, when do you think those new business rules we talked about last week will be implemented? We need them by Friday."

To reach the point where no-code is a no-brainer further implies inflexibility in the capabilities of applications and moreover, fungibility in their fundamental uses. The question to ask is are the upper layers of abstraction reducible to what's analogous to the outputs of a parse tree.

If we reach this point where creativity and actual innovation is lost and we're all simply attempting to make the next 'facebook for dogs', I anticipate my future personal career switch to starring in geriatric pornographic films.

Given the way we had tremendously productive tools like Visual Basic 6 and Delphi, that seemed to be a reasonable interpretation.

But those tools gave way to C++ and all the .NET insanity. I don't know why someone would give up Delphi, which worked flawlessly and didn't generate any (as far as I can recall) re-only generated boilerplate, to C++ which was a mess, but it happened en masse.

Then most people abandoned personal computing, and the windows desktop for always internet connected pads and phones. Tools have gone severely downward in the past 2 decades as a result.

I suspect we'll get some really powerful AI tools, and go back to worrying about null pointers in a few years anyway.

What’s great is that you could also have AIs write tests - for performance or correctness. Then future prompts could rely on these tests to stay in the correctness bounds for existing projects.

Emulating cognition is almost limitless in what it can do once it gets sufficiently good. So good that it can operate itself. You could hire an AI founder and give them cognition and compute resources to solve any problem.

Here’s an example:

You: Build me a profitable company that uses AI generated content to entertain humans.

AI: How much can I spend on cognition and compute? How much time do I have?

You: I want you to spend at most $X before coming back to me. You have until Monday. Along the way I want to see your plan before we decide to execute. Spend at most 5% of that making the plan and 1% calculating its probability of success with confidence interval.

… within some small timescale

AI: Here’s my plan as a video with rough examples demonstrating the product and strategy. Here’s a table with our probability distribution of predicted success metrics and confidence intervals.

You: Plan approved you can spend the rest of the $X

… on Monday

AI: Done. We’ve made a profit of $Y, with total revenue so far of $Z. We have a plan for reinvesting these proceeds to make even greater future profit. Here’s a table of our expected success metrics based on reinvested amount. How much should we reinvest?

You: Reinvest 50% into perpetuity and deposit the remainder in my account. Book me a trip around the world using 25% of the current deposits with accommodations for my family.

Now go enjoy your life.

The fallacy here is that programming is not a process of translation. It is a process of invention. Going from rough or high-level functional requirements to a functioning computer program requires inventing novel logic that has not been invented at any other step. It involves making business decisions that have not been made at any prior step.

Whatever can be categorized as menial "translation", i.e. a step in the business process where no new logic is added or business decision made, has already been automated away - compilers.

Nevertheless, AI is different. Because now you don't have to specify things at a programming-language level of granularity. It will select the programming language constructs most statistically likely to match a solution to the specified problem.

So now we're in a whole 'nother world where the programming, as such, will be done by machine while the role of designer or architect must still be done by humans. But the legions of programmers employed by companies are about to go the way of farriers.

> In essence what has happened in software development is that the level of abstraction has gone up while the machine has taken over more and more of the nitty gritty details. From punchcards, to assembly, to COBOL, C, Perl, Java, Python, Erlang, Rust.

I've had friends and peers contact me in regards to the AI, GPT, et al headlines and they're always surprised at my calmness. You've written out exactly what is happening and why there shouldn't be any worry regarding jobs. I think the worry is generally under the premise that everyone has to upskill themselves which is against human nature. Folks are feeling uncomfortable but this is another cycle.

> But the rigidity of what is needed to specify a program that really does what you want hasn't. Especially evidenced by the fact that recent programming language developments often have a specific area where they shine, but not raising the abstraction level that much.

Another great point. Like you wrote, there really is a need for "translators" for programming languages and it's not going away anytime soon. If anyone has played around or even just read/watch through folks using AI/GPT/Etc. you'll come to notice that the tech is not "stable". It's only good in limited instances.

Finally, the headlines and copywriting of most of the pieces and journalism coming out is definitely hit and miss. A mix of pessimism and optimism. It's important to remember what we are witnessing is another technological cycle and another cycle in general if you want to looking at a bigger scale but that's another discussion for another time.

I believe the world is wiggly, not geometrically perfect, intellectuals struggle with that because square problems are easier to solve. Ideal scenarios are predictable and it’s what we like to think about.

Have you ever had to use a sleep() intentionally just to get something shipped ? That’s a wiggle.

We’re going to try square out the world so we can use ChatGPT to solve wiggly problems. It’s going to be interesting.

Yesterday I tried to use a SaaS product and due to some obscurity my account has issues and the API wouldn’t work, they have a well specified API but it still didn’t work out, I’ve been working with the support team to resolve it, but this is what I call a wiggle, they seem to exist everywhere.

Ask a construction worker about them.

But it's definitely not true of the average piece of software. So much of the world around us runs on software and hardware that somebody had to build. From your computer itself, to most software that people use on a day-to-day basis to do their jobs, to the cars we drive, to the control software on the elevators we ride, software is everywhere.

There is a lot of waste in software, to be sure, but I really don't think the average SE works for a company that shouldn't exist.

Everyone thinks only in terms of current needs and state of affairs of people when analyzing a future technology. No one thinks about the insatiable human desire for more and the higher expectations for that new normal that always meets the increased productivity available. Anything that automatically solves much of our wants is doomed to be static and limited.

It's not wrong, but it's also not applicable to all people who enjoy performing an instrument.

The advice here is clearly meant for someone who wants to invest in themselves to provide food and shelter for themselves and/or a family in the future. (Ie “doing all this hard work for nothing… AI will make my future job obsolete”).

The advice is spot on. Soft skills are hard to learn, harder to teach, and allow for flexibility with regards to the tool used.

> anyway something about it bugs me and I don't think I'd follow it exclusively even if I was starting today.

I’d be you like the money but don’t seem to want it as much as you want to solve deterministic puzzles (“not interested in becoming a manager” ie “not interested in maximizing career/salary growth potential).

What bugs you seems to be that you can’t yet see the puzzle left for you to work on once GPT-12 makes coding obsolete and software architecturing obsolete.

A long time ago I got some good feedback, “You were hired because you typically know the right answers and/or know how to find them. You were promoted because you also seem to know how to ask the right questions, and that is significantly harder.”

I’m relatively certain it’s analogous to Carmak’s advice.

This is not going away with the AI in the picture.

It will be just different.

I'd unfortunately tried to make that mismatch work for too long, and as a result I completely destroyed all of my programming interest via severe burnout.

If this resonates with whoever reads this: please take your passion seriously and protect it. I don't know if I'll ever be able to enjoy coding again, unfortunately.

Most didn't.

Programming in the traditional sense will be obsolete and people programming for the fun of it will be a niche thing.

But if you know who he is and what he does these days, it makes sense I suppose. Can't be in that business environment day after day without going slightly nuts eventually.

Bad developers on the way of becoming obsolete by AI will see drastic improvements from the thing that’s about to replace them. Otherwise it’s slightly better intellisence integrated in your editor.

The difference is that bad developers are primarily concerned with literacy and their primary intent is chasing easy. Better developers are comfortable reading code no differently than an attorney reading a large contact and their primary intent is chasing better automation. It’s the difference between designing a car engine versus hammering pieces together.

I suspect this will open wage distinctions. Those who can write software will be identified from those who can’t. Those who can will be fewer in number and their wages will increase. Those who can’t will be a lower skilled commodity with depreciated wages, like the way data entry was once a skilled profession many decades ago but no longer.

Hardly. 10% of the time spent is in writing code and the other 90% goes behind debugging and fixing things.

Even if AI shrinks the time spent in that 10% in writing by another 90%, you still have have to take full time for maintaining that code. Changing, debugging, testing, deploying, profiling, log analysis.

Worse, its now someone else's code you need to understand and debug, and not the one written by yourself.

1) Wages have very little to do with value/productivity in a free market. They are almost entirely determined by supply and demand. Value simply places a ceiling on compensation. Thus, if far more people can perform a "programming" job because of GPT-X, unless the demand for those jobs rises significantly the net result will be wage reduction.

2) There's this weird thinking on HN that since a developer's job involves [insert your % estimate of time spent actually coding/bug fixing] and the rest is figuring out requirements, dealing with weird requests, planning, etc. that means developers can't be replaced. However, I don't see a whole lot of discussion around what the difference is between a developer and a competent business analyst in a GPT-X world. The latter can be had for significantly less money, requires less training, and if the actual programming part is largely automated away or concentrated in the hands of fewer "real" developers, those roles start to look awfully similar.

I wish! I still often find out my team members don’t know basic text/Unix tools. Heck one guy took our list of enums in a JSON file and wrote on his keyboard by hand each of them into a class. It took me maybe a minute in Sublime Text when he wasted at least a day

Except population exploded also, and the only reason we could support such a population has been thanks to advances in agriculture (it could be argued that's not a good thing, as the larger population is helping fuck our planet up in other ways, but that's for a different thread). So there has been an increased demand for food.

However, there's only so much arable land on this planet. The planet is finite in size. So when basically the entire planet is already being farmed, you can't really add more farmers, so further efficiency is just leading to less farmers.

Software is not so finite. It technically is, as we only have so many servers or whatever, but we're nowhere near the upper limits of what all we can handle or the appetite for software that companies have (which seems about infinite). Additionally, we have a habit of rebuilding and replacing software every few years, so even if we reach capacity limits, there's still demand for new software to replace the old, or working on new features for existing software.

So it's a bit different of a situation and not really comparable.

And how, exactly, is this going to work?

Is every IDE going to pay some license fee to OpenAI? Will that be up to the companies or—even worse—individuals who use the IDEs?

What happens when OpenAI decides that GPT-4 is passé and it's time to move on to something else? Will the existing IDEs that are designed to interact with GPT-4 stop working?

Will GPT-5 or whatever provide the same kinds of assistance, or will there be regressions? Will they require a completely different license for it?

See, these are some of the important questions that come with assuming that a fairly new for-profit company will act as the backbone for your marvelous programming renaissance—particularly when the service in question is one that takes quite a lot of resources to continue to operate.

Personally, I would be interested in some kind of LLM-assisted IDE, but no way in hell am I going to make any significant portion of my job dependent on an organization that decided, as soon as it was clear there was real interest in what they were doing, that they'd just toss the "Open" part of their name and principles out the window and just go for closed-source proprietary product and maximum hype for more profit.

As long as people are in charge, we'll have plenty willing to pay technical workers who see themselves as artists.

They will naturally fall behind their colleagues.

In my experience - I ignore the modern IDEs and systems purely because I don't have time to learn every new tool... :-D

Citation needed. Numerous actual citations have demonstrated hallmarks of intelligence for years. Tool use. Comprehension and generalization of grammars. World modeling with spatial reasoning through language. Many of these are readily testable in GPT. Many people have… and I dare say that LLMs reading comprehension, problem solving and reasoning skills do surpass that of many actual humans.

> They model intelligent behavior

It is not at all clear that modeling intelligent behavior is any different from intelligence. This is an open question. If you have an insight there I would love to read it.

> They don't know or care what language is: they learn whatever patterns are present in text, language or not.

This is identical to how children learn language prior to schooling. They listen and form connections based on the cooccurrence of words. They’re brains are working overtime to predict what sounds follow next. Before anyone says “not from text!” please don’t forget people who can’t see or hear. Before anyone says, “not only from language!” multimodal LLMs are here now too!

I’m not saying they’re perfect or even possess the same type of intelligence. Obviously the mechanisms are different. However far too many people in this debate are either unaware of their capabilities or hold on too strongly to human exceptionalism.

> There is this religious cult surrounding LLMs that bases all of its expectations of what an LLM can become on a personification of the LLM.

Anthropomorphizing LLMs is indeed an issue but is separate from a debate on their intelligence. I would argue there’s a very different religious cult very vocally proclaiming “that’s not really intelligence!” as these models sprint past goal posts.

The hype, more appropriately the cult following claims it will replace jobs and analogous to, second coming of Christ in the aspect of change the world. What it appears to me is there is massive money to be made. It as if, because how strong the hype is, it will drive future VC back startups to be make the next billions. My suggestion to you is, if you are in to make money, you will need to put the common sense part away and join the bandwagon.

I have same sentiment as you regarding LLM, but the biggest issue is that this sentiment will not make money. To make most of what is going on, is to fake the belief that this model will have a great affect on humanity and software solution that makes use of LLM needs funding till an IPO.

I'm sorry, but the landscape in then might be as alien to someone asking today, as todays would have been to someone asking 15 years ago (2008).

What John said is correct, but personally I think he's underplaying how much people could be affected. Those "product skills" take years of grinding to really sharpen, and in 15 years only a few people might actually be needed to apply them

If programmers can be replaced by AI, so can it replace even the blue collar jobs. Because if it can’t that is what this developer here will be working on.

(Submitted title was "John Carmack: From a DM, just in case anyone else needs to hear this". A mod changed it to "I’m concerned AI will make CS jobs obsolete" but yeah, that changed the meaning. Sorry!)

But talking to my friends who do these jobs it always seems like it would be even more vulnerable to AI than programming.

Experienced electricians get paid decent wages because they have had lots of training and then have seen loads of different problems. So they intuitively know things like 'This is a 1960s house so if there's a problem with the lighting the first thing I should check is the fuse box connector, it should look like xyz, etc. Etc.'. This seems like exactly the sort of thing an LLM could do for them.

I think you could easily see a world where an electrician is someone on minimum wage with very minimal training who blindly connects wires as instructed by an AI.

I reckon the safest jobs are ones with limited reliance on knowledge and a very high level of physical skill (in environments where it's hard to get machines to operate). Bricklayers, plasterers and painter/decorators will be the big earners of the 2050s!

I see this argument way too often. How many electricians and plumbers does the world really need? And if the market becomes over saturated, how much will those jobs pay? How often will you actually have a job to do?

(“Force me to write code” suggests that we’re looking to think deeply about what we’re doing and trying to minimize unnecessary action, so the rote actions are bad.)

Lots of people learned how to make games for NES, SNES, PS2, PS3, etc.

All those machines are now obsolete.

Current gen consoles are using x86 and ARM now and most upcoming AAA games are built on Unreal Engine. The competitive advantage of those who mastered coding for the Cell processor is gone.

What should SONY have done instead? Should they still use the PS3 architecture in the current gen consoles to keep those developers employed?

That really depends on the type of "Software Engineering" you're doing. In my experience, in greenfield projects, boring CRUD-type programming can easily take up 50% of your time.

It'd be great if AI could automate this boring CRUD-type programming away, and let me focus on the architecture and interesting algorithms.

It seems similar. New heights are possible for those with skills, and the barriers are lowered for those without training. There will be new demand for both things, competition for quality at the top, and new applications where it wasn't worth it to produce art before at the bottom.

Both art and programming seem hard to predict what value you'll get out of investing in skills now, because there's both barriers being broken down and demand being opened up.

I do think there is a key difference, though, which is software hasn't shown signs that it's getting close to done "eating the world" yet, due to the universal nature of the turing machine. It's nothing to do with programmers being special and everything to do with computers being a single tool that's applicable to everything and has sustained decades of exponential gains in power.

I wouldn't stop someone from investing in art skills if that's their interest, and I wouldn't stop someone from investing in programming skills if that's their interest. But if they were interested in both equally, I would absolutely suggest programming.

No, the sense of unease comes from people fearing for their livelihood, given that it looks like that their raison d'être is about to be revoked by some AI automating their career away.

A point you so aptly summarized with: > Vast swathes of the human economy are just scaffolding to support the rest: humans reproducing to keep the optimization machine going.

The unease is, imo, only so palpable however, because every stakeholder that stands from profiting from such a development - i.e. capital owners - refuse to describe it as what the development really is.

Publicly advertising AI as "we're basicially moonshotting the largest job automation operation ever attempted, so 20-30% of you will be out of a job in the next 15 years" would probably cause unrest - and rightly so!

> What else can you do anyway?

Communism - and ya hate to see it (as an american)!

The means of production becoming dead-simple to use, that's a prelude for the proletariat being able to seize them.

On a more serious note, you can always protest, and escalate, which I'm hoping will happen.

> Professional developers will recognize that we're talking 50-90% of the LABOR-HOURS that go into software development,

I call it 'dumb coding'. You have a type of programming that requires you to really think, and then there's the type where you just need to write 200 lines of code but you know exactly what to write. If AI could pickup the slack on 'dumb coding' and let us think about 'smart coding', we would all be way way more efficent.

More like 20-30% at max. And it's not including debugging the output of chatGPT, which I've found that it has been making subtle mistakes - which will probably take away all of the time gained.

Writing code isn't the biggest time sink, figuring out what to write is.

Zero developers will lose their jobs due to LLMs. That’s just yet more needless hype and expectation.

That's definitely a possibility. The barrier to entry won't be just in terms of how much you need to know, though, but also the fact that society as a whole might not require that many top tier leetcoders.

Basic web dev has been commoditized for awhile, but a company of any size requires much more than basic web dev.

Humanity has an uncanny ability to devour any excess capacity, and I see no reason it won’t do the same with things AI makes easier/lower cost.

What I do worry about is that AI will put further pressure on the lower skilled jobs keeping many people afloat. Call centers for example, likely will not exist very soon.

I envy the speed with which a younger version of myself will be able to pick things up.

Companies are legal fictions, and have no motives because they don't actually exist, the people who control the resources of the company are the ones to worry about.

I find the idea of being an expert in a language acceptable if it's been used for long enough. Almost all of my coworkers only know .NET and there are enough jobs needing people for new projects and legacy projects that they most likely won't have to learn anything else.

> or tool y

This is where the absurdity begins for me. I have a coworker who is 5 years into his career with the title of "senior react engineer". He started as a "junior react engineer" and at this point only knows how to solve problems with React. He has limited knowledge of the underlying language or general CS concepts. Every problem he encounters can and will be solved by installing NPM packages.

I've came to the same conclusion:

I'm earning more than my friends, but

I've spend years doing it at work,

I've been learning it for years at college and

I've been doing it for years during my "free" time.

The $ per hour spent ratio doesn't seem to be very good.

When talking just about $/hour spent ratio then there are jobs which pay well and you can start earning decent faster.

Like well drilling, truck driving and I bet countless other

I don't blame them. I gave up on an awful lot of social skills so that I could escape the worst of capitalist exploitation. I pimp out my mind for my money. Others pimp out their bodies, or souls...

Now these things are practically given away for free to drive people towards websites where you can be sold software you won't ever own (SaaS/cloud) which was the next hype-train that was setup by a smnall group of people and that was used to accumulate wealth. But the end result was very modest or zero improvements in actual productivity.

Here we are on the next hype train. And I think you've very much spotted the pattern. What these things are good for is driving up demand for new products and services that have increasingly marginal, zero, or sometimes even negative effects on human wellbeing overall.

The immediate issues are: who decides the boundaries of (publicly) acceptable thought -and- who profits?

I think you touch on the deeper and even more challenging issue:

> I'm now trying to teach my son, an avid programmer, how to work with chatGPT. He's 13, so he's got a lot of opportunity to really integrate it into his career, but he also has a lot of blind spots where chatGPT can really lead him down some blind alleys and knife him.

When the talking computers can answer any (allowed) question, the educational challenge becomes building human minds that can recognize and select the right options from the unbounded "white hole" of content that the machines can produce.

Now, the word "right" in the previous sentence is doing a hellofa lot of work. Deciding the right course of action is an open-ended intelligence test. It's evolution, eh?

What will those people do, whose job will become obsolete? Are there support systems available to help people learn new valuable skills society needs?

If only a few people at the top will benefit from these tech advancements and the rest will have to fight for scraps then society will eventually fail or end up in a total tech feudalistic system.

Back in the 60s it was said that future advancements and automation will transform our society into a leisure and more innovative society.

Whatever happened to that vision?

Offtopic, but it's scary how HN actually becomes worse than Reddit on these ChatGPT posts.

When I was younger every programming job was supposedly about to be outsourced. I did exactly what Carmack suggested, and it worked out well for me. I think it’s a great general strategy for working for a long time, but not ideal for someone who wanted to pass leetcode style interviews at a top tech company.

For example, would anyone at my google tech interview care that I’m comfortable with a companies financials, managing P&Ls, margins, etc? No, just how fast I can write a sort or whatever.

The best new models are so powerful and general that you literally don't have to train them for any specific task. Just give them some context.

ChatGPT couldn't count. GPT-4 gets a high score on a math SAT.

You and your friends will be easily replaceable with AI. Quite possibly already with GPT-4. If not, certainly we should anticipate within 3 years.

If anything, I'd expect them to become more frenzied in their efforts.

As someone in this post has put it quite beautifully: > It's like telling a musician to become a DJ because the point of performing is to entertain people.

He already talked about this in his interview with Lex Fridman - https://www.youtube.com/watch?v=xzPuGf89vpI

His new startup is literally a consulting / training agency.

GPT4 is basically Pong. Within a few years we will be nostalgic for its surprise value

HN has a God Complex when it comes to people like Carmack though, so you can't really survive disagreeing with him