Why does the GPT-Engineer idea have to be restricted to programming? Why can't there be a GPT-Engineer which generates architectural design blueprints, or automotive designs, or electronics design schematics? I read that Nvidia has been using AI to help it design chips (not sure how it does that). But why can't we have AI design all kinds of things beyond just software? What would be required in order to make that happen?

You still need to understand terms, maths and logic

Saw this great tweet by some guy saying natural language will become the new programming language

I love how people invent fancy phrases to calm the concerns around their job security.

That’s the spirit. Keep kidding yourself.

But can you screen GPT people with leetcode? /s

ALL the databases are going back to Mircosoft. All this AI stuff is just terrible, the handful of good jobs that are here may be gone and nothing is going to take the place of those jobs.

@@jwoods9659 I agree, but it is inevitable

@@jwoods9659 Any work that can be automated should be. The ideal employment rate is 0.

"Companies will refine job specs for junior devs" These are the same companies that ask for 10yrs experience in a 3yo language. I'm exaggerating, but it will take a long time for companies to adjust their expectations.

No harm asking here, as someone getting their feet wet in coding for the first time with a bootcamp, what's the chances I've timed this badly? I'm looking for career change (admittedly I know the bootcamp isn't enough, need to get more studies after it)

I honestly think that's just a matter of time. But, if I'm wrong, it will eventually get to the point that either companies build from scratch, taking advantage of the fact that they can build at 10x (or maybe even 100x) speed or simply lose to newcomers that can start from scratch and don't have to deal with the challenges of legacy code.

AGI: "Challenge Accepted"

@@jgonsalk one issue with legacy code is that there is close to zero documentation and no one has updated it to reflect all the changes over decades of work. So getting all the "internal" requirements to an AGI agent still requires ingesting all the code by some other AI tool to produce the corresponding prompts.

The developer will never go away. It will be the one that instructs the AI on how to do the job, and review the code to see if it actually does what you wanted to do. It's just at a higher level. It's an instrument. It's like robots making the cars. The engineers never go away, they program the robots and maintain them, make sure they do what they're supposed to be doing.

@@gerardorosiles8918 Yes, but the original idea of changing to another language is almost never possible with people either (in a practical time/budget sense). The idea of an AI helping to refactor a portion of existing code without changing the functionality seems more possible eventually. Like training it in the techniques of Michael Feathers' book, to slowly create seams that let you create automated tests for the current functionality, to let you refactor while keeping the tests passing. I'm sure it'll still be a while, but I'm not convinced we won't get at least that far in the next couple of years.

Existential. That's the word. The way we cope with these changes will set the trajectory of humanity for countless generations. It's existential.

skript kiddies gonna have a field day...

Well said, wait let me find my submarine :)

@@_SimpleSam I dont think it's going to change much of anything at the expert level. It's going to make it a lot easier for beginners to seem more competent, and I think we've already seen a massive bottleneck at entry level jobs. But at the end of the day, LLMs are stupid.. it's like if you take the meme of a severely autistic person who answers everything literally, but multiply it by 10000000000000000x. Sure, there are a lot of uses, but the context and intuition will never be matched. It's going to cause massive changes, but at the senior+ level, and architecture level, I don't think it will be as big of an effect as in the entry level.

@@tonyvelasquez6776 I think you are entirely missing it, friend. You are thinking of it like a tool. Instead, let's try to think of it as an interpreter. Realize: Natural language is Turing complete. The entire stack will be implemented on natural language, with automatic natural language error handling and testing. We are going to see an iterative process where we are backed away and abstracted from the metal, step by step. Eventually, it won't even be about writing software. All software will be generated on the fly according to user request.

Plenty of models out there have been designed to return the sources documents.

@@jonbig04 could you provide some examples? I havnt come across them

in some domains, linear regression models or simple random forest models are prefered over "fancy" neural network models because of their simplicity and interpretability. It's a tradeoff

​@@jesserigonuse gpt copilot for microsoft edge. It will always choose traceable sources unless you ask for logical reasoning or something like that

You have to verify everythig GPT throws at you manually, and yes you have to be literate enough to do the research or accomplish the task in the first place. I see many cases when it just hallucinates something that is completely wrong, which is a bit of a problem when it comes to hard science and highly formal fields of study, but it's also kind of smart, i can see an actual human coming to a similar wrong conviction.

I'm a senior UX designer. I have no idea what he's talking about. I wouldn't be able to check or verify anything here. You need lots more abstraction layers here and a real GUI. But, what I'm thinking is: why does anybody need to work on "boilerplate" things? That is just a waste of time. The world needs a fuck-ton more software. And we need to write it better... there is so much bad software out there (which anyone working for any business knows). Could AI finally unlock not doing "low hanging fruit" all the time?

Being literate is DEFINITELY not what you would need to be. These are LLM's they excel at word play so they will just write back the steps and the user will say go ahead.

@@Joakim-ie5um It's not like anyone spends a significant portion of their time writing boilerplate? Boilerplate-heavy frameworks are generally accompanied by automatic generators. Sometimes boilerplate heavy projects are results of limitations of toolset or personal limitations of the team or a result of technical decisions rained down from the management. Boilerplate results in very little creation effort since it's either pattern-generated or typed actually really quickly but it creates ongoing maintenance effort. In my experience (20+ years of C++) the big effort of developing medium to high complexity software is maintenance, debugging and troubleshooting. As the project grows, increasingly less time is spent writing code and more just deliberating how it has gone wrong or how it might go wrong with the next change, and i can't see ML systems having the scope of either for the time being. You have heard that programmer productivity is approximately 10 lines a day. A programmer can easily throw down 1000 lines of code a day (which is why the 10 line stat seems absurdly low; i assure you it's not), and it is code which is syntactically correct and at a glance semantically correct, just like resulting from AI, but it takes 100 times as long for all the long-term large-scale issues this code has created to be shaken out. Corollary: be somewhat wary of the developers who have nominally exceptionally high productivity on the team, and seem like a "star developer" or "100x developer". By all reason they're creating issues everyone else spends all their time debugging, bringing overall productivity of the team down. Since everyone else has to familiarise themselves with their code, spending extra time, and they don't make any effort to ensure their code is a good citizen in the project. I would say any high engineering cost automation product aimed to create code is of super little value compared to automation to increase code quality or reveal hidden issues. This is also why developers are so excited about Rust language which frontloads some of the effort but reduces maintenance cost.

tell me the bests books to aquire that knowledge

Spot on!

Best comment

“They can’t produce new ideas and they aren’t capable of reasoning” Keyword: Yet. Depending on the reasoning required for product X. Market feature progression most likely will follow product road maps created by predictive analytics. The challenge will be in ideas for new markets (visionaries), market shifts and reactionary stop gaps for unexpected failures. Any technical discipline that’s repetitive- standardized platforms, tools etc, MOST design engineering skills are taught in college and trade schools in cookie cutter fashion. Reasoning and critical thinking is no longer focused other than the top universities. Don’t fool yourself…will be a day where AI bots are chiefly specialized in ASIC design, architecture, etc in various fields of applied sciences. Don’t bet against…just a matter of time.

did calculators replace accountants though?

"Code" will disappear completely. Software is just a crutch. We will ask AI directly to do a task, instead of developing a piece of software specifically for that task. Software development will be a discipline of the past, like many other forgotten professions. Natural language will be the medium we will use to describe and implement functionality. It will be the new "code" with the AI being the "runtime".

Just wait until AI completely takes your job away at every level, we're only about 3 years away from programmers becoming 100% obsolete.

Brother, logic dictates that AI will overpower us in no time. We may see our value - and we should. But there is not a corporate bottomline in the world that does.

​@@flightevolution8132If you have tried latest tools and advances in AI you can see the massive gaps it still has honestly. The jobs it is able to easily replace are the most common ones, like web development, simple API and still it does a terrible job of maintaining code bases. I have tried to get state of the art AI to make functional projects and I can safely say it actually allows me to do the job of 3 or 4 persons previously. However it is not quality work. Code made by AI just sucks ass when asked to do complex algorithms or optimizing things. I encourage you to try and make a fully functional CFD code to see what Im talking about

Not sure what you’re talking about, but the 4 year program I went to we learnt everything starting at a semiconductor level up to bit, logic gates, and built everything from the ground up. Basically everything that a coding bootcamp doesn’t teach you. Coding bootcamp is to feed the industry cheap and fast labor, but also to make money off of the people that want to get a higher paying job that think is easy to do, even if they may not be cut out for it. To the bootcamp business they just want your money.

@@nikflix8331 I'm sure you learned the basic concepts for programing at the bit level. The point was you are not going to write a functional program with market value today by doing bit level programming (with certain exceptions). For the majority of the industry, we write programs at a language level that could be 2-3x removed from the bit level. I see AI programming interfaces as just another layer on top that makes coding more accessible. You seem jaded about coding academies but my company has a subscription for a reason. The majority of people coming right out of college with a Bachelors in Computer Science are not fully equiped to function in their day to day tasks. Coding academies are a quick and easy way of getting them to the point that we need. I couldn't care less if a junior programmer coming in to our lab knows how to program at the bit level. It's not useful anymore.

Good point - codium is AI focused on tests, seems promising.

Yep this is a brilliant point. I’ve been thinking similarly - LLMs can take over the work of converting a spec into BDD -> TDD -> test suite -> implementation

Executed a private project just like that recently. It was extremely efficient. I have 100% coverage as I start by defining the business criterias, have AI write the tests, then fill in the implementation, and occasionally I write custom logic myself, only to have AI refactor it and prettify it while still passing the tests.

​@@jonatanlampa510 how do you confirm the tests the AI writes actually make sense and have full code coverage, without actually reviewing every line that it writes manually? I think that's the issue here, it certainly saves a tonne of time by writing things out for you that follows a specific pattern but at the end of day you need to verify everything manually anyway I see chatgpt as an incredible assistant but will not replace engineers in entirety because you need a human to confirm the AI isn't just hallucinating, but yes, it improves productivity massively if used correctly

​@jackcollis7258 agree. I got it to write a bunch of manual tests (i.e. just words not code) against acceptance criteria and there were loads of errors and gaps, even after repeatedly reprompting it to correct its mistakes.

Where do the future quality programmers come from if very few junior programmers will be needed? And how do the few remaining junior programmers hone their skills when they mostly let AI do the job in order to remain competitive?

The video talks about "high quality programming". Sorry but I dont't know any. Do you mean Windows, the bugged to death OS? Or Linux, the another bugged to death OS? Or? Because these are the biggest pieces of today's programming, crappy and full of security holes. Is AI going to make it better? No, I would say quicker && even worse.

This period will be short lived. "Code" will disappear completely. Software is just a crutch. We will ask AI directly to do a task, instead of developing a piece of software specifically for that task. Software development will be a discipline of the past, like many other forgotten professions. Natural language will be the medium we will use to describe and implement functionality. It will be the new "code" with the AI being the "runtime".

yea isnt it like when the code libraries started getting very built out, it just make's the basic stuff easier

My opinion... Software will be a black box which humans won't even know exists. When my mother goes to the bank, she has no idea that the bank even has an I.T. department, let alone what it does. She doesn't need to know. Remember punched cards? "Punched cards", what are they? Exactly. Remember software? "Software", what's that? Get the picture?

Good points!

Are you using GPT4 or 3.5?

@@JohnWalz97 I'm using the free 3.5, cause I'm not allowed to use it at work, and I'm not paying a dime for my personal projects. I know GPT4 is much more advanced, and I know from a friend that he uses it as a work horse, but still he is very experienced developer who can describe well all the technical stuff he needs. I think that AI won't replace developers any soon because it is though on a flawed code from internet and it's based on text predictions. So, even if someone describes well a certain task and the corresponding model manages to produce a working version, there are still things like security that need to be observed carefully, or they may cost someone a huge amount of cash, reputation and more.

​@@Deadliousyou can't imagine what a jump GTP-4 was for coding. When I tried 3.5 I thought the same, but if 5 is a comparable jump as 3 to 4 (and when it truly becomes multi-modal, then I think a lot of complex topics will become easier to learn), I can imagine that it'll start replacing entry level engineers (or even mid level) and then for 5 to replace all devs wouldn't be a big jump.

​@@DragonRaider5Its still just a predictive text model pulling data from the internet. If the data is wrong (which will become a greater problem over time), its utterly worthless. GPT5 or GPT3000 wont change that. And the idiots who depend on these systems to do tasks that they couldnt complete themselves are going to make massive errors and mistakes that they arent skilled enough to spot.

If you think about it, too much effort is wasted on GUI, and often the GUI ends up poorly designed - not intuitive/difficult to navigate, too much/too little information displayed at the wrong time, trendy unproductive GUI, etc. The perfect solution would be to interface AI with the code and have it display a dynamic GUI based on user directives. This however cannot be so dynamic as to be changing every time the program is run. More like based on use case, and in the form of a "style" PS I find the text interface of AI chatbots refreshing for getting information. Compared to being overloaded with graphical content and useless verbal diarrhea on websites.

power for knowledge then how use knowledge then damn i ahve to not be lazy and use knowledge eating well and exercise.. nvm i mean coding well

like the optimism but the nature of this technology will not let enough ppl to leverage it. The ones that already have the experience and resources will go even higher while the rest will struggle even more. It will be harder to train if you don't have connections and to access such tools if you don't have the resources ( i doubt it will stay this cheap forever). But yeah.. some will thrive given their luck and standing when this becomes the status quo.

Shhhhh...you're going to dismantle the hype just like Web3, Crypto, and NFTs.

yeah but this is the first step...next step tell the bot to look a a git folder and analyze that fork you are working on...LOL infact if I can get this working Im going to have it analyze its own code and suggest improvements....BWAHAHAHAHA Its alive!

Big enterprise software, if well developed is just thousands of pieces of code like the example shown.

@@Cyhawkx yes very simple

True

3.5 is garbage compared to 4 these test results are nothing

Of course it's garbages as a replacement... *right now*. That's the concern. What about GPT 10? Or 20? How long until it can do our jobs better?

I agree. Gpt is great if you already know how to code or test. If you dont you will generate dodgy code and not test properly. For a few years there will be many jobs fixing gpt bugs.....a bit like the year 2000 problem but bigger. But in time things will change....how? nobody knows.

When humans first started to develop tools they used the materials that were close to hand, wood, stone then later on metals, then silicon etc. These tools developed and evolved over time to fit the environment they needed to exist within, AI is also just a tool trying to find its place amongst the humans that use it. We are still in the early days of this technology, it is improving rapidly though, GPT-4 currently has a bunch of plugins available to it, so it can search the web or access things like Wolfram Alpha etc. I think people need to understand that the level GPT-4 is at the moment is more akin to a tech demo and not a fully functioning tool, that being said it is still massively useful for many people if they know its limitations. Over time AI systems have a tendency to improve, they are only really as good as the datasets they are trained on and the fine tuning that is applied to them. AGI is a whole other world, you are talking about a non-human system having the knowledge and understanding to solve all problems, also a level of sentience that we can't currently comprehend. Transformers are part of this, GPT is a NLP model, it is good at seeing patterns in text based on certain contexts, something many humans are also good at, but like all humans they are also good at seeing false positives, pareidolia is a good example of this. I am also very concerned with how much trust people put into GPT 3.5/4 etc but they are people who don't understand what it actually is, that being just a tool in the early stages of development. I am pretty sure when the hammer was first invented, many people accidently hit themselves with it without fully understanding how to use it, to be fair some people still do lol

Yep, your experience mirrors mine. I tend not to trust anything I get from it. I tend to use it mostly for generating basic boilerplate or making alterations that would be cumbersome to do via a regular expression. It can help with documentation, but like its code generation, you need to keep an eye on what it's spitting out as it can easily produce believable sounding bullshit.

I think transformers might get there, they just need to be augmented with long term memory and recursive "thinking" processes. When I'm thinking about solving a problem I myself hallucinate answer and try to disprove it based on my knowledge or I start from first principles. Currently Transformers are used just to do the first part, but it's proven that they can also reason given their context and there are some early implementations of long term memory augmentations already. And this memory could hold examples of whole high level architectures or even knowledge about single transistors, shift registers, architecture specific accelerators, whatever that LLM without augmentation can't take into account. So in like 3 years we will have better models, new specialized models, better datasets, order or two of magnitude lowered costs of inference because of hardware accelerators, matured long term memory implementations for LLM, new architectures and frameworks of recursive "thinking" about a problem, probably even full blown multi-model reasoning systems with different models for coding, planing, reasoning etc. I seriously think even high level system designers might be forced to adopt of whatever workflow is coming... I could easily imagine a complex systems of augmented LLMs where there are continuously recursively updated discrete steps of high level planning, middle level planning, writing pseudo code based on previous steps, and then passing this pseudocode to programming language specific LLM for final translation to code. Some parts of this system could be also integrated with chatbots that could ask users for any additional info.

I'm still surprised people use the chat front end and not the API with proper prompts. Huge difference. I don't mind though. Less competition :)

It will only continue to get better and development will require less and less man hours over time. Its highly likely this will have an adverse effect on the rights, salaries and employment levels of software developers. There isnt an infinite amount of software that can be made.

@@stugeh This is a really good discussion. I wonder what the limitations here are, and how they will be overcome. If you end up needing thousands of words to define specifically enough the application or the requirements you want, it may end up being more cumbersome than just talking to a human and asking for "do the thing with the thingy on top of the other thingy". If we don't solve for that, I can see the situation in which metaprogramming/programming confugurations for prompts become a skill. What if you want to make a modification in your code? is it simpler to go in as a developer and tweak it? or re-deploy it as a complete new service by changing the prompt? For small enough changes it could be that separating the prompt into smaller chunks would be best, and that point you have created the software equivalent of terraform, but with prompts and different parts of your application. I believe there is still value in knowing how to code and not becoming exclusively an operator, at least for the time being. I do believe that knowing this technology and keeping up with the next ones (two paper down the line, like the guy from Two Minute Papers says) is super important. We joined this industry as software engineers, and engineers should never stop learning.

I would agree but if you are into making your own custom models, you'll realize it won't be this way for long, seriously not longer than a few years. AI will accelerate AI research itself soon.

​@@P0lntL3sS I understand what you are saying, and I agree that the progression will be as exponential as we are seeing it. I wonder if there is an upper bound limit to this, given the constant creation of new tools, lack of standardize adoption, initial lack of trust (we all expect this to fade), and confusing competitive advantage among them. We'll see what tool or suite of tools hits the right spot and how that shapes the industry, all we can do is make the best out of the situation. Food for thought!

@@stugeh You'd be surprised =] The way I see it, it's just another level of abstraction that will help make developers more productive, maybe allowing for more complex software to evolve. They didn't need less developers when they stopped using punch cards or when the first compiler was invented, they needed more.

I would imagine that gpt will also help people decipher the 100s of code styles in a gpt generated code base. For example, I had a friend recently send me a function, I definitely could have spent 20 minutes reading it critically and understanding it, but instead I got gpt to outline the main steps in the function, which made the readability faster, and I was able to understand it in a fraction of the time.

I bet there are ways to address at least some of those issues. Like this video uses a wrapper application. So a wrapper could tell it to have a certain style, or at least keep the current style it sees in the project. Also, I think it'll be a while before you'd be having an AI just create a large codebase on its own. I work at a company with a bunch of senior devs, and we still code review each other as part of the process of adding new features. So it'd be good to have a person code-review the AI. And the AI should be prompted to change only the parts it needs to, separate out feature vs refactoring changes, have good commit messages, etc. Just because a future AI in theory could re-write an app from scratch for each new feature, I don't think there's a good reason to want it to do that, vs having it act more like a human would. Depending on how the AI works, it might even be better for it, having old commits and diffs to look at. This is all so new that we don't really have a good set of best practices yet, and the targets are also always moving. But even if we get to the point that an AI can handle a big codebase on its own, that'll have its own set of best practices that comes with it.

Because the floor is large.

@@markm1514 so is your mom

Thank you so much!

I cant even get It to work

I just want to add one small point here (that actually occupied minds of almost every philosopher during the whole human history): but what is thinking? what is creativity? can you define it? when and where is that strip of events and complexity that makes just taking patterns and returning patters to a creative mind? we yet to see that and nobody knows when. and it might be pretty soon to hapen.

​@@robin_birdie_and then it will become impossible to see anything you do as truly unique and valuable. How will I feel motivation to solve any problem on my own knowing I'm not achieving anything special. Just let AI do it and go lay on the beach. Your job is done here.

​@@robin_birdie_we are constructing rationnal reasonning though, mixing theorems and axioms together. GPT is just predicting the most probable words, I somehow doubt its creativity potential.

If you define 'primary' in terms of duration, I agree. If you define 'primary' in terms of the end product, I would say that working, correct code is the primary task. But I understand your point. Someone needs to write the requirements, document the design, write test cases, comment the code (although it would seem that the GPT should be able to do this), unit test, merge and test the released code. And when you're working with an existing code base, to fix a bug, quite a bit of time can be spent in investigation.

​@@prependedprepended6606if you work for a large company like I do you spend most of your time trying to navigate all of the process and procedure and management reports and other obstacles they put in the way just to get your job done. I spend very little time programming anymore which I find very disappointing.

@@prependedprepended6606 Exactly this.

@@aaronbono4688 Aaron, seriously, try to get out of there if at all possible. I've been in that situation and it can suck the life out of you after a while. Especially if there are any devs you respected that left there to go somewhere else eventually. I was really scared to leave the security of that job, but was definitely the right decision in the end.

@@ShawnFumo I have worked in well over a dozen different companies over the last 25 years. Big corporations are not the most enjoyable places to work but you make the most money there. I found a company that's better than most and since I am focused on saving hard for retirement I'm just fine where I'm at. The smaller more exciting companies are also more volatile and I've had my fill of that and I'm done with the stress.

Make a real example and try it. I think we are already here.

This is the worst it's going to get.

Its takes an AI about a minute to reformat and optimize hundreds of thousands of lines of code in any language you like... today.

@@obsidianjane4413 Not in my experience. It's useful but it needs careful supervision. No doubt we will get there soon enough though.

The question in my mind is, will AI be able to adequately understand business requirements. If it can get to that point then yes developers are in trouble, but otherwise we will still need humans to interpret and appropriately model the business

I find the results to be of a comparable quality to offshored, but iteration is way quicker.

Spot on, here in Australia more companies are now using off shore engineers than local engineers. We have a engineer who is our translator and lives locally who speaks to the off shore teams and the work is just as good but for 1/3rd the price.

The issue with AI, though, is no matter how good it is, how do you ensure that it is indeed correct in reviewing the code? With an AI, who do you hold responsible for any issues? What if the LLM being used is running internally, do you fire the lead of that department or team? With people reviewing it, it is much easier. And even if the failure rate is for some reason higher with people, at least there is someone who can be held accountable, and someone who can verifiably better at their job. That's not so simple with LLM.

Why you think they bought NPM and GitHub, they don't need Stackoverflow because their data is more open than Wikipedia. Microsoft is still or again Evil. Like all the Evil Big Tech

Wait - who will advance technology if everyone is just using canned solutions provided by LLMs that are based on years-old code bases? No more junior devs and no more CS students means once the grey beards retire, there'll be no one left capable of innovating or improving. It'll just be a bunch of tech priests performing rituals to appease the (quite literal) machine spirit, reciting sacred prompts to hopefully get a working solution. Patterns generated by the machine will be treated in a cargo-cult fashion and pieced together until they run or compile without anyone really knowing how and why. Hyperbole, of course, but maybe not too far fetched either...

Well, finally we will have Warhammer 40k

Until we create business analyst GPT

​@vitaliiivanov9514 nope coding is very clear logical instructions that's why most no technical people cant do it

I really appreciate reading level-headed thoughts like this. Thank you. I'm tired of seeing so many AI-enthusiasts feel the need to advertise their new tools as ground-breaking and scary. But it's what drives engagement, so 🤷‍♂

I upvoted, but I'm not sure if there is evidence to "expect diminishing returns" yet. In some sense yes, like the leap from MidJourney v1/2/3 to where it is now, going from something that was only usable in a very narrow set of applications, to now having really good results for many things with v5+. Now it is more about better details, more resolution, better understanding, etc. But even if it is technically less returns, one that can make hands vs one that can't make hands ends up being pretty important in practice. And also text to video now starting to go full force. I see so much progress lately with making models smaller, with less training data, training on processes vs final results, different ways of prompting, adding memory, increased context sizes, combining multiple models together as a group, etc. I'd be surprised if we are already most of the way there for programming abilities of AIs.

Thank you - appreciate your comment!

I think that what is missed here is that someone needs to specify complete and correct requirements. And yes, when multiple layers must be changed in existing code, unless the AI knows *your* existing code base, it's going to be difficult for it to generate all of the necessary parts. To be fair, Arjan did call out that the most likely scenario would be using an AI GPT to make developers more efficient.

thats what i was thinking it makes writing trivial apps a lot faster, rather than spending a hour to do that it would take a few minutes but this program is very simple.

when he said "It takes minutes to write a complete application" I chuckled. That's barely a simple service. Yeah, it was really quick, but hardly a "complete application" Another thing that a lot of people miss is that in a professional environment, most of the time will be spent deciding what we want and how we want it (and then changing your mind when you're halfway there), not actually writing it.

@@MadsterV The thing people fail to realize is that coding is 10~20% of an engineers task. Most of the time is spent on knowing the business. IF you follow that code is the byproduct of learning. Engineers are in the business of learning the business, politics, dealing with diverse situations outside the screen. Due to these reasons AI will just be tools as businesses rely on human relationships to store knowledge. Who knows maybe there will be a AGI that can replace that but its honestly a few decades away

@@jokwon7343 but not all engineers need to know or understand requirements. As a senior dev, with current gpt tech, i can replace 3 developers and maintain the same productivity. a year from now - maybe 10? of course dev productivity expectations are dramatically rising as well. But either way, its not 'decades away'

Fuck that is harsh. Well I can bet that the right opportunity will be yours. Are you in a location where there are a lot of tech companies or are you only applying for remote jobs? I graduated in 2008 and just this year I was able to get a job in my field of study. It might require a lot of patience against feelings of never being able to do your dreams. Don’t be afraid to take another job that is not what you want for the long term. You should be focused on paying off student loans by any means necessary. Trust me, you do not want to be in default of those. You won’t even be able to get a pay it in 4 account approval. Trust me. It happened to me. You will catch your groove. Focus on continuing to skill up by networking with people in your field you can learn from. Constantly be learning even still. When the right opportunity comes you will be that much better. Just a tip, look into quantum computers. This is going to be the next big thing. You think AI is really something? Wait till you see about quantum computers. If you cop the skills for working in that you will surely be mf golden especially in the quantum computer explosion that is coming. It’s worth the uphill learning curve my bro! That is what I recommend. One more quick story. When I was in college, you were really only expected to get a bachelor degree for a secure and decent paying entry level job, and when I graduated the recession it, and when the recession lifted you needed much more than a bachelors degree to be competitive, and to get that jobby job. I am 41 and according to MIT I do not make a living wage for where I live in California but I’m still making it and guess what I am continuing to skillup. Yo what you said is a little daunting to me because what I’m pursuing is in the related field of our subject in my head just runs with negative shit but I have to try because if I don’t try my chances of success are 0.0#. Find some people in your net work, or make them in your net work, who are in a similar situation as you and former company, and start finding an identifying opportunities with businesses, or somewhere in life and create and carve some projects for you to work on to add to your real life portfolio. You were going to need that absolutely. Even if you have to do it pro bono at first. You look like you have some time on your side based on the picture that I see in your photo here. This one’s gonna be about the journey, my bro. Good luck my bro!

I doubt the main reason for the harsh job market are LLMs. I guess it's rather due to the economy, some huge tech companies basically detaining a monopoly (bad for competition and innovation, everything else is basically being sucked up by the "advertising industry") and maybe some sort of saturation of the job market (coding isn't a niche thing any longer, plenty of young and talented people got CS degrees, took bootcamps etc. over the last decade). However, I feel like good engineers (those who actually understand what they are doing) are still highly requested and will probably remain requested in the forseeable future.

It was like that for me as well as a junior dev, it has nothing to do with chat gpt

Do you think there will continue to be room for such startups to compete for existence against increasingly more massively endowed gigantic and mid size tech firms?

@@user-yv6xw7ns3o I really don't know. My gut though says that everyone able to hold their own during the first stages of their journey to become a developer in that hypothetical environment will be able to identify niches to fill the gaps between those giants. I'm quite optimistic that A.I. will be more of an excellerator than a true hindrence. Even if the job of a programmer in and of itself might die due to grand accessability to everyone, those everyones will have to distinguish themselfs through great architechtual prowess and immensly good ideas. The field will change. But the real programming is mostly the functioning construction of interconnected subsystems, wouln't you agree? And If one can't think of the details in such a system they are little of a programmer in the first place, whether they know syntax or not or have to know syntax due to A.I.. I admit that A.I. will also be capable of creating interconnections with one not understanding a thing about their functionality. But the more complex the A.I. the easier the entry into a niche, and the more niches are filled the more creative one has to become. I think it's an interesting feedback loop :>

I strongly disagree. Most students will definitely not be able to use AI (which is good at spitting out boilerplate of already solved problems), to build businesses. In fact, I don't believe that AI will help even senior engineers to build new businesses (except for, of course, saving some time spitting out boilerplate code).

@@nomadtrails Interesting take. Due to it's unimaginative nature or are there other reasons in mind? Don't you think that this issue will be solved in a view years? I can imagine a programming A.I. which has the current capabilities included in a model with clear testing and learning directives based on syntax alone. After which you could give it a task to solve a deeper problem.

@@nomadtrails I'm with moodmaker. The vast majority of software even in startups aren't actually some super innovative concept, in terms of the code. It is just applying the standard coding practices to new business problems, in such a way that the eventual complexity is managed (and so hopefully the whole thing doesn't collapse into a ball of tangled thread). OpenAI said they improved math in GPT-4 by training it not just on getting the right answer, but on producing the right steps to solve the problem. I don't see why an AI won't be able to be trained to turn generic concepts into code, to ask clarifying questions, to refactor existing code into simpler pieces, etc. It certainly isn't there yet, but who knows in a year or two.

So, you don't think that ChatGPT's can't do imagery?

@@prependedprepended6606 sure... but a.i. is a long way off from replacing artists. A LONG way. If I need a pixel animation for a game... it might be able to give me something but it won't interpolate correctly and it will lack specificity and won't take palette into consideration. Neural networks seem to be great at making fine art but they're not there yet for "working art" like illustration.

​@@prependedprepended6606while I think you are correct in your response to this particular post art is not just imagery, there is an art to designing an application. Coming up with the idea and the instructions to give these bots so that they create what you envision is a big part of the art process.

Consequently creating lots of competition, and what do you think people will do, create games and play your game.

@@malusmundus-9605 There are some amazing 3D model generating AI apps already. One day there will be a simple tool to create 3D models etc..

Yes but the problem is they progress in much higher rate than you do.

There will be no software development long term. Why create a piece of code to do a specific task if you can simply ask the AI to do the task?

We use frameworks already and not write all code by ourself. The problem is that there is no standard of natural language or ai generation and ai companies tweaking algorithms for every version without a clue how it affect its reasoning at the other side. I love ai tools but they are also very unreliable.

@@minimal3734 for one thing because text and spoken language are a terrible user interface for many tasks. For another, we are still very far both from general artificial intelligence that really never needs specific guidance on how to do things (=programming), and from running LLMs cheap enough to warrant the extreme inefficiency in terms of time, energy usage etc

Glad you liked it!

Guaranteed income is already here: $0

exactly ... no layman can use these tools for anything yet.

+1

More people will be able to do the same job. Competition will skyrocket and salaries will plummet. At the same time this all will be automated and before the end of the decade the AI will walk normal people through building what ever stuff they want and even IT research positions will be scarce. AI is the Great Filter, solution to Fermi's Paradox, next stage of evolution and our inevitable extinction.

​@@Ilamarea There's no single thing in AI that will make someone who can't go pass the initial boilerplate code to do a developer's job. Even when AI becomes more capable than making just a boilerplate, there won't be a single thing there that will make a non-developer a developer.

@@Ilamarea How in the world can you walk a non-expert even through the example given in the video? The terminology will not be understood by the layman, who cannot guide the AI.

It will have have a similar effect of not having to build a library every time you want to use it, or with other open source material. You’re just able to get it without killing as much time. There will still be more layoffs in tech though but there will be other new jobs in tech that are related. It’s just change and many people across disciplines will need to adapt.

Maybe we will finally go back to lower level Lang's like FASM

This is exactly what I think. I do not know how long it will take, but for sure it will replace a huge portion of developers, with a few left to manage it. It is kind of what the industrial revolution was back then, instead of needing X persons to maintain production, you now need ~X/10? or even less, and machines. We couldn't see this coming a few years ago. Today, it can not replace a senior developer, but it certainly will.

Hmm, but who said we have to train the new people in doing the junior level stuff only, what if universities/colleges/boot-camps/self-study folks directly start learning the higher level stuff? Like architecture? Won't that threaten the position of senior engineers as well? When the market will be flooded with folks who have the same skill-set that took the old senior engineers years to develop.

Until few large IT companies end up with near to identical chunks of code in their product and then start to suing each other for stealing.

Maybe no in next year

Let’s start a construction business!

@@ArjanCodes OK, I will definitely call to establish the company

Robots do the physical work

I think the best way is to automate all the jobs so that we can just chill and work on our own stuff, like Star Trek. Something tells me that future is beyond the greed of the current era, though. People are so concerned about ML replacing them because right now, we have to work to even stay alive or have a place to live. In another universe, I think the ML models would invigorate creatives to rise even higher, to make stuff the ML still can't. I dunno. I think trying to chase away the AI is focusing on the wrong problem.

⁠@@Mr_Hassell it hard to happened cuz physical things expensive which make it high cost and hard to start as profitable business and some physical work is more suitable to human and much cheaper and reliable. That is my opinion why that is not happening right now

True! AI will produce horrible ‘solutions’.

9:04 develop higher level thinking skills? People proof again and again they are not even capable of recognizing interests that lie beyond their short-term self-interest.

First AI replaced the artists, but it didn't bother me, for I was art wasn't my field. Then AI took over for the software devs, but I didn't even flinch, since I had my mechanical engineering degree. When AI and robots took over mechanical engineering, there was no one left to worry for me...

@@totalermist It's good to see that someone has a sense of humor about this!

No it really will replace you. I don't need a tech lead and 5 developers. I just need a tech lead and an AI. Yes, I'd like fries with that

Agreed. Moreover, as long as we use LLM based tools, we really shouldn't worry, because this architecture of AI has a great understanding of language, but no real cognitive skills, like: abstraction, cause and effect, algorithmic understand, planning, and imagining. In addition, we must be responsible when using AI tools, because they might make mistakes. However, these AI tools, because of their benefits will probably reduce the open jobs for complete beginners. This will create a situation that slows down the tech industry, because it will deprive of itself joung and talented mindes, even if they are inexperienced. Also, it means that in the future, those who do get hired will have to be very skilled and have a lot of knowledge and experience before their first job, something that is very rare. In the end, it all of this will probably slow down the future growth of the industry, make it less open and more exclusive, which is not completely bad, maby it means we will break production less often...

It has already replaced 8 developers at my company. They have Supply Chain Management processes to be digitized and so instead of hiring 10 developers, they hired just 2 and we are quite efficient as we know how to use GPT to our advantage. So yes, it has replaced a lot of jobs but you won't notice it just yet. Not even in tech, it has replaced lawyers for writing and updating terms of service, privacy policy, cookie policy, etc. It has also replaced executive assistants and business analysts. Now you only need one person to handle those roles using GPT. AI can make presentations for you based on the transcripts that you have from the meetings and calls. I can go on and on.... So, think again.

@bluzter I don't what kind of company you work for or you own but if so can replace employees it's logical to think that starting companies in general become easier in other word the barrier to entry has been removed so the competition between companies will become more serious

@@bluzter if two people can manage it with AI, then it has never been a job for 10 people. And if it was planned for ten people, then it was poorly planned.

thats a good point

Welkom! :)

It literally outputs the very first Google searches

soon it will be