the "AI Engineer" scam tech CEOs don't want you to know about

so this is Mark zberg who says that probably we will have an AI like a mid-level engineer in your company who can write code he mentioned that some other companies are working money but it's not only that right you have Mike benof from s force saying that they're not adding any more software engineers in the next year 2025 because they have increased the productivity by more than 30% using AI actually I think they have about 200 openings for software Engineers but still that's what they say which is why today we will talk about the big

Tech lie the AI driven Engineers together with Bon we will do a first principal analysis of AI driven software development we will look at the data and we will use the scientific method to really understand what's happening because I think there's a lot of confusion right now and a lot of talented Engineers are questioning their careage choices when they actually should not and you will see later on why and the fact is just like in the Batman movie that you always fear but you don't understand so let's understand this thing let's really dive deep and

understand what is happening right now in the software development market and in AI driven development and here is what we are going to cover number one we will do a first principal analysis of the existing AI tooling then we're going to look at the myth of AI driven layoffs and we're going to find out what's actually behind the layoffs the take layoffs happening why AI actually means more coders and not less also called the Jen Paradox in economics next we will look at the gp4 hangover and what happened upon its release and finally we'll talk

about what can you do as a softw engine engineer you're probably thinking do I even have a future is it even W it just like our students and we are here to give you the tools and to show you how you can make the most out of this if you don't know us my name is dagos and together with my brother Bon here in this call we founded the senior de about four years ago where we help JavaScript focused Engineers level up to a senior level in the most effective way possible so let's talk about

AI tooling and let's make a first principal analysis to what this AI tooling actually is based upon and what does it it does really mean for the software engineer first of all it's not about AI what we are talking about is actually an llm a large language model which is behind a chart interface or a code editor and what does that mean for softare engineers so what it means is that at the core of the AI as they call it um there's just a large language model which is built on a naral network with a

lot of parameters that was fed a lot of code in the case of GPT 3 and four the code comes from GitHub like all the open source code We have basically in the world and then stack Overflow and so you feed all that to an AAL Network and then you have this capability of linguistically suggest code or Solutions and because it's built at such a scale it really feels like it can build you know things like a small react application by itself and so a lot of people think that's intelligence right that it's basically intelligent

because of the quality of code sample it gives back what open AI did very well and what new companies are doing is to Rebrand what a lot large language model is which is not very salesy and very flashy into AI AGI and what's the latest one super artificial SII super artificial intelligence and they just keep pushing that into basically everywhere and we will see why they do that later of course the whole business is based on it but the thing with llms is that llms are not limited by the data it ingest they ingest which

is they can be limited by that and that's what they want to make you believe but by Design right because we have all these people that say oh yeah you know CH GPT can only help you and it makes tons of mistakes but it will get better right there is is fundamental belief that they will get better and better because this technology it will improve and at some point developers will be out of way yeah I think everybody's assuming that the models will exponentially get better but we will probably hit a plate two because of

the design of how is it made and what we've seen in the last couple of months with GPT is that there was very little Innovation on how the llm works and a lot on the UI it can Now consume text and images but again it does all that because images are literally text um and then we have these video generators that try to do the same but the design itself of How It's been built it didn't change at all and what we are actually seeing behind all these marketing schemes is the same llm with marginal

Improvement it's like again putting more data um actually there a mistake there but it's like putting K kerosene into a gasoline engine better fuel better data does not mean better performance right you can put whatever fuel in the end the the design of the engine will become the B boundary condition right the limiting factor there the second point is English is not a programming language right it's a human language so people claim English became now the the programming language of the world but the truth is humans can deal with English because they share a nonlinguistic

understanding of the world not because English it's a great programming language exactly and this is where I believe a lot of the tech influencers are wrong a lot of people have come out and said well AI it's already better than a mid-level engineer or you can use AI as a junior engineer I heard that one a lot like hey AI it's your little Junior engineer I'm like no it's not it's the total opposite because the things that AI does really well or the things AI knows or the things you can retrieve with this language large

language model which would be more correct language right you can retrieve code samples and manipulate them they are the total opposite of what a junior engineer can do junior engineer and mid-level Engineers usually have a very good understanding of the world of intention of where the team you know what the team needs and they sometimes have trouble understanding the lower level API the browser how JavaScript really works so I believe that both mid-level and Jor Engineers have huge complementary skills but they are exactly on oppos sides when it comes to replacing each other basically as

say the worst Junior Dev it's much better than the best AI 12 Junior devs can actually sore problems and Bon you already this quote from Yan leun which says llm errors are not fixable without a major redesign meaning that whatever it will take us to AGI or the next step in this technology curve it's not the current technology that were being SW and and the point of this first point is you know don't freak out these things they they might seem very intelligent right because they have a lot of tricks and things behind but they

are not the only intelligence we know so far it's human intelligence and if you want to dive deep into this topic this is one of the slides from Yan talking about how Auto regressive L LMS the current technology it's it's doomed because they are not controllable and the probability that they produce a token that's outside of the set of correct answers is very high and it diverges exponentially in is not fixable without a major redesign the technology is not there despite what you know Mark zberg or Sam Alman might tell you exactly remember that llms

are all about predicting the next token that's how they were design and there's been a huge rebranding on hey this is artificial intelligence but it's really just predicting the next text token so you can imagine if you inest and I think they did it over the whole Wikipedia The Wall Street Journal they injested pretty much every text database you had and a very good predicting the next token that's it so the whole AI discussion it's not about AI it's about autoaggressive LMS which are you know an Network that can predict the next token diges in

tax on to the second part which is the meid of AI driven layoffs and I chose this picture from the movie Margin Call because in the end who's pulling the strings up there it's a bunch of NBAs they might be great at Financial things but they are not that good at technology so you see companies claiming that the tech layoffs that we've seen were driven by an increase of productivity due to AI right you seen the CE of say for saying that and actually the reality it's the opposite they were not driven by any kind

of improvement technological Improvement they were driven by over hiring in the past most companies most te companies over hired they thought hey you know covid means everybody's going it's going to be remote they're spending more time on the platform but then you know Co went away and they hired all these people to have resources to deal with that but when uh restrictions were removed people went out to their normal life then they you had like huge product fails and the metaverse for example in the case of meta was one of them these companies they have

to always sell the next big thing that's the game to raise money A lot of times in the last years those products they don't meet the expectations of investors to do you have to get rid of people the third part is the lack of innovation right which is beyond Acquisitions and monopolies the tech sector like the traditional tech companies including alphabet and meta they don't have a lot to show and if you look at the most successful products they were all built maybe half a decade or a decade ago 2025 this is just a perception

game that NBAs and the people at the top are using to keep the programming class which is developers software Engineers from asking for more money and I will show you why because the reality is the stock market like we have the NASDAQ here we have the S&P these companies are doing very well they talk both layoffs they talk about efficiency but they are making more money than ever check the stock price of alphabet check the stock price of meta and you will see they are doing pretty fine they have the cash but what's happening with

all that that cash and people talk a lot about inflation right but if you look at the the data from 2023 right corporate profits drove more than half of inflation right what does that mean in the last 40 years prior to the pandemic profits right like the money that corporates pocket with just 11% of the price growth right and we saw um an increase in the price for consumers by 3.4% in last year but the input cost like the cost for companies to generate those products has risen by just 1% which means that for many

Commodities and actually for many Commodities and services producer prices actually decreased so corporations have kept those money and they are not passing those savings to the consumers and if you look at the corporate profits as a share of national income in the US they is kated by 30% right from the side of of the pandemic the economy is back or surpass this prepandemic level but workers share of the corporate income has still not yet recovered why because it's very easy as a company to raise your prices you can do that tomorrow right you can just

update and raise your prices but for employees to to also update their salary right they have to go through a negotiation and they have to go through a review process and software Engineers are part of that these people are bluffing uh these companies they have a lot of money and they just want you to believe that you are replaceable they want you to believe that somehow the magic of AI will mean that he will replace you when actually you know they need you more than ever they just don't want to pay you more and that's

the sad reality on to the third Point why AI actually means more coders this is a very well-known phenomena in economy called the J's Paradox uh and why do we have the picture of U of coal factories here is because people thought you know uh when coal will decrease price it will not be used that much but in fact it's just more and more companies started using Cod so why does AI means actually more colders well an increase in developer productivity it means that building software gets cheaper so people will build more software right more

companies will build custom Solutions or ramp up projects that were on the Shelf like basically a lot of companies were not migrating Legacy code a lot of companies were not building certain things that they knew they had to build because they were like oh yeah but we need to hire more deaths and it's going to take a lot and we don't have the budget and again even if you know coders will get faster the main challenge for those tech companies that you saw it's not how fast your developer can developers can code definitely if they

can code faster that's awesome but are you building the right thing and most of them as you will see later fail on exactly this thing fail on building the right thing not turning more Cod and big Tech what big Tech is hiding it's product failures behind this AI improvements as I mentioned for and going back to the to to Mark who said hey we saw an increase of productivity of of 30% engineering is doing very well we don't need soft Engineers but if we look a bit further and we look at how his company is

actually doing we see that safe Force has a product problem right they need Engineers people don't like the product and they are saying hey we don't we're not going to hire more Engineers we we will hire salese to do what to push a expensive product that feels like technical depth um down the customer's throat no what Sal Force actually needs it's engineering talent to simplify the product itself okay the UI it's so clunky and frustrating I can't even be begin to express how non-intuitive it is they have UI issues like this is a screenshot from

you know this this this was July 1st 2024 they need a better designer product testing thing or something we Tred it out got stuck with them for a year because of contact and have since moved on to a different CRM now Mike you don't have an AI problem you have an engineering problem and you're going to solve that with more soft and it's the same for Amazon it's the same for meta it's the same for Google itself this product are not you know delivering and the solution will not be AI the solution will be as

it was in the past good product and great coders and great Engineers that will actually simplify those products and get them back to be competitive in the market but they didn't worry too much because they have a monopoly that's for the for another video on to point number four the GPT 4 hangover yeah so literally when GPT 4 came out you already had the whole YouTube and internet saying okay it's over AJ is here um not only developers will be out of a job but marketers you know product people copywriters and so it's been eight

months and as far as I know there none of the stuff we write that sen Dev it's using AI we tried to use AI several times and it would create you know this one step forward to step backwards kind of thing where you had to just start from scratch because again um many times what happens with these these large language models is that they'll just give you like Faster Horses but you need to think about the car you need to stop and you need to really think about the customer problem and they're pretty bad they

actually slow you down when you do that we've seen GPT already ingested most of the stuff it could the only data that GPT 5 will have that GPT 4 didn't have is the conversation data it had with the 500 billion people that are using it every day however you got to understand that that data is just a subset inferred from the original set of data so the quality is going to be very low and so GPT 5 will more most likely be trained on the same data because the humanity did not produce that much valuable

information or data in this six months and yes people say well the amount of data doubles yes but it's usually a copy or a derivation of the previous dat because valuable data was produced by Humanity getting better at specific problems right not by just duplicating the same text and rewriting it with an llm and so it's important to understand what's the semantic value what is the value of an actual text and if it's derived from another text then it has almost zero value it's just saying the same but in a different way and so it

will probably have marginal improvements but they will Market it as AGI and know probably use some UI tricks like trying to add voice or trying to make it qu itself to make it look very smart or you have the standardized programming benchmarks that they come up with like hey you know 03 is like 95% better than O2 but that's all made up that's all in the lab those are standardized test that AI can easily pass it has nothing to do with the real world and what we've seen is that if you look at the data

GPT usage kind of tank so this is the data in terms of unique visitors to GPT as we see it's kind of stable now and the average visit duration cuz that's actually what's telling us are people using it do do people get value out of it and we see it's slightly decreasing and if you use GPT a lot I use it heavily for coding uh the has been using it for anything that we do senior Dev that's not strictly coding I use it inside csor which is the code editor and you'll see that it gets

to a point where you just get tired of the back and forth and you start you know looking at the code and trying to improve it yourself it doesn't mean you're not going to use it as an autocomplete but it will get to a point where it makes you less productive and I think people will get smarter and slowly you'll see the increase in the average visit there'll be like kind of less visits and people will just get to the point where you're not really using it anymore for important thing and so going back to

the Garden hype cycle which is how we analyze new technologies there it's a lot we are right now in this peak of inflated expectations whereas there's a lot of over promising it happened back in the days with Bitcoin where people were saying what it's going to replace in a year uh the normal currency it didn't like the US dollar is still the main currency the euro is still and yes that's a lot Bitcoin is growing and so on but it's far away from what they predict it to be and so after the peak of inflated

expectations you have the two of T illusionment that's when investors that invested in Devin AI or all those kind of companies that came out will lose money and finally people see where this do techn this technology actually fits in our productive cycle and then it gets added to our everyday life and that's the plateau of productivity we are right now still at the peak of inflated expectations and I think the US just announced an 500 billion investment that they with open AI right so things will still inflate inflate inflate and then we'll see what actually

from there what's actually useful that will just add more gasoline to the fire let's see where that takes us whenever we had a huge deregulation in place there was a recession like the big bubble coming afterward we'll see if that's that's the case now and finally the most important question for you the people watching us is what can you do as a soft engineer to prepare for this there's a bunch of things you can do number one use AI as much as you can add it to your workflow play with it of course use your

brain in the end do not you know do not put your fate or your G commits in fully 100% in the hands of curs or dein if you have access to that or CH GPD okay use it because again what you you fear what you don't understand the more you understand it the more you play with it the more comfortable you will be and the more you will see it for what it is the second point is think in first principles look behind what people say perception versus reality and you've seen right um and you've

seen this Tech CEO talking so much about Innovation and Ai and how aii will solve all the problems when in fact if you look at the people using the product you'll see they have an engineering problem they need more Engineers right so we need in this in this world where everybody saying this and that and even B and I we're telling you all these things but I do invite you to start thinking by yourself and start looking at things in first principles and build your own opinion yeah don't just follow the crowd because it's a

very confused word it's a very noisy world we live in the third point is if you feel underpaid most developers are you've seen the inflation data companies having increasing prices without any justification and they pocketed most of those money they have money even if they're trying to negotiate you on the phone do not listen to that right if your boss is telling you hey we cannot give you a promotion because times are tough it's not true they have the money okay so go there interview and get a better paying job if you feel underpaid most

developers are underpaid right now and of course for that you'll have to do some tech interviews and you will discover you do have some tinle gaps uh if you want to identify to find out those gaps and find out what would be the fastest way the most efficient way for you to fix them and check out the free tle assessment that bar and I put together in the comments