I have been writing about AI for quite a while now, but this is probably the first time I genuinely do not know what to think. Not because the technology has suddenly slowed down, but because the rules of the game may be changing.
I wanted to write something lighter today, but I feel like I have to share some thoughts from the last few days. It is getting harder and harder to ignore what is happening around the newest AI models. @pascal_cescato_692b7a8a20 post, 1%, only confirmed that I am not the only person wondering what comes next.
But let’s start from the beginning. Last Friday, well-known technology journalist Adrian Bridgwater asked me for a comment for this article: OpenAI GPT-5.6 Access Restricted. As someone who used to work in media, I know exactly what journalists hope for when they ask for a comment: a quick response, a short quote, and one strong punchline. 😅 But this time, the topic made me stop and think.
Four years that changed everything
In the last few years, the progress of AI has been incredible. We all know that. On November 30, 2022, OpenAI released ChatGPT, based on GPT-3.5, and generative AI suddenly became mainstream. It took only a few months, and by January 2023 ChatGPT had already reached around 100 million monthly users.
Even then, people were saying that AI would soon take jobs away from developers. And yet, from today’s perspective, less than four years later, GPT-3.5 almost feels dumb.
A year later, we were all laughing at vibe coders and contrasting them with REAL software engineers. But then coding agents arrived, and suddenly we all became vibe coders 😉 Okay, we all know that Claude Code or similar tools still will not replace a good developer today, and AI adoption inside companies often leaves a lot to be desired.
But this is still less than four years of LLMs being truly available on the market. What if, in another two or four years, agents really are good enough to write code much better than humans? Where is the limit of this technology?
Where do developers fit in?
I have to admit, I am a typical overthinker. I love analyzing the world and people, and thinking two hundred steps ahead. Of course, developers would still be needed in such a world, but would all of us be needed? Or would a company that used to need 500 engineers suddenly need five? Or just a small group of people training, supervising, and integrating models?
I am a solid senior engineer, and my market advantage is that apart from writing code, I can talk to people. And business desperately needs that. But I am not the kind of person who will lock herself in a basement for a month and dig deep into hardware internals to make LLMs run faster. I am also not someone who will happily spend 12 hours a day in silence working on benchmarks. I admire people like that, but that is definitely not me.
And I am not sure that if LLMs developed much further, my advantage of “being able to talk to business” would still be an advantage at all. So what should I do? Maybe slowly start looking toward developer advocacy, since that seems to be going well for me? Maybe send my CV to the nearby Biedronka discount store just in case — they are actually hiring, and I am there every day anyway, sometimes guiding people to products better than the staff 😆
Changes, changes...
But then something started to change. Tokens became much more expensive. Companies started realizing that maybe, for simple tasks, a junior developer might actually make more sense 😅 And seriously, I do not yet see a massive wave of hiring interns, but saving tokens, giving up certain tools, and saying “use a cheaper model for simple tasks” has become very common.
And now there is the embargo. First around Mythos and Fable, and now around GPT-5.6. If you missed it, the short version is that access to some of the most advanced AI models is no longer simply “available to everyone who can pay.” It is becoming restricted, limited by geography, organization type, security concerns, or strategic decisions. In practice, this means that not every developer, company, or country can count on equal access to the best models anymore.
I do not know what to think about this. Are these models really so dangerous for critical infrastructure?
Or maybe governments have simply started treating them as a strategic asset, similar to semiconductors? Maybe this is the end of the free AI market?
For developers, at first, it probably will not matter that much. Even if LLM progress stopped at the models we already have today, we would still improve the infrastructure, polish the agents, build better tooling, and continue working quite happily. Maybe for some time the models would even become more stable, with more reliable APIs and better developer experience.
But what happens next? Will working with powerful LLMs be reserved only for selected people? Or selected companies? Or selected countries?
On the other hand... these models are ridiculously expensive. Somebody has to pay for them. It is difficult for me to imagine companies investing billions only to keep their best models locked in a vault forever. They need customers. They need revenue. So maybe this whole "AI embargo" is only temporary? Or maybe governments will eventually step in and treat frontier AI the way they treat strategic infrastructure? Honestly, I have no idea.
So... what happens next?
Maybe it will be like Polish sci-fi writer Rafał Kosik predicted 20 years ago in his young adult series Felix, Net and Nika — AI will become unavailable to the public because it will be considered too dangerous, and models will be kept locked away? 😉 Of course, this is an extreme vision, but honestly, nothing surprises me anymore.
Just a year or two ago, we were asking whether AI would replace developers. Today I find myself wondering about something slightly different: will the most powerful AI even remain available to ordinary people?
What do you think? Where is all of this going? I do not want to pretend to be an all-knowing sheriff here, and I am genuinely curious about your perspective.
Also, I will not publish anything next week because I am going on vacation — like every self-respecting Polish person, to Croatia. This is just a note for those of you who read my posts every Sunday around lunchtime 😆
And if you are from Czechia or somewhere nearby, come to *FrontKon*, where I will be speaking. Let’s high-five there!
Or, if you like, please follow me on LinkedIn.
Top comments (254)
Sylwia, the access question lands differently depending on where you're starting from. from Nigeria, equal access to frontier models was never the baseline — every API call already crosses an ocean, costs latency that developers in Virginia don't pay and depends on infrastructure that runs on diesel generators because the grid gives 4 hours a day.
The Fable shutdown was a disruption for developers who had it. for developers who were already working around geography and cost, it was confirmation of something already true: the intelligence available to you has never been just a function of what you can pay. it's always been a function of where you are.
what changes now is that developers in Poland and the US are starting to feel what developers in Lagos have always felt. that's not a silver lining. it's just the same map, newly legible.
Daniel, thank you so much for this perspective. I really appreciate you sharing it.
Sitting here in Europe, it's easy to forget that geography itself is a privilege. We often take for granted that we have relatively stable infrastructure and broad access to the latest models.
Interestingly, the discussion in Europe has recently shifted in a different direction. Many people are worried that Europe is becoming increasingly dependent on the US for AI, and that if we fail to keep up with innovation, we'll end up in a much weaker position ourselves.
Your comment is a good reminder that access has never been distributed equally in the first place.
But you don't even need to look outside Europe. Geography isn't the only barrier, money is another one. Not everyone can afford to pay for a subscription to some AI company, and, in a way, this means "skill" is now behind a paywall.
That's a very good point, and unfortunately it's easy to forget.
I think I fell into the illusion that if even I, living in a post-communist country, can afford a Pro subscription (not every model and not every top tier, of course, but still), then it probably isn't such a big barrier.
But you're absolutely right. Compared to a large part of the world, I'm actually in a very privileged position. Thanks for pointing that out!
Wii, "skill is now behind a paywall" is the line. the geography barrier and the money barrier are the same barrier wearing different clothes . both determine what tools you can access, and the tools increasingly determine what you can build.
what makes it harder to argue against is that the paywall is gradual. free tiers exist. the gap only becomes visible when you hit the ceiling — context limits, rate limits, model access and realize the developers building without those ceilings are compounding faster. the advantage isn't access. it's the absence of friction over time.
Exactly! Do you ever get the feeling it used to be different?
For example, IDEs usually had a generous Community Edition. You only really had to pay once you were building commercial products and making money from them.
With LLMs, it's different. The free tier can disappear at any moment. You never quite know when you'll hit the token limit, the context limit, or lose access to a particular model. That uncertainty itself becomes friction, and over time it adds up.
Sylwia, yes and the IDE comparison names exactly what changed. the Community Edition model assumed you'd grow into paying. The tool was yours to learn with and the business model waited for you to succeed before asking for money.
LLM free tiers assume the opposite. the value is front-loaded, the limits are opaque, and the uncertainty is structural not a bug but a feature. keeping you unsure of when you'll hit the ceiling keeps you subscribed.
The friction compounds differently depending on where you are. in Lagos, it's not just token limits. it's not knowing whether the model will be available at all next week. the Fable shutdown was a reminder that access isn't just a pricing question. it's a policy question. and policy can change overnight without asking you first...
Exactly. Take something like Claude Code on the free tier. You get just enough prompts to see how incredibly useful it is and how much faster you can work with it. Then you hit the limit.
If you can't afford the subscription, you immediately realize you're falling behind people who can use it all day.
At that point, the real hope is that cheaper, "good enough" models—or even local models—keep improving. Because realistically, what else can we do?
Sylwia, local models are already part of the answer and the Africa DeepTech Challenge running this year is specifically building around that gap. The whole premise is: what can you build that runs on 8GB of RAM with no cloud dependency, no subscription, no API key that disappears overnight?
The free tier problem you're describing is exactly what that constraint produces as a design target. not "good enough" as a compromise — genuinely optimized for the environment where the subscription isn't an option.
The honest answer to "what else can we do" is: build for the constraint instead of around it. that's slower and harder than just affording the subscription. but it produces something the subscription model never will — a tool that keeps working when the free tier ends, the policy changes, or the model gets pulled.
I really like that way of thinking. As a software engineering strategy, I think it's an excellent shift.
My only question is what happens if some truly groundbreaking discoveries—say in physics, medicine, or other scientific fields—are only possible with frontier models.
In that case, building for the constraint is the right engineering approach, but it still doesn't solve the problem of unequal access to the very frontier of AI capabilities. That's the part I keep wondering about. 🤔
Sylwia, that's the distinction worth sitting with. building for the constraint solves the productivity problem. it doesn't solve the discovery problem.
and the discovery problem is where the gap compounds in ways that are hard to reverse. if the next breakthrough in protein folding or materials science requires Mythos-level reasoning and Mythos is available only to vetted US agencies and certain allied institutions — the constraint isn't just inconvenient. it shapes which problems get solved, by whom, and whose reality gets modeled in the solution.
the someone-else-pays piece I'm finishing this week is partly about this. not the science angle specifically, but the same structural point: when access is tiered by geography and policy, the frontier doesn't just move faster for some people. it moves in directions shaped by who's at it.
building for the constraint is still the right engineering answer. but you're right that it's not the whole answer.
Not to get too revolutionary here, but we should always remember that companies "owning" models or data centers is just a social construct.
We don't just let companies build nuclear weaponry either, so if AI becomes too powerful for the status quo, societies totally can just decide to put that critical infrastructure under democratic control.
Exactly. In the past, access to knowledge was never perfectly equal, but over time it generally became more accessible. Then the internet came along and democratized knowledge even further.
My concern is that AI could reverse part of that trend. If the most powerful tools are available only to a small group of people or countries, then we're no longer just talking about unequal access to technology—we're talking about unequal access to discovery itself.
That would be a very different world from the one we've been moving toward for the last few decades.
@darkwiiplayer That's an interesting point, although I'm not entirely convinced.
One important difference is that today's frontier models were largely created by private companies investing enormous amounts of their own money and research. Nuclear weapons, on the other hand, were developed as government projects from the beginning.
So I'm not sure the comparison maps perfectly. That said, if AI becomes strategically important enough, I wouldn't be surprised if governments became much more involved than they are today.
No, today's frontier models were created by private companies committing one crime after another, DDoSing wikipedia along with countless privately hosted websites, plagiarising every line of code ever published regardless of license and committing the most blatant financial fraud the world has seen so far.
And yes, the comparison does map perfectly, because it's not about who invented it, it's about who can control it. If the first atomic bomb was made by a private company (which wouldn't have been allowed in the first place, so there's that already), governments still wouldn't allow any private entity to own it.
Just think about it. Why can't I just order a Nuke on amazon right now? Is it a matter of intellectual property, or a matter of what I could do with it? Yea, it's not an IP problem.
And I think "strategic" importance is only one reason to get involved; the fact that it's becoming an essential aspect of society is just as good a reason.
Let's be real; no AI company has any moral right to control their products; if anything, they've more than earned being dissolved for their bad behaviour. At this point the one and only argument for allowing them to exist is that they're somehow still of use to society. I don't think they are, but most people still seem to think so. If that changed, there'd be zero reason not to take back what they stole and consider their work on top of it as interest and damages.
I disagree with two points.
First, I don't think the comparison with nuclear weapons really works. A nuclear bomb has one primary purpose: to kill. That's why you can't buy one. AI has countless legitimate uses in science, medicine, education, engineering, and many other fields. To me, it's much closer to asking, "Can I buy a supercomputer on Amazon?" The answer is yes—if you have enough money.
Second, regarding AI companies stealing data. If it's wrong when private companies steal, does it somehow become acceptable when the state steals? I don't think using the word "government" automatically makes stealing morally different.
I don't think governments should steal data, my point is that these AI companies didn't earn their achievements with honest work, but through crime. Taking away their control over their models is more like taking away stolen goods from a thief than, say, taking windows away from microsoft. At best it's somewhere in between those two leaning more towards the stolen goods.
That being said, if governments were to steal data as AI companies do, there'd be a few differences that still make that less bad:
¹ same difference as spending tax money on, say, a park that anyone can use vs. constructing an office building as a gift to a bank; the government takes your money anyway, but what's being done with it matters.
Personally, I don't mind if some AI, say, scrapes my blog and uses the text as input to train a new model. Not in principle.
What bothers me, and what I would never consent to, is that my intellectual property, bad as it may be, gets fed into such a system and the result is then owned by some third party. Same mentality as a copyleft license. If I give content to humanity, I don't want someone to repackage it and sell the product; if they want to use what I give away for free, they should also give away their work for free. Otherwise, name a price (and I'll say I'm not selling).
Regarding nuclear bombs, I do see your point about purpose, but I don't think it invalidates the example. There's many other cases where technologies have a potential for harm, so they're strictly regulated even when used "for good", and would quickly be taken away from companies who handled them with the carelessness of AI companies.
Imagine operating a nuclear power plant with the same approach to possible damage being done as the companies carelessly scraping over wikipedia's images, even the ones not in cache, hammering their storage infrastructure and iirc. being responsible for somewhere around 30% of their infrastructure costs a year or so ago. We'd never let that company handle radioactive material like that, even if they intend to use it for power generation.
Out of curiosity, which country are you from?
Maybe it's because I live in Poland, but I'm not nearly as confident that governments would necessarily manage this any better. Watching one government after another over the years has made me rather skeptical about handing them even more power.
Germany. We're neighbours 🇩🇪🍻🇵🇱
That explains a lot! 😄 Poland is already a fairly wealthy country, but unfortunately we still often have a very communist mindset among those in power.
I wouldn't call that a "communist mindset" though. A communist mindset is giving according to your means and taking according to your needs, even if you end up getting less than you contribute.
I think what you mean is really just an openness to corruption, and that's just as much of a problem if not more in much of the west right now, with AI companies often just getting away with whatever they want if they ask nicely, while the people who are affected don't really get a say.
That's fair. 😄 What I meant was "post-communist" in the Central and Eastern European sense, not communism in the Marx/Engels sense.
Here in Poland, when people say "communist mentality," they're usually referring to the legacy of the Warsaw Pact era, which in practice had very little to do with the original communist ideals.
A wild @sylwia-lask has been spotted in "The Daily Context" for the AI Engineer World Fair!
Interesting read! :D
Wow!!! 🤯 Thank you so much for the screen, Francis! How cool is that! ❤️❤️
Sylwia, your Biedronka backup plan is solid. I hear the pay is decent and the product knowledge requirement matches yours already.
Jokes aside — this is the piece I couldn't write. You're inside it, I was watching from 2029. The "where do I fit" question is the one that actually keeps people up at night, and you're one of the few who'll say it out loud without dressing it up.
The 403 on a Monday morning is abstract geopolitics made very, very concrete.
Enjoy Croatia. The embargo will still be there when you get back. So will I, apparently — glad someone noticed. 🙂
Haha, exactly! 😄 From what I've heard, Biedronka has pretty decent benefits too—private healthcare, holiday vouchers... and it is really close to my home, feels almost like remote job 🤣. Sounds like a solid backup plan. 😄
As for the article, I completely agree. None of us really knows how this is going to unfold. We can try to predict the technology, but we're just as likely to be surprised by political decisions as by the models themselves. That's probably the biggest lesson from the last few weeks.
That's the sentence of the week. The technology was always the easier variable.
And honestly, Biedronka private healthcare sounds better than most startup equity packages right now. Keep that CV warm. 😄
Hahaha, exactly! 😂 I've got a nice collection of vested startup equity from different companies... and somehow I'm still not a millionaire. 😄
What comes next? This part:
That quote is becoming suspiciously relevant these days. 😅
Btw, I absolutely love Dune. 🙂
Restrictions are never a good sign, but I’m not sure if I really miss these new generation models right now, like Fable or Mythos. For me, the main issue is the price. If they cost roughly twice as much as Opus, for example, you need a really good business model to justify using them.
GPT-5.6 hurts more, because it looks much more attractive from a price/performance point of view. But honestly, the reasoning models we already have are still not bad.
So from the point of view of a regular dev in Europe, maybe not much changes. Globally, though, that is a different story. I’m curious to see where this goes.
P.S. I like Biedronka, that’s a good backup plan. 😆 And yes, Croatia is the best, but I heard prices went up a lot, so this year we decided to switch to Italy. 😅 (Typical Eastern European holiday-planning conversation. 🤣 )
Exactly! GPT is still incredibly attractive from a price/performance perspective.
One pro tip, though: apply for the AWS Community Builders program in January. You already write great articles, so I think you'd have a very good chance of getting accepted (you even don't have to write about AWS staff). They give you $500 in AWS credits every year, and you can use those credits for Kiro. 😄 I genuinely recommend it, it's a great program for people like us.
As for Italy vs. Croatia... 🤣 Just an hour ago a colleague at work joked that Croatia used to be the cheaper alternative to Italy, and now it's the premium alternative to Italy. 😅
We're heading to the Makarska Riviera, though. Two years ago it was still reasonably affordable because it's a bit too far for many German tourists to drive. 😄 I'll let you know whether the low prices survived this year!
Oh, thank you for the tip! I will definitely apply for it.
Makarska is great. We went there multiple times, but a few years ago we found an amazing place on Krk Island, and since then we’ve kept going back there. And yes, I definitely want to hear about the price changes. At least I’ll know what my wallet should prepare for next year. 😅😆
Oh yes, Krk is beautiful too! 😄 I love the Makarska Riviera because you get both the sea and the mountains.
The last time we stayed in Gradac, I even hiked to the top of Sv. Ilija. The funniest part? I did the entire hike alone and didn't meet a single person on the trail. 😂
How is that even possible? Could it be that people were discouraged by that tiny inconvenience of... 35°C in the shade? 🤣
I bet that solo hike must have been amazing, but 35°C in the shade? That sounds less like hiking and more like a survival challenge to me. 🤣🤣
i think this will help - dev.to/aws-builders/how-to-become-...
Thank you so much! That's a great article. 😄 In my opinion @gramli would be a perfect fit for the program.
And the program itself is fantastic. Sometimes I wish I had a second life just to attend all the webinars, events, and community activities. There are simply too many great things happening. 😂
Thanks for the kind words, Sylwia! ❤️ To be honest, I didn’t even know that something like the AWS Community Builders program existed until you mentioned it and it looks great! 😄
And @sarvar_04, thank you for the link. Great article!
Looks like the DEV.to community works exactly as it should, amazing!
Thanks @gramli 👍🏻
Haha, same here! 😄 I didn't know the program existed either. I actually found out about it here on DEV too. That's one of the things I love most about this community, you always end up discovering something useful. ❤️
I don't think this is unique to AI — explosive growth followed by a slowdown is the default tech pattern, not the exception. We've seen versions of this story before, from early computing through to today's AI agents.
Semiconductors are the clearest parallel. Moore's Law — transistor counts roughly doubling every two years — held up remarkably well for decades but has slowed significantly since the mid-2000s. That wasn't about running out of room on the chip; it came down to physics — the breakdown of Dennard scaling (essentially, power density and heat) and eventually quantum tunneling effects as transistors shrank further. The industry didn't stop innovating, it just changed strategy — multicore, chiplets, 3D stacking — instead of relying on pure density scaling. I'd expect AI to eventually follow a similar arc: rapid gains, then a plateau as we hit compute or data limits, with progress continuing through smarter architecture rather than raw scale.
Though I'll admit a brand-new model getting capability-restricted by a government this week is a strange data point for the "it's already saturating" theory — feels like we're still on the steep part of the curve.
On the embargo: I think you're onto something. Governments don't restrict technology they see as harmless or low-stakes. Treating frontier AI like a strategic asset, the way semiconductors get export controls, suggests both a real security concern and real economic competition underneath, even if security is the official line.
That's exactly what I've been wondering too. I'm really curious about when this technology will stop scaling the way it has over the last few years.
But even more than that, I'm curious where we'll end up when it does. What will the world look like at that point? Not just software engineering, but science, medicine, education... pretty much everything. That's the question I keep coming back to. 🙂
I feel the same way. Beyond software, I often wonder what people across all industries will be doing in the future. If human labor is no longer essential, what gives currency its value, and how will society redefine purpose and contribution?
We'll see! 😄 After the Industrial Revolution, people were supposed to work less too... and somehow that never really happened.
Humans seem to be incredibly creative when it comes to inventing new kinds of work for themselves. 😂
Intriguing article, interesting views!
I'm actually surprised that this US government seems to be starting to regulate AI - doesn't that run counter to what they stood for, which was "no regulation of AI", total freedom and "cowboy style" all the way? I really thought they rejected the idea of regulating AI, seeing it as an "EU thing" ...
Or are they trying to limit access to US residents only, is that the point? (but Anthropic already said that that's not doable, so they shut off access to Mythos etc completely)
But to be honest I'm not sure that slowing down the whole AI craze a bit is such a bad thing ;-)
That's exactly what surprised me too! 😄 They usually present themselves as very pro-free market and against regulation, and then suddenly we see restrictions like these (even if they're officially explained as national security measures).
And yes, maybe slowing things down a little wouldn't be the worst outcome. 😄 Right now it feels like if you disappeared into the jungle for six months, by the time you came back the entire AI stack would have changed anyway. 🤣
My thoughts as well ... let's not go crazy and just wait & see, it's not the end of the world either way!
Hahaha, but what if we end up with Skynet... or the Matrix? 🤣
Ah, if people got paid for overthinking, I'd be a millionaire by now and wouldn't have to spend my days cleaning up code after junior developers. 😂
Might actually be a strength, the overthinking thing? The best philosophers and scientist were/are probably prone to overthinking things, lol ... maybe I should overthink a bit more as well !
Haha, give it a try! 😄
But seriously, it can be both a gift and a curse. That's actually one of the reasons I write this blog and keep a few side projects going. I don't care about "personal brand" (WTF even is it), but they give my brain something useful to chew on.
Otherwise... things get dangerous. 🤣 I start overthinking the most ridiculous scenarios, usually involving people and relationships.
It's like having a sheepdog. If it gets to work all day, it's calm and happy. If it doesn't... it starts chewing the couch. My brain works pretty much the same way. 😂
Haha, yeah everyone's "wired" differently :-)
I think we're asking the wrong question. The biggest shift may not be whether AI replaces developers, but whether access to frontier AI becomes concentrated in the hands of a few organizations and governments.
History suggests that when a technology becomes strategically important, openness gives way to control. Semiconductors, nuclear technology, and even GPS followed similar patterns. If frontier models become restricted, the next wave of innovation may come from open source and smaller, specialized models rather than the biggest proprietary ones.
The future may be less about who builds the smartest model and more about who gets to use it.
This is an incredibly sharp perspective, and your historical comparisons to semiconductors and GPS are spot on.
The current climate strongly reminds me of the "computers are taking our jobs" panic of the 1970s and early 80s. Back then, computing power was also entirely concentrated in the hands of a few massive corporations and government institutions during the mainframe era. The anxiety about automation replacing the workforce was very real. However, instead of a complete corporate lockout, we eventually saw a massive shift toward decentralization driven by the personal computing revolution and open ecosystems.
We are living through a similar architectural shift right now, and honestly, the sheer scale of it is a lot to process. It is incredibly hard to predict exactly how the balance of power will settle between gated, proprietary frontier models and agile, open-source alternatives.
You are likely right that the defining bottleneck of this decade won't just be about who can build the absolute smartest model, but rather ensuring the ecosystem remains open enough that the next wave of innovation isn't locked behind a handful of corporate gatekeepers. Great post!
Thank you so much! I really like the comparison with the early days of computing.
And yes, that's exactly my concern. If AI innovation ends up concentrated in the hands of just a few corporations, we're in trouble. Competition, open ecosystems, and broad access have always been huge drivers of innovation. I'd really hate to see us lose that.
I don't doubt that for a second. I'm convinced we'll see an incredible amount of innovation around smaller and open-source models.
My concern is exactly what happens if frontier models become increasingly restricted. If the biggest breakthroughs are only available to a handful of companies or governments, then we may end up with a two-speed AI ecosystem. That's the part that worries me the most.
Like other pieces you've written, this is a fun read once again!
As a senior dev who also has to handle the business side of communication, i still find myself looking at this purely through a technical lens. it's wild seeing the narrative shift from " AI replacing us " to these weird global access restrictions.
Honestly, i'm just waiting for the current AI bubble to burst so we can finally see what the actual sustainable next step looks like, because right i genuinely have no idea where is this gonna go.
Anyway, enjoy Croatia! The embargo and the hype will definitely still be waiting for you when you get back. 😎
Exactly! 😂 A few weeks ago I was joking that AI would soon be running the world and replacing politicians... and then geopolitics stepped in and reminded us who's still in charge. 😄
Thanks! I'll definitely enjoy Croatia. Let's see whether another embargo drops while I'm away. At this point, I wouldn't even be surprised anymore. 😅
finally see* damn it, i just found the mistake today haha
hahaha I didn't notice it either 😅
The next phase will belong to people across every industry who are willing to embrace AI. They will build AI tools on their own, replacing those who cannot use AI. In this process, programmers will matter less and less.
A recent post in China went viral: an HR professional used SoloEngine to build a recruiting Agent in three minutes, screened out six candidates from 310 resumes in thirty minutes, and racked up 300,000 views in a single day. What makes it interesting is that the same company had previously spent 2.75 million yuan on an end-to-end AI office system developed by a professional team. They pushed it hard for six months, only to end in chaos and abandonment. The difficulty of implementing AI in enterprises is not about technology at all; it is about people. When leaders make decisions, they are chasing the AI trend; programmers understand code but not the business, and much of the business knowledge cannot even be articulated, so no one in between translates real business needs clearly. The future of AI development is destined to be about neither throwing money at code nor letting coders own the process; it is about letting people who truly understand the business build AI tools tailored to their own industry and job. The final outcome will be that people who can use AI replace those who cannot use AI.
That's an interesting example, but I'm not completely convinced by it.
Building a working application quickly has never really been the hard part. We were doing impressive things at hackathons long before LLMs came along. AI simply makes that part even faster.
The real challenge has always come afterward: getting people to use it, scaling it, maintaining it, integrating it with existing systems, and making it create real business value.
That's where I think software engineering is still very much alive. 🙂
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