But the point about the multi-finger fingers -xD- was not about transitional technology, but about explicitly avoiding direct brain connection as an additional layer of security.
A recent (2023) finding: from Guillaume Singelin, Frontier [0]. Fitting it into "cyberpunk" may need a bit of a push, but since the limits are kind of blurry I don't really care. The narrative is not perfect perhaps falling into wanting to say a lot more than the page limit allows, but all in all it's a good enough read.
I'm vouching for Frontier as well, as well as "Carbon & Silicon" [0] from Mathieu Bablet. All of his work is gorgeous, I love his art.
If you liked Frontier's theme and are into video games I recommend you check out "Citizen Sleeper" [1] illustrated by Guillaume Singelin as well.
It's a 7 hour narrative text-based adventure that really hooked me one week-end. Your choices depend on how you "spend" your dice, dice that are cast at the beginning of every single day on the station so you get to pre-plan your actions somewhat.
Gameplay wise it's mostly reading, but I liked exploring the station they created.
I've had quite a few conversations and read many thoughts on the subject of job security in the software industry through the years. New technologies, various crisis and crashes, just age, incoming "hordes" of less prepared developers, or whatever.
If I had to highlight the one thing all those conversations had in common it would be precisely this:
I thought that having this knowledge would set me apart
I think in the future, those who succeed will be equivalent to wayfinders.
People who _can_ see the wood for the trees, and are able to understand multiple (sometimes conflicting) requirements and work out a way through that solves the problems that arise, for all involved parties.
An understanding of domain, the ability to communicate effectively and a mind that can think laterally, will all be vital.
Past, Present, and Future. If you control the means of production you win. Knowledge, skill, and experience are largely irrelevant to the conversation. I’ve held this opinion for quite some time and would be interested to hear alternative perspectives.
That's clearly wrong, because capital doesn't just appear out of thin air. You are ignoring that there's clearly rare skills involved that enable a few to become very successful. Your strawman only applies to the second generation that inherits wealth, and case in point inherited wealth tends to disappear in a couple of generations further proving that skill is required to build and maintain wealth.
> Past, Present, and Future. If you control the means of production you win.
Yeah, but we were talking about only success, not winning.
In the past and the present, you could succeed purely on a combination of skill, talent and labour. This approach looks like it will not work much longer.
We exchange our knowledge, time, and skill for money. If this exchange is no longer viable — because similar value can be accessed via LLM agents — we'll have no way of making money.
I do think some (non-billionaire) people will survive the transition, but the question then becomes: what happens to everyone else?
I don't think history bears this out. If you look at the most successful entrepreneurs of the computer age, none of them started out as owners of capital. Bill Gates, Jeff Bezos, Steve Jobs: yes, they had some level of privilege and opportunity, but they didn't start out as billionaires. Their success came from their ideas.
Gates famously came from a rich family, but Bezos did too - he used hundreds of thousands of dollars in investments from his immediate family members to get Amazon off the ground. Maybe 1 to 2% of Americans would be able draw that much from their family members if they were to launch a startup. If we define "bootstrapped" wealth as starting from an economic background within one standard deviation of the national average, then he doesn't count.
If the labor -> wealth pipeline is weakening, then the present won't behave like the past, i.e. you would need assets to success since you won't be able to work your way up.
By completely eliminating the need for a human workforce, therefore rendering a majority of humanity obsolete, therefore lots of social inequality, therefore lots of starvation, poverty and death.
When billionaires say "think about the trillions of people that will benefit from AI" and some notion of living in a post scarcity world, they are talking about _their_ descendants, not yours.
> If we're all broke/starving/being exterminated, who will the rich sell to?
Themselves. The economy is a big cycle where money changes hands to drive production i.e. things getting made. AI will simultaneously greatly increase production (especially once humanoid robots are as dexterous as humans) and make the humans whose jobs it will do economically irrelevant.
So the rich will buy and sell very nice things to each other while the rest of us get left out in the cold because we simply cannot compete with the robots. And because they will capture and control all resources (either by law or by force) we won't be able to create a functioning parallel economy either.
> So the rich will buy and sell very nice things to each other while the rest of us get left out in the cold because we simply cannot compete with the robots. And because they will capture and control all resources (either by law or by force) we won't be able to create a functioning parallel economy either.
Here's another framing for you: at this point _there are no longer rich and poor people_. There are fewer people, but we knew that was going to happen as a consequence of declining birthrates. The elderly are taken care of despite an otherwise unsustainable dependency ratio, because robots can manage the actual business of survival. In that world everyone is a member of the nobility by the virtue of being _human_. There are a few holdouts - mostly religious nuts and other cults - but by and large everyone who is willing to accept the machine's gifts has their every material need catered to.
There is no world where legions of filthy rich AI barons lord it over the technologically illiterate peasants, though. How could there be, when literally anyone can plop down $20 and get access to a frontier model? When open weight models trail _at most_ a year behind the closed ones and compute continues to proliferate?
One of the few things we have figured out about AI is that productivity gains are mostly captured by the people using the tools, not the person paying for the model. In other words, using an LLM is a skill and there is still no substitute for the human driving it.
it's so nice watching HN derive fundamental human rights and basic theories of marxism for themselves.
except no, that's probably not whats going to happen, unless you want to explain to me why there have been voices calling for gruesome stuff to happen to the unproductive for the past 20 years ;)
> In 2008, a software developer in San Francisco named Curtis Yarvin, writing under a pseudonym, proposed a horrific solution for people he deemed "not productive": "convert them into biodiesel, which can help power the Muni buses."
> How could there be, when literally anyone can plop down $20 and get access to a frontier model?
For now. And that too at a massively discounted rate to drive adoption.
> When open weight models trail _at most_ a year behind the closed ones and compute continues to proliferate?
Open-weight models require computing power to run. Consumer hardware prices are rising because of AI build-out, so much so that companies that used to serve ordinary consumer markets are switching to serve only datacenters. Megacompute does indeed continue to proliferate.
> One of the few things we have figured out about AI is that productivity gains are mostly captured by the people using the tools, not the person paying for the model. In other words, using an LLM is a skill and there is still no substitute for the human driving it.
Will this be the case in 20 years? Agentic workflows have come as far as they have in about two years of existence. Do you really need the problem between chair and keyboard will be needed after another 10? And do you really think that in 20 years time that we will all be paid to prompt increasingly advanced and independent LLMs?
> everyone who is willing to accept the machine's gifts has their every material need catered to
The way automation is going, knowledge work will be automated first before any physical production processes are. A lot of people will lose their livelihoods before goods in particular become "the machine's gifts". What do you think happens then? Will the capital owners who have captured this reduction in costs reduce prices proportionally? Or will they keep the gains for themselves? Do you think governments around the world will tax the upper class to the point of being able to give everyone their current livelihoods through government benefits?
You are pretty much just describing some sort of fantasy automated communism. Not to mention, in your world, gatekeeping the machines would instantly become the most profitable venture possible.
> Not to mention, in your world, gatekeeping the machines would instantly become the most profitable venture possible.
Yes, it would! That's why frontier labs don't open-source their models :)
The point is that the technology is already too democratized for anyone to hold onto it. Google had chatbot LLMs in 2019 and tried to keep them under wraps, how many years did that buy them?
> Do you really need the problem between chair and keyboard will be needed after another 10? And do you really think that in 20 years time that we will all be paid to prompt increasingly advanced and independent LLMs?
I think that things are going to get so much cheaper that we'll still be paid more than enough.
> The way automation is going, knowledge work will be automated first before any physical production processes are.
So far, LLMs are great and all, but they only really "fill in the blanks." That's a fundamental limitation of the entire concept of modelling in general; you cannot generalize to out-of-distribution inputs. The bottleneck is going to end up being human beings no matter which way you slice it. Because the bottleneck will be people, more and more of them will be hired, even though each individual is incredibly productive. This is also called Jevon's paradox, when making a resource less expensive leads to overall market growing.
> You are pretty much just describing some sort of fantasy automated communism.
If you went back a thousand years ago and told someone carrying a bucket full of water that one day pipes would run across the civilized world and water would literally be free basically everywhere, they might react the same way. If VLA-driven robots start reducing manufacturing prices, is it so unreasonable to slowly expect more and more things to go that direction?
> The point is that the technology is already too democratized for anyone to hold onto it. Google had chatbot LLMs in 2019 and tried to keep them under wraps, how many years did that buy them?
They were hardly the only ones in the space. OpenAI has been around since 2015. GPT-3 was released in 2020 and ChatGPT in 2022. Not to mention, I wouldn't call something produced by a handful of megacorporations worldwide particularly democratized. In fact, Google's transparency is what allowed it to be democratized, because it published its findings about transformers publicly.
> So far, LLMs are great and all, but they only really "fill in the blanks." That's a fundamental limitation of the entire concept of modelling in general; you cannot generalize to out-of-distribution inputs. The bottleneck is going to end up being human beings no matter which way you slice it.
This is a laughably naïve take especially when LLMs have a) been trained on quite literally all the data the world can provide and b) are being trained more and more using reinforcement learning techniques - which don't rely on data at all and instead on producing emergent behaviour from a set of ground rules. With every new release their agentic capabilities improve and they become more independent, requiring only the impetus to get going.
> This is also called the Jevons paradox, when making a resource less expensive leads to overall market growing.
Oh yes, there will definitely be more software. That is guaranteed. What is not guaranteed is how many humans will be involved in making it. Just as more coal is being mined than ever but fewer people are involved in it. Efficiencies in coal mining aren't what made the average coal miner's working conditions or income better, regulations are.
> If you went back a thousand years ago and told someone carrying a bucket full of water that one day pipes would run across the civilized world and water would literally be free basically everywhere
If you told a Roman this, they would not be as surprised as you would think as aqueducts already existed back then. They would be more surprised that the common man had the ability to vote in most countries. I doubt it will stay that way with improvements in AI, at least not without a great reduction in population.
you should have read marx, owning the means of production is a fundamental requirement for communism, rendering currency obsolete. one thing that's usually left out though, is that the means of production also have to be so stupidly easy to use, that any ordinary human can make use of them.
it's just not going to be you or me who is going to be within that group of ordinary humans.
It's hardly speculative when it is effectively what happened just after the Industrial Revolution, but with more power ceded to capital. In many ways, it's already happening.
No, that was not "effectively what happened" in the Industrial Revolution. That was an enormous change, but it didn't "completely eliminate the need for a human workforce." That's just hype.
Fine, it is not effectively what happened then. It is worse. At least workers are required to run factories (even though working conditions were ridiculously horrible back then). With AI, in maybe 20 years, 95% of all white-collar workers will be economically irrelevant. You won't need accountants, or programmers, or designers. And we can't all become lawyers and surgeons, or tradesmen.
The Industrial Revolution indeed did not completely eliminate the need for a human workforce. The AI Revolution will.
measuring programmer productivity is notoriously difficult. Does james, who shipped 20 features without testing thoroughly provide more value? or does joe, who patched a security hole in that time and avoided disaster? what about jason, who facilitated communication between them, and kept the infra going so their changes could go into prod without issues?
This also was true for teams, and indeed, businesses. It's not a property of the code itself, its a property of products and outcomes. I don't think AI agents doing the day to day changes will affect this directly (but people may have more time to think about these higher level problems, and increased volume of changes may make the issue more important)
I suppose, my best guess is that a team will be reduced to one or two people; the those that are left will be judged solely on outcomes.
Two (human) brains are always useful; the benefit of a human in these scenarios is that we can be accountable, and that we have a very real incentive to do well and not be fired. The LLM obviously doesn't care in that regard!
How do you do that in practice though? You won't know the engineer is a con-man until after you have spent $$ and months into the process. Then you are in the position of trusting nobody.
Could you please stop posting unsubstantive comments and flamebait? You've unfortunately been doing it repeatedly. It's not what this site is for, and destroys what it is for.
"Oh, we'll just ship production to China, and do the design and marketing in US, this is where the real value is anyway, China will never be able to do design and marketing as well as we do".
Literally same thing:
"Oh, we'll just let LLMs code, and we'll just do Taste. LLMs will never be able to do Taste"
does it never? seems to me that people pay me precisely for my knowledge, learned over many years. The knowledge translates into action, sure. But thats like the old parable about a plumber being paid €150 for a 5 minute consult that involves turning a single screw. "i could have turned that screw!" the customer cries, ignoring that yes, they could have. But they didn't know to.
I think perhaps the problem is instead "I thought that having this knowledge would set me apart, forever, without me having to learn anything else"
right. Apprentices will always grow, and so too must you, if you want to keep being paid. Their job is to come with new tools and new ideas, and your job is to keep a wider view into what you're doing and why, maintaining trust (you need to build the authority to tell apprentices no when their ideas might flood the customer's house), and keep moving towards other parts of the business and solving harder problems (working with sales, hiring, etc to manage customers and apprentices). AI will not build authority for you.
If your argument is that the customer themselves could use an AI or whatever to learn plumbing, that was always an option (libraries, google, youtube). They pay you so they don't have to worry about flooding their house (or at least have someone else to blame).
They might be able to "one shot" simple fixes that you might previously have assigned to an apprentice, but believe me, AIs are not about to start doing complex things for the layman that actually required seniors previously in either programming or plumbing, because very few of those things were just "type better into a computer". (build trust, speak confidently, know what doesn't work, take responsibility, test without breaking systems, communicate and work together with other professionals, have opinions)
I agree that it is easier than ever to start doing stuff, instead of reading. I don't think that means its easier to jump right to doing large projects. The problems to be solved there are often subtler, of a different class, and manifold, and a layman may not realise what has gone wrong until long afterwards or never (this also happened before, many people took on projects they weren't ready for and reinvented the wheel trying to solve issues they ran into)
it's oft debated, but I do fall on the side of "you should still know maths even in the age of the calculator/matlab/llms". I have found productive employment, and indeed tickets to speak to the big boys in their gilded palaces many times because graphs and charts are their favorite toys and knowing maths got me there. They have always been able to make things with excel, with matlab etc. Often they actually can make charts themselves, but they don't care to become experts in what data is important and what isn't.
The LLM isn't yet good enough to tell you what data matters. People act like LLMs are magical gods that do everything, but it is but another tool. It has limitations, just as it has strengths. It is not ultimately convincing, it is not infallible, and experts will keep finding edge cases all the damn time. Anyone working with them every day knows this, and you need to know it too.
I think a more sane minded customer would not mind paying for the assurance and having someone to blame in case things go wrong, not necessarily because of their domain knowledge.
I could theoretically learn everything about plumbing but would still rather call a professional for the peace of mind that it was done "correctly" and it the process goes wrong, I would have an instant fix instead of trying to go back and educating myself on plumbing more.
Could you consider that as part of knowledge? Yeah and also no. Because the knowledge can be copied and put into a LLM but legally a LLM cannot sign off on things like NDAs or take accountability like a human has to in these roles.
I agree. I also think that deciding that LLMs encode all knowledge perfectly, either now or in an imagined future, is foolish. My experience is that they match the average general state of experts among the field. The sort of thing a junior might read to start to grasp the general ideas and issues in a field. They rarely have opinions, or good intuitions around more specific scenarios. This is why the current equilibrium of a senior piloting one works so well- theyre leaning on it to speed up, but pushing it away from the "average" where circumstances demand.
We can argue about imagined future progress, but I don't see that getting much better, given that the literature doesn't often do that, and how often experts in one scenario end up being poorly suited given another set of facts.
Knowledge depreciates, so it is clarifying to add time explicitly: I thought this knowledge would set me apart...
Forever? That seems over-optimistic for all occupations in all eras.
For the rest of my working career? This really hasn't been true in a long time either, especially in software, where technology changes on the order of years.
For the duration of my mortgage? The fondest hope, but pretty much like the above.
For the next 10 years? Here is the big change. Even for fields like medicine, where knowledge really did set you apart. The AI can adapt faster. AI is inside the human OODA loop.
The good news I think is that you have to be really really specialist for the specialist knowledge to actually be the important bit; for most it's the ability to obtain specialist knowledge, and apply it.
As long as we can adapt, move on to the next knowledge-needed area, we'll hopefully be alright.
(I think there are many analogies here to things people have always said about undergraduate study – e.g. it's about teaching you to learn, not teaching you the specific things you're taught, to be remembered and applied forever.)
May be for OO not yet for DA. Existential pressure drives better(fruitful) decisons and actions. AI has yet to incorporate that into training/inference.
I don't know (also english is not my first language), but to me it takes knowledge to know what is the right tool for the job. To know what is required to make the client happy. To know where great code matters and where quick and dirty or nowdays vibe code is sufficient.
And that knowledge can be complex. It usually requires knowing how people think and act, who don't know how to open a terminal. Because those are the main people using software.
>>I thought that having this knowledge would set me apart
The whole leetcode movement was designed to sell this idea that knowing a solution that can be looked up in a matter of minutes on the internet some how puts you astronomically ahead of those who don't. Strangely enough go look at that site itself and thousands submit working solutions to those problems.
Knowing a solution discovered by somebody the first time, is no test of capacity or ability to get work done. It would probably matter if you discovered solution to a novel problem by yourself. How does knowing the end result of a long process by other people decide your ability to do anything at all?
During interviews I have seen companies go to absurd lengths to justify these tests. Including asking candidates to imagine they might not have internet and might need to know these solutions.
The only skill that really matters in our line of work is today most popularly known as high agency lifestyle. And delivery skills largely depend on ownership. In my decades of experience with software work, not knowing a thing isn't even a correlating factor in getting things done.
Agreed. The ability to learn new things, and what characteristics their ability to learn has -- that's one dimension that strongly differentiates people in nearly any domain.
But there are other dimensions as well that differentiate people and determine their value to business, like the ability to be handed problems no one else can solve and stick with them through sheer stubbornness until solutions begin to emerge.
My concern is less about knowledge and more about the ability to communicate and make good decisions. I'm not sure how well it holds up against technology that can sometimes make a good showing at it, but is most importantly automated, cheap and subservient.
Everyone but insane people like me want some kind of durable stability to their life
they don’t want to be forced to reinvent themselves every five years because the world is changing faster than it ever has
While I understand where people are coming from to an extent that’s just never been my lifestyle and so when I see people looking for some kind of long-term stability I just kind of baffled at what makes them think that that was ever possible.
It’s like the propaganda from the American 1950s nuclear family idealism really got locked in in a way that people believe that there was a real thing
And while it was certainly true that American baby boomers got to ride the economic pax Americana that happened from 1949 to today, that period is over
While it is still possible for you to have a career your career is most likely going to change every 5 to 10 years now and that’s just a fact of the society that we have built
we did not build society intentionally
It was built via attrition and the current leaders are the ones who are fully committed to monetary based global domination
Red Queen hypothesis is a hypothesis in evolutionary biology proposed in 1973, that species must constantly adapt, evolve, and proliferate in order to survive while pitted against ever-evolving opposing species.
Why do we always assume environments and other agents will always remain static.
Knowledge often does not produce competence, especially in the applicable market. I work on the system administration side of things, and I have encountered many output-competent developers that were immeasurably stupid, but very little incompetent ones with tons of cryptic knowledge and intuitive understanding of the systems they worked on.
It seems to me that knowledge doesn't always imply competence, but the lack of knowledge often very well explains incompetence. And, since the LLM is replacing the competence part without imprinting any knowledge on the one that wields it, it generates a lot of competent imbeciles that pass interviews and appear as though they not only do things, but know things as well. And once you reach that critical mass, sheeeeesh
From your example, perhaps you mean "competence does not imply knowledge" or more accurately in fact "lack of competence implies lack of knowledge" i.e. !competence -> !knowledge, in that competence && !knowledge is common but !competence && knowledge is rare.
The following does not answer your question. I am me; I'm not "the HN crowd", if there is even one. And if there is such a crowd I wouldn't be the one knowing what it thinks.
The following is only a perspective on the argument of "the product works" and what "code elegance" means. I don't really care much about LLMs but the following is not necessarily tied to them.
Also, I'm retired from professional programming so feel free to ignore all of it as antiquated and irrelevant.
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Code is not really "a means to an end". Code is better described as a liability.
People you write code may have different perspectives on code but those with more experience generally end up with this idea engrained in their minds. Code is a cost.
Thus, you'd want to have less of it, and you'd want to have code which:
- you at least have some grade of confidence that you can understand as deeply as possible, because that means you can maintain it better and more efficiently. It means that you can, when if fails, quickly/easily find where it failed, sometimes even why it did.
- you can manage in its entirety, which becomes exponentially more difficult when there's more of it and you didn't write it yourself. Not only that, it becomes more difficult to manage it when it has been incorporated in very large chunks that reach all over the codebase, and it becomes a lot more difficult when it lacks consistency, coherence and a certain uniform style.
What you call "the elegance of code" is not an aesthetical quality but a practical one. A developer obviously wants to have something that works, but that it does so well, reliably well. And they want code that is manageable enough that when shit happens -and it always does-, the fix will be hopefully easier and will hopefully make the resulting code more reliable, not less.
And, sure, in some circumstances development speed does matter. The problem is that the circumstances in which it does are frequently "unwanted" ones, usually external pressures, which we already disliked. Usually, you need to develop faster because someone else is pressuring you into putting that speed above reliability, not because it is intrinsically better to do it faster.
The one acknowledged situation in which development speed is tolerated above these other qualities is when doing a prototype. But then again, experienced developers know that prototypes can very easily turn into traps. When doing a prototype, quality is relegated because it is understood that this will not be the final product. It is understood that a prototype's code is disposable. But too often prototypes then become either the product directly or the basis for it. And again this happens because of external pressures. Most of the time because someone says "hey, it's working" without realising that it is barely so, that it's fragile, that it relies on constant tweaking and manual adjustment. But as it appears to be working, it gives the impression of being good enough to make financial sense to build on it.
And when you "ship version 2.0 at an incredible pace" what you're usually doing is shipping prototype 2.0, an unreliable system that requires more constant tweaking and manual adjustment. A system that entraps the developers into more maintenance on each iteration, when they'd want the opposite.
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All in all, using LLMs to produce code may have its place. But if you focus on the idea of producing vast quantities of it faster, then that may not be the best use.
And you can contact hn@ycombinator.com if you're serious. But I'm not sure they do actually accept contributions. And anyway a dark mode is something that has been talked about for years and there doesn't seem to be much interest in adding it to the site. You may try other -external- options to add a dark mode through a browser extension.
So you've followed your tutorial and you've built your little project. And it works! That's great. Congratulations.
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But... now let's think for a moment about what you're doing there. Not the technical bits, but what the user sees.
You have decided that the average male lives to 71-72 and female to around 74. You have then decided that this average should be taken as a hard, fixed limit. And that people will die at that age no matter what.
These two assumptions are somewhat tricky. I mean, the first one is fairly random without a context. For, say, India, this is about right, but for other countries of the world -or as an average for the whole world- it can be quite different. And you don't mention any particular country.
But anyway, it's the second assumption that is more problematic. Because the number is just an average and using it as a hard limit is clearly wrong. First of all because death is not linear. Take a look at this sample table for the US [0]. Life expectancy increases with age. That means that initial life expectancy can be 80 years, but if you make it to 60, your total life expectancy goes up to 84. And if you make it to those 80 your life expectancy still gives you -on average- another 9.5 years to live.
Why is this relevant? Well, because such a calculator would assume the user, the person that goes there to see how much time they have left with their parents... well, still has their parents alive. It would be stupid otherwise if they know their parents are already dead. So this is 2026. The user states that their dad was born in, say, 1956. That's 70 years. Is the 71.5 average life expectancy right? Not at all. Even as an average, even as a hard limit, it is wrong. For a person at 70, that life expectancy would be something like 80+ and the remaining time should be calculated according to that. Sure, this means you need to write code that is a bit more complicated than what you've done here. Because you don't just have one average life expectancy, you need a whole table or function to calculate it. But, hey, this is learning! It's a coding exercise. So it is an opportunity to learn more and go beyond the simple tutorial into an exercise that is just a little bit more advanced.
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But then again, let's ignore even this. Let's go back and keep the simple exercise. Let's assume just one fixed life expectancy. Then, as I mentioned above, we have a problem that's worse, more... stupid. Because as I said such a calculator has to assume the parents are still alive. Otherwise is simply makes no sense. And yet, you're giving the user the option to choose birth years as far back as 1940, while directly assuming that anyone born before 1952 for men or 1955 for women is already dead.
When you offer that option, you're saying it is a valid option. But when the user chooses it, you're saying they are stupid for doing so.
What you're doing is like this conversation:
- Hi, I visit my dad every Friday afternoon.
- That's nice. But from this other perspective that may not be a lot of time. How old is he?
- Oh, my dad is 78.
- Bad news: your dad's already dead.
- What? No, he's fine, I saw him just yesterday.
- Your dad's been dead for years.
- You're an asshole.
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So... again, congratulations on your coding exercise. You did it. The coding is solved [perhaps]. Well done.
But take this as an additional learning point: The problems you solve will sometimes involve writing code, but they will always require you to think about the details and nuances of the problem itself. It's all about the decisions and assumptions you make.
You want to link https://8bit.gioorgi.com/ or https://8bit.gioorgi.com
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