I read “Code was never the hard part” as “Writing the Code down is easier than the stuff you do before it (like Architecture, Design Patterns, Requirements) and after it (Testing, Troubleshooting, Refactoring, etc)”.
“Code was never the hard part” is probably made up by someone who never had to program anything serious.
“Writting the code was never the hard part”
It’s figuring out in detail what the program is suppose to do (i.e. Requirements), how it can and should do it given the technical constraints of the available deployment environment and performance & reliability requirements (i.e. Technical Analysis) and how it all gets structured from the highest level to the lowest level so that bugs are minimized, performance is suitable with the appropriate margin to absorb expect unexpected problems and costs for maintenance and future requirements implementation are low (i.e. from Technical Architecture and Systems Design down to Software Design) that are hard.
And I say this as somebody who has done all of those professionally, plus the coding (oh, so, so much coding) for systems of all kinds and sizes in various countries and industries, including some mission critical high performance distributed systems (which if they failed would have cost millions of $$$ in lost business income).
Fly by the seat of their pants coders who have never worked in a properly professional environment have no fucking clue just how much more there is to it than “coding” to go from no software at all to “reliable and robust software system that serves existing business needs”.
A lot of “coders” are like I was in the beginning of my career: they think they’re the shit, know nothing but a very limited range of work environments which they think “that’s how things are done” when those environments are actually, amateur hour, every hour of every day, every day of the month, every month of the year - they’re basically at the peak point of the Dunning-Krugger curve for software development knowledge.
For me, that is all integrated part of “programming”. You missed the documenting the code part, but i consider this as an oversight.
Define “serious”.
An OS, a compiler, any complete application. Or at least significant parts of it. And I mean programming from A to Z: defining, detailing, implementing, verifying, documenting.
That try, the hard part is algorithmic and avoiding archictuctural traps and experience. Pissing code which didn’t work or look like it work but don’t is easy.
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This to me seems to be a very odd interpretation of the phrase “coding was never the hard part”. First, that doesn’t mean that it’s not hard, just not the hardest. Second, and more importantly, they jump to deciding what to build being the hard part as if those are the only two things?
I have used a variation of this phrase (I usually say coding was never the bottleneck at work) but I’ve never even considered deciding what to build as to be what the bottleneck is.
First, I should say by coding I mean taking a concrete design for a change and writing a single pass at implementation. Modern models to this extremely quickly with up to good performance depending on exactly what you ask them to do.
The things that take up more time in software development just for engineers, leaving aside things that design and pms do.
- Coming up with that concrete design for a change (humans may do this in many ways, one of which is writing the code without a plan and refining)
- Architecting the system at all levels. This one is continuous and huge. A good architecture will easily adopt changes as they come, but you can never foresee all possibilities, and even if you could, there’s usually other people around you who can’t, which brings me to
- Communicating the system design and coming to consensus about aspects of it. This is mostly applicable to teams and is the primary reason individuals can often outperform entire teams. It’s also one reason why throwing a second LLMs at a problem doesn’t solve it at twice the rate. You’ll never get linear scaling
- Upkeep tasks: what needs to be replaced and fixed now, how do we best monitor and alarm to figure this out in the future.
There are “what to build” aspects in here and many engineers also spend time on the overall what to build questions, but the way the article was talking about it seemed very high level.
Coding isn’t easy, it’s hard. But it’s also not usually the bottleneck in software development.
Whoever you are, don’t outsource your understanding, judgement, empathy and taste to AI. Don’t abdicate your responsibility. Don’t be a meat proxy.
By expanding the ability to program to people without the knowledge of how that code works in the first place, it’s naive to expect that most uses of AI in programming will be informed uses by senior developers able to recognize errors and security flaws.
Such a pro-AI position also ignores the enormous amount of theft that these tools are built on.
the ability to program
people without the knowledge of how that code works
Ain’t that the biggest oxymoron you’ve seen today.
They are not given the ability to program, per se, in my opinion. They are doing something else.
Maybe I’m misunderstanding your comment though. Not sure if you’re referring to the code output when you said “that code”, or some other code. Please let me know if I got it wrong.
Such a pro-AI position also ignores the enormous amount of theft that these tools are built on.
Or, less likely, it could be that person knows and just doesn’t care. I certainly don’t because I believe intellectual property is bullshit.
It’s one thing for individuals (particularly those without the means of paying) to pirate content that its original creators have already been compensated for and now exists to milk money for an IP holder for a century; it’s another matter entirely when AI companies with multi-billion dollar valuations scour the internet for content to include in their models to then profit from without permission from or compensation to the millions of people whose work they depend on.
Yeah that’s the thing: I don’t believe it’s wrong to profit from people’s content without their permission, because I don’t believe they own that content after they share it with humanity and I absolutely don’t believe they should get to enforce that “ownership” via state violence. Everyone should get to use anything they want in derivative works, whether for profit or not. The fact that this could plausibly affect people’s livelihoods (but IMO wouldn’t; if there were significant profits in IP “theft” corporations would already be doing it) is a failure of capitalism and frankly not the reproducer’s business.
The entire AI industry is built on IP theft; even if you don’t believe in IP ownership, companies like OpenAI and Anthropic rely on their ability to scrape the internet for content, with only largest of publishers having the resources to sue for anything in return.
So long as copyright is being enforced at the individual level for consumers, large corporations shouldn’t be allowed to get away with infringing on it for profit.
So long as copyright is being enforced at the individual level for consumers, large corporations shouldn’t be allowed to get away with infringing on it for profit.
Sure, but my conclusion from that isn’t “IP law should be enforced on the big corporations too;” it’s “IP law should be abolished and also down with capitalism.” Why should I want an unjust law to be enforced even more vigorously?
The problem in there is corporations. AI is just the means of the dickery, not the cause.
I would also go further and say the root cause is capitalism, and that someone being able to eat or be housed should not be based on whether or not their art has met the criteria for corporate purchase. But I digress.
I’m baffled I just downvoted a comment saying “intellectual property is bullshit”. There’s a first time for everything I guess. And yes it is bullshit but gosh, what a weird place to take that stance.
I mean, a key element of the anti-AI movement is that AI “steals” art, but I fundamentally believe in that art (and ideas) can’t be owned and therefore can’t be stolen. Ditto for code or what have you.
AI training is data theft not IP theft
It can be both…
Yeah, it can be both, like, if you want to argue that in our current capitalist society people need to be compensated fairly for their work, I’ll hear that argument, but I don’t think it’s the best or most accurate framing. I think it’s just as obnoxious reddit made a deal with google to train on my (and everyone else’s) comments throughout the website as I do the possibility it was trained on my artwork, and I’m not alone in that.
The data theft is another story, but there’s clearly an IP theft angle to anti-AI arguments, as seen in the other person response.
His other comment applies just as easily to to stolen medical images, like this woman’s , as it does more creative works. It feels violating either way. Virtually no one is worried about Mickey Mouse appearing in data sets, but lots of people do feel wronged when their emails are trained on without permission or compensation, even though they’re not really IPs.
I appreciate the intent behind that sentence, and the problem is that is written (or said) by people who don’t understand coding.
Syntax was never the hard part. Code syntax is a set of rules that you can teach a machine and it’s “easy” enough for an LLM to grasp it. The problem here is that this phrase does a “code = syntax” but ignoring all the difficult things that actually are in the code. Architecture, design, tradeoffs, translation of vague requirements into concrete software components…
All of those things are terribly hard, and the reason why many LLM-first coding projects get abandoned at 70% and then companies need to hire a Software Development consultancy to mop up their mess.
Interestingly what I’ve said here ☝️ ️comes with an interesting implication. There used to be a type of software “engineer” that couldn’t actually think through a problem and implement a good software solution. They were valuable because they could refactor, write code, but not think through a problem. These are the people who have the most to lose at the moment, and also the ones that find the least value on AI, because AI only does really well the single thing they could do.
That style of software developer used to be called “monkey coders”.
Employing “monkey coders” because they are cheaper is a great way to end up paying a lot more money over the long run because their work is unmaintainable, ureliable, not robust and stupidly hard to be upgraded to implement new requirements.
Which, if you think about it, it’s pretty much what you get with AI code.
And yeah, totally agree that these are the people who are most threatenned directly by AI at the moment. Then again, they were the ones most threatenned by outsourcing already (to India especially, since when they grew massive as an outsourcing place for software development they started hiring tons of people there who had no skill whatsoever for it and would never have gone into software development and were pretty bad, so most coders based in India were eventually this kind of code writter).
Hiring “monkey coders” was always the product of bad management: they looked good on paper - cheap, made lots of code, bums on seats, often the kind of person who worked long hours (which in low efficient management cultures makes a manager look good because of “making their people work hard”) - whilst creating massive costs spread over time and hitting everything from production downtime costs to future system improvement costs. In some ways the mass replacement of developers with AI is born from the same management incompetence as outsourcing, which is probably why it is hitting the US so hard.
Which brings us around to how, indirectly, even good software developers are right now threatened by AI - the kind of incompetent manager who thinks code lines is a productivity metric aren’t replacing just “monkey coders” with AI, they’re cutting down head-count with no selectivity or even replacing first the more professional coders because they’re the most expensive.
This might not be sustainable in the mid and long term because AI, like “code monkeys”, just piles up massive less obvious over-time costs on software systems (I expect a lot of companies will go under from this shit) and some are already getting desperate for the kind of professionals that can fix their self-inflicted AI problem, but people who aren’t prepared for up to two of being out of well paying software development jobs (so, most people) are getting screwed instead of aligning themselves to really profit from the wave of post-AI “oh, shit or systems are unreliable shit” work for senior types that’s just starting, plus if indeed as I expect companies will fail due to this, the Tech boom will be over and there will be fewer positions than there were 2 or 3 years ago.
Remember that story about the chalk mark engineer with Ford? Chalk mark 1$, knowing where to mark 1000$ ? Same with code. “Code” is easy. Knowing what to write, why and where, that’s the hard part. LLMs have somehow managed to automate the code part, without the abstraction, at least in an error proof way. I don’t think “coding isn’t that hard” is insulting, and I don’t use C++ because I think it’s hard. But it’s not because writing something is hard, it’s because writing precisely what is needed is hard.
Anyway, this debate doesn’t matter, negotiate better, be active politically to ban stuff or not, complaining on the internet won’t do anyone any good. I know you’re emotionally invested in this, just… breathe and do something else? Idk. Also I’m not your enemy on this, so no need to attack me.
I won’t miss writing code. In part because I still do when I feel like it, but also because most of the time it is extremely boring. A mere mean to a goal for which you probably have the path mapped out in your brain already. It is basically just busywork at that point.
There are these moments where you need to squeeze out performance, where you change something about the UI or generally visuals and get a pleasing result, or where you discover a small tweak that collapses a lot of complexity you originally planned for - but that is, in my humble experience, not the norm in programming. The vast majority of code is boilerplate or stuff you have already written a thousand times in some variation. The more experience you have the worse it gets.
I was ecstatic when I realized how good agents have gotten, realized how I could focus on design and architecture and with small corrections, get more than adequate software. Because for me personally, programming is the least fun part of software development. Most of the time that is. And you can hate it all you want, but programming is a skill worth nothing on its own now, and it will never be again. You can take solice in the fact that you can still do it for fun if you want to.
idk, code was always written only once, but it will always be read many times. Writing code with LLM centric way and just focusing the high level gets hazardous pretty quickly, since somebody actually needs to understand the codebase deep down (or at least the relevant part) when something goes wrong. When you have 100k+ line codebase with multiple contributors with LLM it can very quickly turn into a black box, which nobody understand anything deep down anymore and everybody are more and more incentivized to use LLMs to interact with the thing to get anything real done. Then it’s couple hallucinations away from turning into a fragile mess, where things break unexpected and nobody knows why.
Programming on its own was never what got you paid.
