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- Hacker News
- Yes, and it doesn't matter.
Writing code in programming languages is a skill/necessity created by us to instruct computers what we want them to do
Initially in the 60s, this was done by connecting circuits one way or another (think ENIAC). Then we devised "programmable" computers and devised a bunch of codes (computer code instructions) that abstracted away those cables.
The we created Programming Languages to further abstract away the hardware complexity, and to be able to write down our wishes in a way that is more transferable between us humans, but that is still computable by machines.
But with LLMs and neural networks, at some point these abstractions wont be necessary.
The computers will still be making computations, but the way we tell them what we want is going to evolve.
It's fascinating.
by xtracto - Not to detract from your point, but there were software-programmable computers in the 50s. Check out Usagi Electric's videos about the Bendix G-15, where he loads software from punched tape.by badc0ffee
- Computers are useful because we can instruct them what we want to do precisely.
It’s true we usually don’t care about all the details, which is why abstractions exist. An abstraction hides details by fixing them, and lets you specify the rest precisely.
An LLM isn’t an abstraction in this sense any more than asking a coworker to do something is. The details are not fixed, but decided for you. If you can’t understand or modify what was decided yourself, the only interface left is going back and forth in natural language.
So no, the abstractions won’t become unnecessary. The details don’t just go away. Plenty of people really don’t care about them, and for them the LLM is fine, but only because it’s gluing together the millions of LoC of existing libraries and frameworks where the details have already been fixed, overwhelmingly by humans.
There will always be a need for human professionals who aftually understand all that obscure stuff, and per TFA, it’s looking like it won’t be the ones who went all in on AI.
by foltik - So far I think I have learned far more from LLMs than I've lost to them. I forget some syntax, definitely. But I now reach for a much wider range of tools that I have become familiar with because of LLMs.
So, partly agree, partly disagree.
by causal - May I ask how many years experience you have?by larsfaye
- Yeah, I have to say some of this deskilling argument sounds like Socrates complaining about the invention of writing ruining people's ability to truly own the text. I really don't mourn my lost assembly skills or my lost C skills. And I'm not missing the details of whatever web framework du jour my Claude is vibing for me on my extremely useful dataviz internal tools; and I have learned how to rein the agents in to not ruin my high-performance Go code and yet debug concurrency issues. Maybe coding qua coding is what some people find their summum bonum, but for me programming is instrumentive - to build real things in the world that do things to make something better. When I want pure virtuosity of intellectual construction, I read maths papers in arxiv.
(Not to say that the current state of the art with LLMs merits borrowing money for a multi-trillion spend on hardware that will be obsolete in 5 years, but for me that is a different issue).
The master decrying the invention that resulted in more wisdom for more people than anything prior:
"For this invention will produce forgetfulness in the minds of those who learn to use it, because they will not practice their memory. Their trust in writing, produced by external characters which are no part of themselves, will discourage the use of their own memory within them. You have invented an elixir not of memory, but of reminding; and you offer your pupils the appearance of wisdom, not true wisdom, for they will read many things without instruction and will therefore seem [275b] to know many things, when they are for the most part ignorant and hard to get along with, since they are not wise, but only appear wise." (quoting from https://www.historyofinformation.com/detail.php?id=3439)
by lanstin - It believe the most likely consequence of AI is to promote generalists: people who have a domain expertise, can work cross discipline, and has enough programming knowledge to keep the LLMs on track. I don't think 'pure' software engineers will end up being as highly valued as the last decade though I also think that will be true for other disciplines as well. Just as an example, in signal processing, it's not uncommon to have a person designing the general algorithm and another person dedicated to implementing the algorithm in the embedded system. With the quality of coding agents, it's not really necessary to have both of those people anymore. A person who is moderately experienced in both can do the job now.
- I'm looking forward to having the same experience as COBOL engineers did after retirement: companies backing up the brinks truck to anyone with the skills to keep the lights on.by chojeen
- It's like I said in another article, I've spent my life in C# and JavaScript. I'm a low-level programmer now, did even have to learn C or assembly.
- that would be nice, but unfortunately I think the supply vs demand situation is quite different this timeby spogbiper
- > backing up the brinks truck
now that's a phrase I have only heard in one other context: as an alleged quote from former Boston Celtics player Isaiah Thomas (who was really about 5'7 despite his official listed 5'9; yes, professional basketball player in NBA). This was around 2017 when he had just come off a career year and was soon due for a contract extension in the low 9 figures. He got injured and bounced around for a few years before eventually leaving the league, and never got that payday.
by xdavidliu - If you actually look at Cobol job listings, they pay like 50k and want a master's degree. The myth of them being paid really well is not true at all.by superdisk
- TBH it was already pretty bad. There is a stark difference between the best and the average in my experience. The top, say, ten percent of coders are vastly better than anyone else when it comes to anything but boilerplate glue code(which is still needed and is better done by average coders anyway).
This is speaking from my experience as a systems/c/c++ guy. If you are a js web frontend guy, python, or whatever I have no idea if this applies to you.
by 01100011 - Yea, it does apply. Honestly I'd argue that as you move up the abstraction layer cake, it applies even more. If a team gets a tool which 2x's their output (maybe a higher level language vs writing in C), then the difference in absolute output someone who produces 1 widget per day and 5 widgets per day becomes substantial. If you're given a tool which 10x's your output in a day, then it's even bigger. And of course you can have devs on a team who produce -.5 widgets per day.
Think about the worst colleague you've had, now give them a tool which 10x's their output :)
by rozap - I fall into the category of senior engineers who benefit from LLMs for all the reasons mentioned in this post. I find it's possible to agree completely with sentiments like this and still feel as if this is all written in the sand below the high tide line, and ten years from now nobody will care about this.
Horsemanship and sailing were both specialized skills of high value to society, and now they're not. But in each case there was probably a liminal period, when being an accomplished horseman or sailor was still valuable, even as motors were taking over. Eventually that period ended, as the new generations without those skills found ways to get by with cars and motorboats.
by jp57 - Uhhhh sailing is still an extremely valuable skill? Think piloting cargo ships, cruise lines (for non-American pilots), marine equipment...by nunez
- If my horse is ‘a useful piece of software’, what are the cars and motorboats that AI coding is going to give me?by keybits
- This analogy breaks down because computers aren't going away unlike horse drawn carriages or sailing vessels. Computers aren't being replaced by something. It's that fewer people will understand how they work while the efficiency and reach of computers extends into areas of life previously unreachable due to the scale of having humans build it or the refusal of humans.
I could wax philosophical about what that leads to but enough people already have.
by TehCorwiz - I strongly agree with the concept that cognitive friction is the engine of learning.
First and foremost, it's an issue of "dependency": if you stop training the "muscle" of logic and reasoning, it gradually atrophies, just like unused physical muscles. You become dependent on external tools that replace a capability you once had yourself.
A historical example that brought about a similar shift is this: when the production process moved from the craftsman's mind and hands to the Fordist factory (and the assembly line), the skill of building things shifted from human craftsmanship to anonymous, structured processes.
Bit by bit, traditional artisans lost their knowledge and "know-how." Today, having a piece of furniture in our home depends on a massive production and supply chain; the "average" person no longer has the ability to build it themselves.
The exact same thing is happening to software.
We are the (now "former") software craftsmen.
by aledevv - theres even more recent things to learn from > https://en.wikipedia.org/wiki/Ironies_of_Automation
> Bainbridge argues that new, severe problems are caused by automating most of the work, while the human operator is responsible for tasks that can not be automated. Thus, operators will not practice skills as part of their ongoing work. Their work now also includes exhausting monitoring tasks. Thus, rather than needing less training, operators need to be trained more to be ready for the rare but crucial interventions
by intended - > Today, having a piece of furniture in our home depends on a massive production and supply chain; the "average" person no longer has the ability to build it themselves.
Tangential, but this is one of many reasons that I (and I suspect many others here) have taken up wood working.
by Carrok - Another example is autocorrect absolutely destroying the world's ability to spell even the most basic words. Ever since mobile phones came along and removed the friction of walking to the dictionary, everywhere I look people write as if they have extremely serious brain trauma - grown adults struggling to write as well as we used to as children!by pixelpoet
- > "...if you stop training the "muscle" of logic and reasoning, it gradually atrophies, just like unused physical muscles. You become dependent on external tools that replace a capability you once had yourself."
For a bit of extra unease, consider that these people will retain their right to vote, both in making business decisions as employees, in shareholder meetings as shareholders, and in government elections as voters, despite their atrophied reasoning abilities. Who will wind up whispering what to vote for in the ears of these reverse centaurs?
by ThrowawayR2 - > cognitive friction is the engine of learning. I agree 100% too.
This is why in order to understand new codebase or to ramp up to new projects, I use AI to generate a textbook style reading material for me along with "verify yourself" types of exercises along the way. Then I print them on a paper and read it using a pencil/pen and take notes.
Because of my math training, I am in the habit of slowing down to read textbook style texts which helps.
by ksd482 - As a tech educator I 100% agree. LLMs are not going to become a "new compiler" where we don't have to worry about the code any more. There's a reason we trust deterministic systems.
I've been worried about this a lot, I even created an agent skill called do-i-understand that's designed for novice devs (and experienced too, because atrophy) where the LLM asks you questions about the PR you're about to submit. I've found it helps a lot: https://github.com/AnthonyPAlicea/skills/blob/main/skills/do...
One way or another, there will be a skill reckoning.
by TonyAlicea10 - A deterministic LLM is possible. Would you trust it?by chrisjj
- Why do you trust the non-deterministic LLM with your skill?by nonethewiser
- It doesn't matter if the LLM is not deterministic.. the OUTPUT of typed code is deterministic in the sense that it can be seen to be type safe, compiled, and run appropriate unit tests on it.
If I use two LLM's to create some chunk of code and they both do it slightly differently but they both compile and pass appropriate tests.. it honestly doesn't matter if the LLM itself is not deterministic in exactly what it's going to output.
I would also argue- doesn't that make sense? You give two human coders the same task and they are also going to come up with slightly different results.
- The snake eating it's own tail for llm software development has really been met with a shoulder shrug whenever it gets brought up. At best you might have a small cohort of developers that don't cook their brains with AI and their reward for that appears to be having to review terrible AI code written by people who have cooked their brains.
Completely unsustainable.
- This paints the situation black and white. Also doesn't help anyone.by fbrncci