Comment by moron4hire | Hacker News Reader

Comment by moron4hire | Hacker News Reader

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Not all change is progress.

Change comes with pros and cons. The pros need to outweigh the cons (and probably significantly so) for change to be considered progress.

Syntax highlighting has the pro of making code faster to visually parse for most people at the expense of some CPU cycles and a 10 second setting change for people for whom color variations are problematic. It doesn't take anything away. It's purely additive.

AI code generation tools provide a dubious boost to short term productivity at the expense of extra work in the medium term and skill atrophy in the long term.

My junior developers think I don't know they are using AI coding tools. I discovered it about 2 months into them doing it, and I've been tracking their productivity both before and after. In one case, one might be committing to the repository slightly more frequently. But in all cases, they still aren't completing assignments on time. Or at all. Even basic things have to be rewritten because they aren't suitable for purpose. And in our pair programming sessions, I see them frozen up now, where they weren't before they started using the tools. I can even see them habitually attempt to use the AI, but then remember I'm sitting with them, and halt.

I tried to use AI code generation once to fill in some ASP.NET Core boilerplate for setting up authentication. Should be basic stuff. Should be 3 or 4 lines of code. I've done it before, but I forgot the exact lines and had been told AI was good for this kind of lazy recall of common tasks. It gave me a stub that had a comment inside, "implement authentication here". Tried to coax the AI into doing what I wanted and easily spent 10x more time than it would have taken to look up the documentation. And it still wasn't done. I haven't touched AI code gen since.

So IDK. I'm very skeptical of the claims that AI is writing significant amounts of working code for people, or that it at all rivals even a moderately smart junior developer (say nothing of actually experienced senior). I think what's really happening is that people are spending a lot of time spinning the roulette wheel, always betting on 00, and then crowing they're a genius when it finally lands.

>>In one case, one might be committing to the repository slightly more frequently. But in all cases, they still aren't completing assignments on time.

Most people are using it to finish work soon, rather than use it to do more work. As a senior engineer your job must not be to stop the use of LLMs, but create opportunities to build newer and bigger products.

>>I can even see them habitually attempt to use the AI, but then remember I'm sitting with them, and halt.

I understand you and I grew up in a different era. But life getting easier for the young isnt exactly something we must resent. Things are only getting easier with time and have been like this for a few centuries. None of this is wrong.

>>Tried to coax the AI into doing what I wanted and easily spent 10x more time than it would have taken to look up the documentation.

Honestly this largely reads like how my dad would describe technology from the 2000s. It was always that he was better off without it. Whether that was true or false is up for debate, but the world was moving on.

> As a senior engineer your job must not be to stop the use of LLMs, but create opportunities to build newer and bigger products.

I think you just hit the core point that splits people in these discussions.

For many senior engineers, we see our jobs are to build better and more lasting products. Correctness, robustness, maintainability, consistency, clarity, efficiency, extensibility, adaptability. We're trying to build things that best serve our users, outperform our competition, enable effective maintenance, and include the design foresight that lets our efforts turn on a dime when conditions change while maintaining all these other benefits.

I have never considered myself striving towards "newer and bigger" projects and I don't think any of the people I choose to work with would be able to say that either. What kind of goal is that? At best, that sounds like the prototyping effort of a confused startup that's desperately looking to catch a wave it might ride, and at worst it sounds like spam.

I assure you, little of the software that you appreciate in your life has been built by senior engineers with that vision. It might have had some people involved at some stage who pushed for it, because that sort of vision can effectively kick a struggling project out of a local minimum (albeit sometimes to worse places), but it's unlikely to have been a seasoned "senior engineer" being the one making that push and (if they were) they surely weren't wearing that particular hat in doing so.

I don't get this idea that to build a stable product you must make your life hard as much as possible.

One can use ai AND build stable products at the same time. These are not exactly opposing goals, and even above that assuming that ai will always generate bad code itself is wrong.

Very likely people will build both stable and large products using ai than ever before.

I understand and empathise with you, moving on is hard, especially when these kind of huge paradigm changing events arrive, especially when you are no longer in the upswing of life. But the arguments you are making are very similar to those made by boomers about desktops, internet and even mobile phones. People have argued endlessly how the old way was better, but things only get better with newer technology that automates more things than ever before.

I don't feel like you read my comment in context. It was quite specifically responding to the GP's point of pursuing "bigger and better" software, which just isn't something more senior engineers would claim to pursue.

I completely agree with you that "one can use ai AND build stable products at the same time", even in the context of the conversation we're having in the other reply chain.

But I think we greatly disagree about having encountered a "paradigm changing event" yet. As you can see throughout the comments here, many senior engineers recognize the tools we've seen so far for what they are, they've explored their capabilities, and they've come to understand where they fit into the work they do. And they're simply not compelling for many of us yet. They don't work for the problems we'd need them to work for yet, and are often found to be clumsy and anti-productive for the problems they can address.

It's cute and dramatic to talk about "moving on is hard" and "luddism" and some emotional reaction to a big scary immanent threat, but you're mostly talking to exceedingly practical and often very-lazy people who are always looking for tools to make their work more effective. Broadly, we're open to and even excited about tools that could be revolutionary and paradigm changing and many of us even spend our days trying to discover build those tools. A more accurate read of what they're saying in these conversations is that we're disappointed with these and in many cases and just find that they don't nearly deliver on their promise yet.

> life getting easier for the young isnt exactly something we must resent.

I don't see how AI is making life easier for my developers. You seem to have missed the point that I have seen no external sign of them being more productive. I don't care if they feel more productive. The end result is they aren't. But it does seem to be making life harder for them because they can't seem to think for themselves anymore.

> a senior engineer your job must not be to stop the use of LLMs, but create opportunities to build newer and bigger products

Well then, we're in agreement. I should reveal to my juniors that I know they are using AI and that they should stop immediately.

> I understand you and I grew up in a different era. But life getting easier for the young isnt exactly something we must resent.

Of course not. But, eventually these young people are going to take over the systems that were built and understood by their ancestors. History shows what damage can be caused to a system when people who don't fully understand and appreciate how it was built take it over. We have to prepare them with the necessary knowledge to take over the future, which includes all the warts and shit piles.

I mean, we've spent a lot of our careers trying to dig ourselves out of these shit piles because they suck so bad, but we never got rid of them, we just hid them behind some polish. But it's all still there, and vibe coders aren't going to be equipped to deal with it.

Maybe the hope is that AI will reach god-like status and jut fix all of this for us magically one day, but that sounds like fixing social policy by waiting for the rapture, so we have to do something else to assure the future.

AI code generation tools provide a dubious boost to short term productivity at the expense of extra work in the medium term and skill atrophy in the long term.

At the moment, sure. They've only been available for about 5 minutes in the grand scheme of dev tools. If you believe that AI assistants are going to be put back in the box then you are just flat out wrong. They'll improve significantly.

I'm very skeptical of the claims that AI is writing significant amounts of working code for people

You may be right, but people write far too much code as it is. Software development should be about thinking more than typing. Maybe AI's most useful feature will be writing something that's slightly wrong in order to get devs to think about a good solution to their problem and then they can just fix the AI's code. If that results in better software then it's a huge win worth billions of dollars.

The belief that AI is worthless unless it's writing the code that a good dev would write is a trap that you should avoid.

> At the moment, sure. They've only been available for about 5 minutes in the grand scheme of dev tools. If you believe that AI assistants are going to be put back in the box then you are just flat out wrong. They'll improve significantly.

I am extremely skeptical that LLM-based generative AI running in silicon-based digital computers will improve to a significant degree over what we have today. Ever.

GPT-2 to GPT-3 was a sea change improvement, but every since then, new models are really only incrementally improving, despite taking exponentially more power and compute to train. Coupled with the fact that processor are only getting wider, not faster, or less energy consuming, then without an extreme change in computing technology, we aren't getting there with LLMs.

Either the processors or the underlying AI tech need to change, and there is no evidence this is the case.

> The belief that AI is worthless unless it's writing the code that a good dev would write is a trap that you should avoid.

I have no idea what you're even trying to say but this. Is this some kind of technoreligion that thinks AGI is worth the endeavor regardless of the harm that comes to people along the way?

Same. I've heard that this area is improving exponentially for years now, but I can't really say the results I'm getting are any better than I originally experienced with ChatGTP.

The dev tooling has gotten better; I use the integrated copilot every day and it saves me from writing a lot of boilerplate.

But it's not really replacing me as a coder. Yeah I can go further faster. I can fill in gaps in knowledge. Mostly, I don't have to spend hours on forums and stack overflow anymore trying to work out an issue. But it's not replacing me because I still have to make fine-grained decisions and corrections along the way.

To use an analogy, it's a car but not a self-driving one -- it augments my natural ability to super-human levels; but it's not autonomous, I still have to steer it quite a lot or else it'll run into oncoming traffic. So like a Tesla.

And like you I don't see how to get there from where we are. I think we're at a local maxima here.

To use an analogy, it's a car but not a self-driving one -- it augments my natural ability to super-human levels; but it's not autonomous, I still have to steer it quite a lot or else it'll run into oncoming traffic. So like a Tesla.

And like you I don't see how to get there from where we are. I think we're at a local maxima here.

To continue the car analogy - are you really suggesting we're at 'peak car'? You don't believe that cars in 20 years time are going to be significantly better than the cars we have today? That's very pessimistic.

There was a meme from back when - "if cars advanced like computers we'd be getting 1000 miles per gallon by now".

Thinking back to the car I had 20 years ago, it's not all that different from the car I have now.

Yes, the car I have now has a HUD, Carplay, Wireless iPhone charging, an iPhone app, adaptive cruise control, and can act as a wifi hotspot. But fundamentally it still does the same thing in the same way as 20 years ago. Even if we allow for EVs and Hybrid cars, it's still all mostly the same. Prius came out in 2000.

And now we've reached the point where computers advance like cars. We're writing code in the same languages, the same OS, the same instruction set, for the same chips as we did 20 years ago. Yes, we have new advancements like Rust, and new OSes like Android and iOS, and chipsets like ARM are big now. But iPhone/iPad/iMac, c/C++/Swift, OSX/MacOS/iOS, PowerPC/Intel/ARM.... fundamentally it's all homeomorphic - the same thing in different shapes. You take a programmer from the 70s and they will not be so out of place today. I feel like I'm channeling Bret Victor here: https://www.youtube.com/watch?v=gbHZNRda08o

And that's not for lack of advancements in languages, Os, instruction sets, and hardware architectures, it's for a lack of investment and commercialization. I can get infinite money right now to make another bullshit AI app, but no one wants to invest in an OS play. You'll hear 10000 excuses about how MS this and Linux that and it's not practical and impossible and there's no money in it, so on and so forth. The network effects are too high, and the in-group dynamic of keeping things the way they are is too strong.

But AGI? Now that's something investors find totally rational and logical and right around the corner. "I will make a fleet of robot taxis that can drive themselves with a camera" will get you access to unlimited wallets filled with endless cash. "I will advance operating systems past where they have been languishing for 40 years" is tumbleweeds.

The cars we have today are not so far off from the cars of 100 years ago. So yes, I highly doubt another 20 years of development, after all the low hanging fruit has already been picked, will see much change at all.

"after all the low hanging fruit has already been picked"

Another great analogy. LLMs allow us to pick low hanging fruit faster. If we want to pick the higher fruit, we'll need fundamentally different equipment, not automated ways to pick low hanging fruit.

For what its worth I agree quite strongly with you and moron4hire in this thread

I wanted to make an observation that what you two are describing seems to me like it maps onto the Pareto principle quite neatly

LLMs seem like they have rapidly (maybe exponentially) approached the 80% effectiveness threshold, but the last 20% is going to be a much higher bar to clear

I think a lot of the disagreement around how useful these tools are is based around this. You can tell which people are happy with 80% accuracy versus those with higher standards

> Mostly, I don't have to spend hours on forums and stack overflow anymore trying to work out an issue

Who does that? If I can’t find something within 15 minutes on the web, it’s back to reading specs, docs, and code. Or bringing out the debugger.

I think a lot of people use forums and stack overflow to find information about a problem they are facing. But you're right, specs, docs, and code are other sources that I hadn't mentioned. I find that forums and stack overflow have utility beyond the documentation, because the docs don't contain information about issues people have faced in the past and accounts about how they have been solved.

But the same idea applies to specs/docs -- instead of reading the specs or the docs, I'd rather be talking to a LLM trained on the specs and docs.

There was a point where I started to dive more into specs, docs, and code, and less relying on finding the answer I'm after.

But in defence of those spending hours on forums, sometimes a project is not well documented, and the code isn't easy to read. In those situations though, I'll be browsing their Github issues or contacting them directly.

Often though I find it highly valuable to go read the docs, even if an LLM has given me a working example. Sometimes, I find better ways, warnings, or even information on unrelated things I want to do.

*ChatGPT, GPT stands for generative pre-trained transformer.

I have no idea what you're even trying to say but this. Is this some kind of technoreligion that thinks AGI is worth the endeavor regardless of the harm that comes to people along the way?

I'm saying there is a lot of value in tools that are merely 'better than the status quo'. An AI assistant doesn't need to be as good as a dev in order to be useful.

These tools don't behave like assistants though, despite being advertised as being assistants

They turn you into the assistant instead of the programmer in the driver seat

Whenever you use them, you have to shift "code review mode", which is not the role of the primary programmer on a task, it is the role of a secondary programmer doing a PR

It's "a lot of value" if you like being the assistant to a very inconsistent junior programmer

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