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Tips for programmers to stay ahead of generative AI

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Re: Tips for programmers to stay ahead of generative AI

#241

Post by Gigachad »

jabradoodle wrote: post #211
kromem wrote: post #201

Earlier quoted context omitted.

Oh, it will improve by several orders of magnitude. But even then, it's not 'replacing' you. It's just going to let you spend less time on BS and more time on the things that are your maximal value contributions to a project. If I had a dozen junior or mid level devs you could hand work off to, would that save you time? Would you kick back and not review what they were doing, particularly around business critical par…

For sure it will still mostly make sense to have a division of labour where you have people who are focused on building software. The question is if generative AI is powerful enough to reduce the number of programmers needed to achieve a task, without creating enough opportunities to replace those programmers. Before we are all replaced there could be a moment where demand for software engineers is 10x less.

Society would simply demand more capable and complex software. Specialized industrial applications that currently look like windows 98 java apps would be expected to be as polished as iOS.

Re: Tips for programmers to stay ahead of generative AI

#242

Post by Tainnor »

3np wrote: post #219
oldstrangers wrote: post #39

My fear isn't that I'll be replaced, it's the technology becoming so good that it'll be kept far out of reach of the common person. I genuinely believe OpenAI knows what a GPT 5+ type world looks like, and they're probably having a lot of debate on how best to monetize it. They could practically charge anything in the world for it assuming it still undercuts the cost of hiring a human. One Nvidia super cluster runnin…

Indeed. "AI will only do the boiler-plate and crud, while us senior engineers won't be replaced any time soon". Sure, you get yours. But what about the next generation of devs and engineers - where do we source the senior engineers replacing us when 90+% of all entry-level and junior positions which actually involve writing repetitive boilerplate to a large extent are gone, and the few remaining are offshored and out…

Why do junior engineers have to mostly write boilerplate code?

Junior devs lack experience, not intelligence. It's fine to give them difficult problems, as long as they're supervised.

I've worked with brilliant junior devs, sure, the code they wrote wasn't terribly idiomatic or maintainable, there were style issues, typical gotchas a more experienced programmer would be aware of etc., but it's not like they were fundamentally unable to solve a hard problem.

Re: Tips for programmers to stay ahead of generative AI

#243

Post by slaymaker1907 »

Or how about this: we hold AI companies accountable for treating the internet as free real estate and attempting to put FOSS developer brains into a jar with a ChatGPT label. These LLMs should not be afforded the same rights as humans and should instead be treated as derivative works of their training data.

Re: Tips for programmers to stay ahead of generative AI

#244

Post by manmal »

kromem wrote: post #204
wouldbecouldbe wrote: post #62

Earlier quoted context omitted.

The thing is the hallucinations, I also wasted few hours trying to work on solutions with GPT where it just kept making up parameters and random functions.

Integration with linters is going to be the next stage in generative coding. It should suggest, lint the suggestion in the background, and if it passes offer the suggestion and if not provide the linting issues output to rework the suggestion. In general, token costs going down will in turn increase the number of multi-pass generation systems over single-pass systems, which is going to improve dramatically. Combine a…

You wouldn’t believe what you can get past a linter. You need test cases that cover the intention of the code, but I‘ve also seen well tested code behave totally counter to its purpose.

Re: Tips for programmers to stay ahead of generative AI

#245

Post by Tainnor »

dt3ft wrote: post #41
oofsa wrote: post #36

The current AI may improve coder performance by only 5%, but it can improve non-coders' learning speed by 1000%. Learning to code has become significantly easier because of ChatGPT, and many university students are already using it for learning. Not only can they let ChatGPT write boilerplate code, but they can also let ChatGPT write comments for code snippets they don't understand and explain unfamiliar syntax. I wo…

Majority having “coding” skills is not happening. Writing code is boring for majority. Why write code when you could be playing games and having fun on TikTok? There is your answer. We love writing code because we are nerds who love to solve complex problems. New kids who are not interested in writing code but using shortcuts to get code written for them by ChatGPT while not understanding it - is the least of our con…

That's a bit of an uncharitable take on people with different interests. Some people who would find coding boring do instead enjoy things like teaching children, treating patients, putting out fires, making art, evaluating stocks, do research, or the millions of other things that humans do as a job or hobby. It's not just people spending time on TikTok.

Re: Tips for programmers to stay ahead of generative AI

#246

Post by starbugs »

vidyesh wrote: post #228
strus wrote: post #213

If you worry about "staying ahead of generative AI" in it's current state, then I think you are not a good coder and you should learn more instead of worrying about that. LLMs are only good in writing new code without surrounding context. They are pretty useless in legacy codebases and in codebases with a lot of internal solutions. I've used Copilot for 2 months at work and maybe 10% of suggestions were useful, and f…

> then I think you are not a good coder and you should learn more instead of worrying about that I am not sure if its that simple and/or so black and white. Everyone is bad when they start, and even stay okay for a while. So fear is very rational, the fear of getting replaced by someone or something better is very humble. No matter how good or bad one is, theres always someone better than them. I think for most peopl…

> I think for most people its smart to adapt to using AI in their workflows to make them better and more efficient

It probably is smart to try out and test everything for a while to see if it is an actual improvement or not.

What I have a serious problem with is the proposal that this now needs to be part of a workflow when it actually doesn't improve anything.

Generative AI in its current form may be helpful in some cases and unhelpful in others. Plenty of examples are mentioned in the context of the other comments.

I agree that the parent statement "then I think you are not a good coder" is a somewhat dangerous overgeneralization.

Re: Tips for programmers to stay ahead of generative AI

#247

Post by slaymaker1907 »

briHass wrote: post #142
irrational wrote: post #77

I work for a Fortune 100 company. Recently an email was sent to all 100,000 employees saying that nobody was allowed to use DALL-E 2, ChatGPT, Codex, Stable Diffusion, Midjourney, Microsoft’s Copilot, and GitHub Copilot, etc. due to concerns about those tools using other people’s IP (meaning our company might end up illegally using their IP) or the potential that the tools might get a hold of our IP through our use o…

Same here. Anyone that works in a highly-regulated industry doing software (e.g. finance, healthcare) is probably not going to see much AI pressure on programmers until the legal quagmire is cleared up. There are privacy concerns with the data, the same ownership/copyright problems often discussed, and ultimately, there needs to be someone (a human) to take accountability (blame) if everything falls down horribly.

I don’t think GPT is legally possible, at least for code generation. AI companies are completely delusional in thinking that they can just use whatever they find on the internet, regardless of license. Regardless of court outcomes, artists, writers, and FOSS devs will lobby congress if necessary to stop this this nonsense. OpenAI has done less than 1% of the work that makes ChatGPT work, most of the work was in producing the training data, and yet OpenAI receives 100% of the profits.

Re: Tips for programmers to stay ahead of generative AI

#248

Post by JSavageOne »

twodave wrote: post #121

Is programming even the hard part about programming? In all seriousness, what we would really need from an AI to start really saving me time would be for it to interview all the customers/partners involved on the project, determine the scope of function needed, boil all that down to a set of sensible domain models that make sense to everyone, identify where/when messages need to be passed, determine which things can…

Interesting take, but I think you're drastically underestimating how much work the programming part is. I think currently at least 90%+ of the work is actually programming / implementing the thing, and that's what AI is going to replace.

Re: Tips for programmers to stay ahead of generative AI

#249

Post by arrowsmith »

abalashov wrote: post #141
wouldbecouldbe wrote: post #62

Earlier quoted context omitted.

The thing is the hallucinations, I also wasted few hours trying to work on solutions with GPT where it just kept making up parameters and random functions.

So much this. The thing hallucinates far more than the hyperventilation seems willing to acknowledge. You really need to be quite competent in the thing you're asking it to do in order to ferret out the hallucinations, which greatly diminishes the potency of GPT in the hands of someone who has no knowledge of the relevant language/runtime/problem domain/etc.

Try paying for GPT-4 - it barely hallucinates at all, at least as far as I've noticed.

Re: Tips for programmers to stay ahead of generative AI

#250

Post by anonu »

JSavageOne wrote: post #248
twodave wrote: post #121

Is programming even the hard part about programming? In all seriousness, what we would really need from an AI to start really saving me time would be for it to interview all the customers/partners involved on the project, determine the scope of function needed, boil all that down to a set of sensible domain models that make sense to everyone, identify where/when messages need to be passed, determine which things can…

Interesting take, but I think you're drastically underestimating how much work the programming part is. I think currently at least 90%+ of the work is actually programming / implementing the thing, and that's what AI is going to replace.

I'm not sure about the 90% figure you quote. I'd say it's a lot less from my experience. But even in that "programming part" I'd say the time to implement core functionality follows the Pareto principle. You can probably code up 80% of what you need in 20% of the time. The other 80% ends up being QA and bug fix iteration.
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