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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

#41

Post by dt3ft »

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 concerns. Let them have at it, but once they see the monoliths we tackle with at work - they will burnout on the spot. Cobol? Still alive and well. For a reason.

Re: Tips for programmers to stay ahead of generative AI

#42

Post by varispeed »

laputan_machine wrote: post #12
varispeed wrote: post #6

Earlier quoted context omitted.

I also find it bizarre that so many people feel precious about the code. They have too much ego attached to what they type in and the AI kind of make them feel insecure. I couldn't care less if I write the code, the AI or someone I told to write it. What matters is the value it provides.

> I also find it bizarre that so many people feel precious about the code. Would you find it bizarre that a joiner feels precious about not just the cabinet they made (value), but how they made it? The joints they used, the process they went through, the wood (i.e., the code )? A plumber, electrician, architect, designer, programmer -- we take pride in our skills. Craftmanship is a virtue, not a vice.

Your analogy suggests that the code is the final product, akin to a cabinet or a building, something tangible that can be appreciated for its craftsmanship. In some instances, like open-source software, the code might indeed be viewed this way, but in most cases, it's not the code itself that end-users appreciate, it's the functionality it provides.

To refine your analogy, the code isn't the cabinet - it's more like the blueprint or the process used to create the cabinet. The user doesn't care if a hand saw or a power saw was used, as long as the cabinet is well-crafted and functional. Similarly, end-users of software don't see or appreciate the code. They only interact with the user interface and the functionality it provides. As a result, being "precious" about the code can sometimes be more about personal ego and less about delivering value to the end-user.

In terms of pride in craftsmanship, of course, it's crucial to take pride in one's work. However, this doesn't mean that one should be resistant to using better tools when they become available. The introduction of AI in coding doesn't negate craftsmanship - instead, it's an opportunity to refine it and make it more efficient. It's like a carpenter transitioning from using manual tools to using power tools. The carpenter still needs knowledge, skill, and an eye for detail to create a good product, but now they can do it more efficiently.

Re: Tips for programmers to stay ahead of generative AI

#43

Post by firebirdn99 »

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…

this is one underrated point. Altman talks about democratizing this technology. But if the leading LLMs concentrate at a few companies, unless governmentally mandated, they could keep guardrails from regular folks accessing it, and also with regulation capture.

Re: Tips for programmers to stay ahead of generative AI

#44

Post by Filligree »

firebirdn99 wrote: post #40
medler wrote: post #15

I use LLM-based autocomplete in my IDE, and it’s not taking away my job unless/until it improves by multiple orders of magnitude. It’s good at filling in boilerplate, but even for that I have to carefully check its output because it can make little errors even when I feel like what I want should be obvious. The article is absolutely correct in saying you have to be critical of its output. I would say it improves my p…

Agreed 100%. It's helpful at filling out some functions maybe if you name them correctly, and boiler plate code. Eventually, they will get better, because these things get orders better with orders more scale. Society has to do something about all the jobs at that point, but we'll hopefully get a sense of how close/far is that, with ChatGPT 5, and the next versions coming up.

The biggest benefit, I’ve found, is it makes me comment my code. If I can make the AI understand what I want, then it turns out that three months later I’ll also be able to understand the code.

Re: Tips for programmers to stay ahead of generative AI

#45

Post by rqtwteye »

ape4 wrote: post #11

It seems similar to off-shoring (a while ago). People in another country would bang together tons of inelegant code that somebody else had to check.

That comparison makes sense. And a lot of management will probably use AI because it’s “cheaper” although the results aren’t very good.

Re: Tips for programmers to stay ahead of generative AI

#46

Post by onion2k »

samsk wrote: post #38

I'll start to be afraid, when ChatGPT or anything similar will take a vague Jira issue, simulate described bug and then make a fix for it ;-) But seriously, what developers do most of their time is maintanace, they spend a day searching for a bug, just to write maybe one line of code to fix it.

If GPT can improve the code that's written in the first place then a lot of that work would just go away.

I strongly suspect that it will. There are whole classes of bugs that occur because some work is boring 'not quite copy paste' work that devs just don't like doing, and don't pay any attention to when they're doing it. Linters and syntax highlighters already catch a ton of those issues before they make it to production, and GPT will make the rest much less likely to happen.

Maintenance is one area where GPT will also shine, because it's 'just' updating some code to do the same thing, so using the existing code as a set of tokens with a prompt like 'update this code to work with v2 of library X' will be extremely effective. It'll be like having something write a codemod for you.

The future is bright. We'll get a lot more productive stuff done, and spend a lot less time on boring grunt work.

Re: Tips for programmers to stay ahead of generative AI

#47

Post by randcraw »

ramesh31 wrote: post #23
laputan_machine wrote: post #12

Earlier quoted context omitted.

> I also find it bizarre that so many people feel precious about the code. Would you find it bizarre that a joiner feels precious about not just the cabinet they made (value), but how they made it? The joints they used, the process they went through, the wood (i.e., the code )? A plumber, electrician, architect, designer, programmer -- we take pride in our skills. Craftmanship is a virtue, not a vice.

>Craftmanship is a virtue, not a vice. Exactly, ultimately we are craftsmen , not artisans. They are two very distinct things. The difference being that the value of our output is directly tied to its' functional utility, not any sense of aesthetic or artistic expression. You can take pride in the means used to achieve an end, but they ultimately must be superseded by more efficient techniques or you just become an a…

Craftsmen are individual contributors. When you coordinate others, you're no longer an IC, you're a foreman, a boss. Coding with LLMs is about managing the contributions of other ICs. It's no different from coordinating low-level human coders who simply implement the design that was given them.

If that's the kind of 'craftsmanship' you enjoy, great. To me, this new model of 'bionic coding' feels a lot like factory work, where my job is to keep my team from falling behind the assembly line.

BTW, I've worked factory lines as both IC and foreman. In either role, that life sucks.

Re: Tips for programmers to stay ahead of generative AI

#48

Post by yayitswei »

medler wrote: post #15

I use LLM-based autocomplete in my IDE, and it’s not taking away my job unless/until it improves by multiple orders of magnitude. It’s good at filling in boilerplate, but even for that I have to carefully check its output because it can make little errors even when I feel like what I want should be obvious. The article is absolutely correct in saying you have to be critical of its output. I would say it improves my p…

I agree with 5%. That said, I've found rubber duck debugging to be an exceptionally effective use case for ChatGPT. Often it will surprise me by pinpointing the solution outright, but I'll always be making progress by clarifying my own thinking.

Re: Tips for programmers to stay ahead of generative AI

#49

Post by al_be_back »

with every new comp-language advance or compiler/transpiler etc, coder's life gets easier - but an engineer's life is more broad, it's about Solving Problems that involve: Tech, Design, User and Business. These problems will only get more complex.

I think the Coder's role will become a very niche market, highly expert/specialist. the Engineer's will grow, very much needing AI to help-out, especially with tasks around: Discovery, Mapping/Relating, Projecting/Simulating.

Re: Tips for programmers to stay ahead of generative AI

#50

Post by wiradikusuma »

I've been thinking about this.. most programmers use frameworks/libraries, e.g. Spring/Hibernate in Java or React in JavaScript. Is there a way to train LLM to "specialize" in our frameworks/libraries of choice? I assume it would result in faster/smaller/more accurate result?
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