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Tips for programmers to stay ahead of generative AI

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271–280 of 319 posts

Re: Tips for programmers to stay ahead of generative AI

#271
post #162

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…

Whether this approach works depends a lot on what you are trying to write. GPT4 is not very good at understanding new algorithms and data structures for example. (I recently tried very hard, but it failed miserably. I can talk about the details, if someone is interested.) But it might be good enough at helping you organise a sprawling project.

Yes I'd like the details on this. My experience has been the opposite of you prompt it correctly, or it has the algorithm or data structure trained in its model already.

Re: Tips for programmers to stay ahead of generative AI

#272

>> One of the most integral programming skills continues to be the domain of human coders: problem solving. Analyzing a problem and finding an elegant solution for it is still a highly regarded coding expertise. Yeah right. I'm on windows 11 now, with English (Europe) as the system language and a double English and Greek layout. Windows continues to shit itself and randomly add two new languages and two new keyboard…

It works for MS because of their high market share, the fact that they sell to consumers and not businesses, and the fact that this is unfortunately somewhat of a niche use case.

Bugs definitely matter for smaller companies that cater directly to businesses, for example. "Our workflow is broken" can cost you a very high-paying customer.

Re: Tips for programmers to stay ahead of generative AI

#273

Earlier quoted context omitted.

Yes. Start small and build up. I’ve found it to be very forgetful and have to work function-by-function, giving it the current code as part of the next prompt. Otherwise it randomly changes class names, invents new bits that weren’t there before or forgets entire chunks of functionality. It’s a good discipline as I have to work out exactly what I want to achieve first and then build it up piece by piece. A great way…

IIRC its "memory" (actually input size, it remembers by taking its previous output as input) is only about 500 tokens, and that has to contain both your prompt and the beginning of the answer to hold relevance towards the end of its answer. So yes, it can't make anything bigger than maybe a function or two with any consistency. Writing a whole program is just not possible for an LLM without some other knowledge store…

This isn't quite accurate.

GPT3.5 is 4k tokens and has a 16k version GP4 is 8k and has a 32k version.

You are correct that this needs to account for both input and output. I suspect that when you feed chat gpt longer it prompts, it may try to use the 16k / 32k models when it makes sense.

Re: Tips for programmers to stay ahead of generative AI

#274
post #188

Earlier quoted context omitted.

...and makes your code public domain (you just admitted here that you're using it)- if anyone accesses app developed by you, they can use it freely without any license. Worst thing - you're feeding potentially not your code into GPT. That'd be a fireable offense to me (and a very expensive lawsuit for at least couple places I know). Not an issue if you're lone wolf, though. It's a dystopian thought, but I wouldn't be…

>...and makes your code public domain Just what is your definition of "public domain"?

Not anything that matches legal reality. That's for sure.

Re: Tips for programmers to stay ahead of generative AI

#275
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 find it increases my productivity about 5-10% when working with the technologies I'm the most familiar with and use regularly (Elixir, Phoenix, JavaScript, general web dev.) But when I'm doing something unfamiliar and new, it's more like 90%. It's incredible. Recently at work, for example, I've been setting up a bunch of stuff with some new technologies and libraries that I'd never really used before. Without ChatG…

Funnily enough I find the opposite, its most effective for me when using something familiar (though nowhere near 90%). If I'm familiar with it, I can figure out pretty quickly whats a hallucination and whats not, and to what extent it is (sometimes its just a few values that need changing, sometimes its completely wrong with almost no basis in reality). The time I spend attempting to fix its output in unfamiliar territory makes it more of a pain than its worth for me

Re: Tips for programmers to stay ahead of generative AI

#276

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…

Agreed, my experience programming has been similar. Simply put the hardest part of most big software projects is just building the right thing.

Re: Tips for programmers to stay ahead of generative AI

#277

Earlier quoted context omitted.

> i haven't seen any evidence that an LLM will be capable of doing that on a non-trivial program any time in the near future Or ever, given that the level of abstraction LLMs work at is completely wrong. They can approximate the syntax of things in their training corpus, but logic? The lights are off and nobody's home.

I've already had the GPT3.5-Turbo model walk through and step-by-step isolate and diagnose errors. They 100% can troubleshoot and correct issues in the code. Literally you give it the code and the error and it can walk you through finding the solution. When I say walk you through, I generally mean when you provide it a function but the error is caused by some input that doesn't conform to expectations. If the error w…

Most bugs I've worked on relate to some weirdness that requires tracking down a specific nonobvious offending function. How would GPT help with that at all? Maybe if you know a particular function is wrong, and ask it to find a bug, but by then most of the work has already been done.

Re: Tips for programmers to stay ahead of generative AI

#278

Earlier quoted context omitted.

> I need it yourself attend endless, pointless, weekly zoom meetings where a manager with zero understanding of the task being done. You don't need AI for that, you need to brush up your resume and find another job - The biggest regret of my career is not having left places early when the organisation/management style sucked the enjoyment/productivity out of what you do, particularly if everyone else there agrees wit…

My point us that (as yet) AI can't replace my job, so I'm safe. (The job is safe whether I do it or someone else does.) Now since I work remotely, I am much more likely to be replaced by a cheaper offshore worker. Certainly seems to already have happened to some of the managers I report(ed) to.

“as yet” is doing a lot of work in that first sentence. We all have a gpt number. Like some small number of workers have already been replaced by gpt4, some it will not be until gpt7, some may out code the robots till gpt9.5… Having a higher number doesn’t mean you are a better developer, just that you sit in more meetings and have to use “soft skills” like kissing ass and playing stupid, covering your ass, and other human games that will require more advanced gpt’s.

Re: Tips for programmers to stay ahead of generative AI

#279

Earlier quoted context omitted.

Were you using GPT-3.5 or GPT-4? GPT-4 reduces hallucinations by at least an order of magnitude, and hasn't failed me yet.

This is my experience too. Paying $20/month for GPT-4 has been absolutely worth it. It barely hallucinates at all; the results aren't always perfect (and the September 2021 knowledge cut-off can be frustrating given how quickly things get out of date in the programming world) but it's more than good enough. I don't remember how I ever got by without it.

You could save some money by using GPT-4’s API and a self hosted frontend like YakGPT.

Re: Tips for programmers to stay ahead of generative AI

#280

Earlier quoted context omitted.

My point us that (as yet) AI can't replace my job, so I'm safe. (The job is safe whether I do it or someone else does.) Now since I work remotely, I am much more likely to be replaced by a cheaper offshore worker. Certainly seems to already have happened to some of the managers I report(ed) to.

“as yet” is doing a lot of work in that first sentence. We all have a gpt number. Like some small number of workers have already been replaced by gpt4, some it will not be until gpt7, some may out code the robots till gpt9.5… Having a higher number doesn’t mean you are a better developer, just that you sit in more meetings and have to use “soft skills” like kissing ass and playing stupid, covering your ass, and other…

Are you suggesting LLMs will inevitably gain sentience, consciousness, and the ability to reason deductively at some point in the future?

Recall that the problem with programming isn’t generating more code. Completing a fragment of code by analyzing millions of similar examples is a matter of the practical application of statistics and linear algebra. And a crap ton of hardware that depends on a brittle supply chain, hundreds of humans exploited by relaxed labour laws, and access to a large enough source of constant energy.

All of that and LLMs still cannot write an elegant proof or know that what they’re building could be more easily written as a shell script with their time better spent on more important tasks.

In my view it’s not an algorithm that’s coming for my job. It’s capitalists who want more profits without having to pay me to do the work when they could exploit a machine learning model instead. It will take their poor, ill defined specifications without complaint and generate something that is mostly good enough and it won’t ask for a raise or respect? Sold!

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