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GitHub cuts AI deals with Google, Anthropic

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Re: GitHub cuts AI deals with Google, Anthropic

#421

Post by pama »

0xFACEFEED wrote: post #354
bongodongobob wrote: post #339

Earlier quoted context omitted.

You. Can. Write. Tests.

How do tests account for cases where I'm looking at a 100 line function that could have easily been written in 20 lines with just as much, if not more, clarity? It reminds me of a time (long ago) when the trend/fad was building applications visually. You would drag and drop UI elements and define logic using GUIs. Behind the scenes the IDE would generate code that linked everything together. One of the selling points…

> How do tests account for cases where I'm looking at a 100 line function that could have easily been written in 20 lines with just as much, if not more, clarity?

If the function is fast to evaluate and you have thorough coverage by tests, you couod iterate on an LLMs that aims to compress it down to a simpler / shorter version that behaves identical to the original function. Of course brevity for the sake of brevity can lead to less code that is not always more clear or simpler to understand than the original —LLMs are very good at mimicing code style, so show them a lot of your own code and ask them to mimic it and you may be surprized.

Re: GitHub cuts AI deals with Google, Anthropic

#422

Post by 0xFACEFEED »

Aeolun wrote: post #408
0xFACEFEED wrote: post #383

Earlier quoted context omitted.

I can definitely see the value in letting AI generate low stakes code. I'm a daily CoPilot user and, while I don't let it generate implementations, the suggestions it gives for boilerplate-y things is top notch. Love it as a tool. My major issue with your position is that, at least in my experience, good software is the sum of even the seemingly low risk parts. When I think of real world software that people rely on…

I think your concept of ‘what the AI wrote’ is too large. There is zero chance my one line copilot or three line cursor tab completions are going to have an effect on the overall quality of my codebase. What it is useful for is doing exactly the things I already know need to happen, but don’t want to spend the effort to write out (at least, not having to do it is great). Since my brain and focus aren’t killed by writ…

I'm with you. I use Copilot every day in the way you're describing and I love it. The person I was responding to is claiming to code "hands off" and let the AI write the majority of the software.

Re: GitHub cuts AI deals with Google, Anthropic

#423

Post by foobiekr »

ianbutler wrote: post #311
thih9 wrote: post #221

I use cursor and its tab completion; while what it can do is mind blowing, in practice I’m not noticing a productivity boost. I find that ai can help significantly with doing plumbing, but it has no problems with connecting the pipes wrong. I need to double and triple check the updated code - or fix the resulting errors when I don’t do that. So: boilerplate and outer app layers, yes; architecture and core libraries,…

I'm actually very curious why AI use is such a bi-modal experience. I've used AI to move multi thousand line codebases between languages. I've created new apps from scratch with it. My theory is the willingness to baby sit and the modality. I'm perfectly fine telling the tool I use its errors and working side by side with it like it was another person. At the end of the day it can belt out lines of code faster than I…

The most likely explanation is that the code you are writing has low information density and is stringing things together the same way many existing apps have already done.

That isn’t a judgement but trying to use the ai code completion tools for complex systems tasks is almost always a disaster.

Re: GitHub cuts AI deals with Google, Anthropic

#424

Post by mistrial9 »

0xFACEFEED wrote: post #369
sbarre wrote: post #359

Earlier quoted context omitted.

I think it depends on the stakes of what you're building. A lot of the concerns you describe make me think you work in a larger company or team and so both the organizational stakes (maintenance, future changes, tech debt, other people taking it over) and the functional stakes (bug free, performant, secure, etc) are high? If the person you're responding to is cranking out a personal SaaS project or something they won…

> A lot of the concerns you describe make me think you work in a larger company or team and so both the organizational stakes (maintenance, future changes, tech debt, other people taking it over) and the functional stakes (bug free, performant, secure, etc) are high? The most financially rewarding project I worked on started out as an early stage startup with small ambitions. It ended up growing and succeeding far be…

adding here due to some resonance with the point of view.. this exchange lacks crucial axes.. what kind of programming ?

I assume the parent-post is saying "I ported thousands of lines of to . I could be very wrong but that is my guess. Like any data-driven software machinery, there is massive inherent bias and extra resources for in this guess-case it is python that runs on a standard cloud environment with the loaders and credentials parts too perhaps.

Those who learned programming in the theoretic ways know that many, many software systems are possible in various compute contexts. And those working on hardware teams know that there are a lot of kinds of computing hardware. And to add another off-the-cuff idea, so much web interface ala 2004 code to bring to newer, cleaner setups.

I am not about this sea change in code generation, but actually code generation is not at all new. It is the blatent stealing and LICENSE washing of a generation of OSS that gets me, actually. Those code generation machines are repeating their inputs. No authors agreed and no one asked them, either.

Re: GitHub cuts AI deals with Google, Anthropic

#425

Post by chillfox »

girvo wrote: post #412
mithametacs wrote: post #379

Earlier quoted context omitted.

You still use type systems, tests, and code review. For a lot of use cases it's powerful. If you ask it to build out a brand new system with a complex algorithm or to perform a more complex refactoring, it'll be more work correcting it than doing it yourself. But that malformed JSON document with the weird missing quotation marks (so the usual formatters break), and spaces before commas, and the indentation is wild..…

The (mostly useless boilerplate “I’m basically just testing my mocks”) tests are being written by AI too these days. Which is mildly annoying as a lot of those tests are basically just noise rather than useful tools. Humans have the same problem, but current models are especially prone to it from what I’ve observed And not enough devs are babysitting the AI to make sure the test cases are useful, even if they’re doin…

There are very few tutorials on how to do testing and I don't think I have ever seen one that was great. Compared to general coding stuff where there's great tutorials available for all the most common things.

So I think quality testing is just not in the training data at anywhere close to the quantity needed.

Re: GitHub cuts AI deals with Google, Anthropic

#426

Post by breckenedge »

thih9 wrote: post #221

I use cursor and its tab completion; while what it can do is mind blowing, in practice I’m not noticing a productivity boost. I find that ai can help significantly with doing plumbing, but it has no problems with connecting the pipes wrong. I need to double and triple check the updated code - or fix the resulting errors when I don’t do that. So: boilerplate and outer app layers, yes; architecture and core libraries,…

Tab complete is just one of their proprietary models. I find chat-mode more helpful for refactoring and multi-file updates, even more when I specify the exact files to include.

Re: GitHub cuts AI deals with Google, Anthropic

#427

Post by AIorNot »

Reviewing these conversations is like listening to horse and buggy manufacturers pooh-poohing automobiles:

1. they will scare the horses. a good team of horses is no match for funky 'automobile'

2. how will they be able to deal with our muddy, messy roads

3. their engines are unreliable and prone to breaking down stranding you in the middle and having to do it yourself..

4. their drivers cant handle the speed, too many miles driven means unsafe driving.. we should stick to horses they are manageable.

Meanwhile I'm watching a community of mostly young people building and using tools like copilot, cursor, replit, jacob etc and wiring up LLMs into increasingly more complex workflows.

this is snapshot of the current state, not a reflection of the future- Give it 10 years

Re: GitHub cuts AI deals with Google, Anthropic

#428

Post by outside1234 »

0xFACEFEED wrote: post #329
ianbutler wrote: post #311

Earlier quoted context omitted.

I'm actually very curious why AI use is such a bi-modal experience. I've used AI to move multi thousand line codebases between languages. I've created new apps from scratch with it. My theory is the willingness to baby sit and the modality. I'm perfectly fine telling the tool I use its errors and working side by side with it like it was another person. At the end of the day it can belt out lines of code faster than I…

As a programmer of over 20 years - this is terrifying. I'm willing to accept that I just have "get off my lawn" syndrome or something. But the idea of letting an LLM write/move large swaths of code seems so incredibly irresponsible. Whenever I sit down to write some code, be it a large implementation or a small function, I think about what other people (or future versions of myself) will struggle with when interactin…

The saying "You can delegate tasks but not responsibility" comes to mind.

You are still responsible for the code AI is writing. It is just that writing code with AI is more like reviewing a PR now.

Re: GitHub cuts AI deals with Google, Anthropic

#429

Post by grensley »

thih9 wrote: post #221

I use cursor and its tab completion; while what it can do is mind blowing, in practice I’m not noticing a productivity boost. I find that ai can help significantly with doing plumbing, but it has no problems with connecting the pipes wrong. I need to double and triple check the updated code - or fix the resulting errors when I don’t do that. So: boilerplate and outer app layers, yes; architecture and core libraries,…

I think there's a number of factors that make it work as well as it does for me:

- Mostly writing React

- Not using any obscure or new libraries

- Naming things well

- Keeping logic simple

- Leaving a comment at the point where I'm about to make a shift from what the common logic would be

- Getting a feel for when it's going to be able to correctly guess or not (and not even reading it if I think it's going to be wrong)

- Trusting short blocks more than long ones

Re: GitHub cuts AI deals with Google, Anthropic

#430

Post by geodel »

WgaqPdNr7PGLGVW wrote: post #223
geodel wrote: post #178

Earlier quoted context omitted.

Well it is volume business. <1% of advanced skill developers will find AI helper useless but for 99% of IT CRUD peddlers these tools are quite sufficient. All in all if employers cut down 15-20% of net development costs by reducing head counts, it will be very worthwhile for companies.

I suspect it will go a different direction. Codebases are exploding in size. Feature development has slowed down. What might have been a carefully designed 100kloc codebase in 2018 is now a 500kloc ball of mud in 2024. Companies need many more developers to complete a decent sized feature than they needed in 2018.

Agree. But we are already in that loop. A 50KLOC properly written "Monolith, hence outdated" app is now 30 micro services of 20KLOC surface + 100KLOC of submerged in terms of convenience libraries with kubernetes, grafana, datadog, servicemesh and so on. From what I am seeing companies are increasingly using off the shelf components so KLOC will keep rising but developer count would not.
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