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GitHub cuts AI deals with Google, Anthropic

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Re: GitHub cuts AI deals with Google, Anthropic

#391

Post by tetha »

sbarre wrote: post #359
0xFACEFEED wrote: post #329

Earlier quoted context omitted.

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…

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…

> Porting a multi-thousand line web SaaS product in Typescript that's just CRUD operations and cranking out web views? Sure why not. > > Porting a multi-thousand line game codebase that's performance-critical and written in C++? Probably not.

From my own experience:

I really enjoy CoPilot to support me writing a terraform provider. I think this works well because we have hundreds of existing terraform providers with the same boilerplate and the same REST-handling already. Here, the LLM can crank out oodles and oodles of identical boilerplate that's easy to review and deal with. Huge productivity boost. Maybe we should have better frameworks and languages for this, but alas...

I've also tried using CoPilot on a personal Godot project. I turned it off after a day, because it was so distracting with nonsense. Thinking about it along these lines, I would not be surprised if this occurred because the high-level code of games (think what AAA games do in Lua, and well what Godot does in GDScript) tends to be small-volume and rather erratic within there. Here there is no real pattern to follow.

This could also be a cause for the huge difference in LLM productivity boosts people report. If you need Spring Boot code to put query params into an ORM and turn that into JSON, it can probably do that. If you need embedded C code for an obscure micro controller.. yeah, good luck.

Re: GitHub cuts AI deals with Google, Anthropic

#392

Post by filoleg »

Aeolun wrote: post #330
chairhairair wrote: post #318

Earlier quoted context omitted.

I have completely the opposite perspective. Unit tests actually need to be correct, down to individual characters. Same goes with API calls. The API needs to actually exist. Contrast that with "high level design, rough outlines". Those can be quite vague and hand-wavy. That's where these fuzzy LLMs shine. That said, these LLM-based systems are great at writing "change detection" unit tests that offer ~zero value (or…

> That said, these LLM-based systems are great at writing "change detection" unit tests that offer ~zero value (or negative). That’s not at all true in my experience. With minimal guidance they put out pretty sensible tests.

> With minimal guidance[, LLM-based systems] put out pretty sensible tests.

Yes and no. They get out all the initial annoying boilerplate of writing tests out of the way, and the tests end up being mostly decent on the surface, but I have to manually tweak the behavior and write most of the important parts myself, especially for non-trivial tricky scenarios.

However, I am not saying this as a point against LLMs. The fact that they are able to get a good chunk of the boring boilerplate parts of writing unit tests out of the way and let me focus on the actual logic of individual tests has been noticeably helpful to me, personally.

I only use LLMs for the very first initial phase of writing unit tests, with most of the work still being done by me. But that initial phase is the most annoying and boring part of the process for me. So even if I still spend 90% of the time writing code manually, I still am very glad for being able to get that initial boring part out of the way quickly, without wasting my mental effort cycles on it.

Re: GitHub cuts AI deals with Google, Anthropic

#393

Post by canadianfella »

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…

[dead]

Re: GitHub cuts AI deals with Google, Anthropic

#394

Post by tensor »

poincaredisk wrote: post #96
ianeigorndua wrote: post #86

Earlier quoted context omitted.

How many OSS repositories do I personally have to read through for my own code to be considered stolen property? That line of thought would get thrown out of court faster than an AI would generate it.

I assume you're not an AI model, but a real human being (I hope). The analogy "AI == human" just... doesn't work, really.

I think in this regard it works just fine. If the laws move to say that "learning from data" while not reproducing it is "stealing", then yes, you reading others code and learning from it is also stealing.

If I can't feed a news article into a classifier to teach it to learn whether or not that I would like that article that's not a world I want to live in. And yes it's exactly the same thing as what you are accusing LLMs of.

They should be subject to laws the same way humans are. If they substantially reproduce code they had access to then it's a copyright violation. Just like it would be for a human doing the same. But highly derived code is not "stolen" code, neither for AI nor for humans.

Re: GitHub cuts AI deals with Google, Anthropic

#395

Post by nottorp »

tetha wrote: post #391
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…

> Porting a multi-thousand line web SaaS product in Typescript that's just CRUD operations and cranking out web views? Sure why not. > > Porting a multi-thousand line game codebase that's performance-critical and written in C++? Probably not. From my own experience: I really enjoy CoPilot to support me writing a terraform provider. I think this works well because we have hundreds of existing terraform providers with…

> If you need embedded C code for an obscure micro controller.. yeah, good luck.

... or even information in the embedded world. LLMs need to generate something, o they'll generate code even when the answer is "no dude, your chip doesn't support that".

Re: GitHub cuts AI deals with Google, Anthropic

#396

Post by TiredOfLife »

hshshshshsh wrote: post #16
candiddevmike wrote: post #5

Wake me up when they support self hosted llama or openwebui. Wonder if we'll ever see a standard LLM API.

Isn there no open source alternative? Like a plugin or something.

https://www.continue.dev/ for autocomplete/chat

https://github.com/cline/cline for the agent thing

Re: GitHub cuts AI deals with Google, Anthropic

#397

Post by TeMPOraL »

bongodongobob wrote: post #339
0xFACEFEED wrote: post #329

Earlier quoted context omitted.

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…

You. Can. Write. Tests.

More importantly, you can read diffs.

Depending on whether I'm using LLMs from my Emacs or via a tool like Aider, I either review and manually merge offered modifications as diffs (in editor), or review the automatically generated commits (Aider). Either way, I end up reading a lot of diffs and massaging the LLM output on the fly, and nothing that I haven't reviewed gets pushed to upstream.

I mean, people aren't seriously pushing unreviewed LLM-generated code to production? Current models aren't good enough for that.

Re: GitHub cuts AI deals with Google, Anthropic

#400

Post by balder1991 »

hansonkd wrote: post #367
0xFACEFEED wrote: post #329

Earlier quoted context omitted.

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 more time I spend in a codebase the better idea I have of what the writer was trying to do. This whole thing of using LLMs to Code reminds me a bit of when Google Translate came out and became popular, right around the time I started studying Russian. Yes, copying and pasting a block of Russian text produced a block of english text that you could get a general idea of what was happening. But translating from en…

> the intention of coding should never to be to belt out as many lines as possible

That’s such an underrated statement. Especially when you consider the amount of code as a liability that you’ll have to take care later.

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