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GitHub cuts AI deals with Google, Anthropic

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Re: GitHub cuts AI deals with Google, Anthropic

#401

Post by tensor »

zeroonetwothree wrote: post #321
tensor wrote: post #308

Earlier quoted context omitted.

Except actual studies objectively show efficiency gains, more with junior devs, which make sense. So no, it's not a "deception" but it is often overstated in popular media.

Studies have limitations, in particular they test artificial and narrowly-scoped problems that are quite different from real world work.

And anecdotes are useless. If you want to show me improved studies justifying your claim great, but no I don't value random anecdotes. There are countless conflicting anecdotes (including my own).

Re: GitHub cuts AI deals with Google, Anthropic

#402

Post by mattmanser »

tensor wrote: post #382
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…

The fact that you think "change detection" tests offer zero value speaks volumes. Those may well be the most important use of unit tests. Getting the function correct in the first place isn't that hard for a senior developer, which is often why it's tempting to skip unit tests. But then you go refactor something and oops you broke it without realizing it, some boring obvious edge case, or the like. These tests are al…

I think you've misunderstood what he meant by change detection (not GP, could be wrong).

Hard to describe, easy to spot.

Some people write tests that are tightly coupled to their particular implementation.

They might have tons of setup code in each test. So refactoring means each test needs extensive rewrites.

Or there will be loads of asserts that have little to do with the actual thing being tested.

These tests usually have negative value as your only real option as another developer is to simply delete them all and start again.

That's what I would interpret the GP as meaning when they use the phrase "change detection" tests.

Re: GitHub cuts AI deals with Google, Anthropic

#403

Post by Nullabillity »

xk_id wrote: post #390
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…

> I'm actually very curious why AI use is such a bi-modal experience. My conspiracy theory is that the positive experiences are exaggerated and come from investors in the Nvidia stock.

That's a very important caveat. In our modern economy it's difficult to not be a shill in some way, shape, or form, even if you don't quite realize it consciously. It's honestly one of the most depressing things about the stock market.

Re: GitHub cuts AI deals with Google, Anthropic

#404

Post by CephalopodMD »

I usually feel like i can confidently express a change I want in code faster and better than I can explain what I want an AI to do in English. Like if I have a good prompt, these tools work okay, but getting that prompt almost as hard as just writing the code itself often. Do others feel the same struggle?

Re: GitHub cuts AI deals with Google, Anthropic

#406

Post by scott01 »

simonw wrote: post #388
javaunsafe2019 wrote: post #387

I don’t know how people can claim such huge success using copilot and such. I also own a subscription and tried to use it for coding but all task from spring boot authentication configuration to aws policies and lambdas it failed horribly. Writing the code myself using proper documentation was the only option. I wonder if false information is written here in the comments section for certain reasons …

You need to spend time learning how to use it. This is difficult because there's no manual, and there's a widespread implication that it should just magically work well without you having to invest any effort in it. If you can figure out HOW to invest that effort it becomes really valuable. I wish I had good resources I could link you to here but I don't, which is a big part of the problem here.

You sound like you’ve had success using this tech for work. Can you tell more about your personal experience, please? I’ve tried ChatGPT a few times a year ago or so, but it was extremely frustrating, and I gave up.

Re: GitHub cuts AI deals with Google, Anthropic

#407

Post by xk_id »

Nullabillity wrote: post #403
xk_id wrote: post #390

Earlier quoted context omitted.

> I'm actually very curious why AI use is such a bi-modal experience. My conspiracy theory is that the positive experiences are exaggerated and come from investors in the Nvidia stock.

That's a very important caveat. In our modern economy it's difficult to not be a shill in some way, shape, or form, even if you don't quite realize it consciously. It's honestly one of the most depressing things about the stock market.

I credit my past interest in cryptocurrencies for educating me about the essence of the stock market in its purest form. And in fact there are painful parallels with the AI bubble.

Re: GitHub cuts AI deals with Google, Anthropic

#408

Post by Aeolun »

0xFACEFEED wrote: post #383
geysersam wrote: post #365

Earlier quoted context omitted.

I'll take a stab at changing your mind. AIs are not able to write Redis. That's not their job. AIs should not write complex high performance code that millions of users rely on. If the code does something valuable for a large number of people you can afford humans to write it. AIs should write low value code that just repeats what's been done before but with some variations. Generic parts of CRUD apps, some fraction…

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 writing crud, I get to spend that on more useful stuff. If it doesn’t make me more effective, at least it makes my job more enjoyable.

Re: GitHub cuts AI deals with Google, Anthropic

#409

Post by hackable_sand »

bob1029 wrote: post #246
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,…

It's the subtle errors that are really difficult to navigate. I got burned for about 40 hours on a conditional being backward in the middle of an otherwise flawless method. The apparent speed up is mostly a deception. It definitely helps with rough outlines and approaches. But, the faster you go, the less you will notice the fine details, and the more assumptions you will accumulate before realizing the fundamental e…

I would love to find out

where programmers are learning this idea:

that writing code fast is ideal.

If it takes 30 years to write one loc, it takes 30 years.

Ideally, it takes 30 years to write zero lines of code.

Re: GitHub cuts AI deals with Google, Anthropic

#410

Post by Aeolun »

ianbutler wrote: post #360
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 have 10 years professional experience and I've been writing code for 20 years, really with this workflow I just read and review significantly more code and I coach it when it structures or styles something in a way I don't like. I'm fully in control and nothing gets committed I haven't read its an extension of me at that point. Edit: I think the issues you've mentioned typically apply to people too and the answer i…

> Talk, coach, put hard fixes in like linting and review approvals.

And sometimes, when all that doesn’t work? Just do it yourself :)

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