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GitHub cuts AI deals with Google, Anthropic

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Re: GitHub cuts AI deals with Google, Anthropic

#311

Post by ianbutler »

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, or any human, can and I can review code very quickly so the overall productivity boost has been great.

It does fundamentally alter my workflow. I'm very hands off keyboard when I'm working with AI in a way that is much more like working with someone or coaching someone to make something instead of doing the making myself. Which I'm fine with but recognize many developers aren't.

I use AI autocomplete 0% of the time as I found that workflow was not as effective as me just writing code, but most of my most successful work using AI is a chat dialogue where I'm letting it build large swaths of the project a file or parts of a file at a time, with me reviewing and coaching.

Re: GitHub cuts AI deals with Google, Anthropic

#313

Post by lifeisstillgood »

I still think it’s worth emphasising - LLMs represent a massive capital absorber. Taking gobs of funding into your company is how you grow, how your options become more valuable, how your employees stay with you. If that treadmill were to break bad things happen.

Search has been stuttering for a while - Google’s growth and investment has been flattening - at some point they absorbed all the worlds stored information.

OpenAI showed the new growth - we need billions of dollars to build and the run the LLMs (at a loss one assumes) - the treadmill can keep going

Re: GitHub cuts AI deals with Google, Anthropic

#314

Post by benreesman »

logicchains wrote: post #193
benreesman wrote: post #173

Earlier quoted context omitted.

It’s all a dice game with these things, you have to watch them closely or they start running you (with bad outcomes). Disclaimers aside: Sonnet is better in the small, by a lot. It’s sharply up from idk, three months ago or something when it was still an attractive nuisance. It still tops out at “Best SO Answer”, but it hits that like 90%+. If it involves more than copy paste, sorry folks, it’s still just really fuck…

>If it involves more than copy paste, sorry folks, it’s still just really fucking good copy paste. Are you sure you're using Claude 3.5 Sonnet? In my experience it's absolutely capable of writing entire small applications based off a detailed spec I give it, which don't exist on GitHub or Stack Overflow. It makes some mistakes, especially for underspecified things, but generally it can fix them with further prompting…

I’m quite sure what model revision their API quotes, though serious users rapidly discover that like any distributed system, it has a rhythm to it.

And I’m not sure we disagree.

Vercel demo but Pets is copy paste.

Re: GitHub cuts AI deals with Google, Anthropic

#315

Post by benreesman »

benreesman wrote: post #314
logicchains wrote: post #193

Earlier quoted context omitted.

>If it involves more than copy paste, sorry folks, it’s still just really fucking good copy paste. Are you sure you're using Claude 3.5 Sonnet? In my experience it's absolutely capable of writing entire small applications based off a detailed spec I give it, which don't exist on GitHub or Stack Overflow. It makes some mistakes, especially for underspecified things, but generally it can fix them with further prompting…

I’m quite sure what model revision their API quotes, though serious users rapidly discover that like any distributed system, it has a rhythm to it. And I’m not sure we disagree. Vercel demo but Pets is copy paste.

We have entered the era of generic fashionable CRUD framework demo Too Cheap To Hawk.

Re: GitHub cuts AI deals with Google, Anthropic

#316

Post by SV_BubbleTime »

gkbrk wrote: post #284
metalliqaz wrote: post #172

Earlier quoted context omitted.

couldn't you s/bullet/ball/ ? or s/bullet/arrow/ ?

You could, but you could also use a model that's not restricted so much that it cannot do simple tasks.

Exactly.

I ended up asking about half pound ball I would throw with a 3600rpm spin and the acceleration phase was 4ms.

It had no issue with that but it was stupid.

Re: GitHub cuts AI deals with Google, Anthropic

#317

Post by 0xFACEFEED »

oogetyboogety wrote: post #279
tanseydavid wrote: post #271

Earlier quoted context omitted.

>> The apparent speed up is mostly a deception. When I am able ask a very simple question of an LLM which then prevents me having to context-switch to answer the same simple question myself; this is a big time saver for me but hard-to-quantify. Anything that reduces my cognitive load when the pressure is on is a blessing on some level.

This might be the measurable "some" non deceptive time saving, whereas most of it is still deceptive in terms of time saved

You could make the same argument for any non-AI driven productivity tool/technique. If we can't trust the user to determine what is and is not time-saving then time-saving isn't a useful thing to discuss outside of an academic setting.

My issue with most AI discussions is they seem to completely change the dimensions we use to evaluate basic things. I believe if we replaced "AI" with "new useful tool" then people would be much more eager to adopt it.

What clicked for me is when I started treating it more like a tool and less like some sort of nebulous pandora's box.

Now to me it's no different than auto completing code, fuzzy finding files, regular expressions, garbage collection, unit testing, UI frameworks, design patterns, etc. It's just a tool. It has weaknesses and it has strengths. Use it for the strengths and account for the weaknesses.

Like any tool it can be destructive in the hands of an inexperienced person or a person who's asking it to do too much. But in the hands of someone who knows what they're doing and knows what they want out of it - it's so freakin' awesome.

Sorry for the digression. All that to say that if someone believes it's a productivity boost for them then I don't think they're being misled.

Re: GitHub cuts AI deals with Google, Anthropic

#318

Post by chairhairair »

tensor wrote: post #306
bob1029 wrote: post #246

Earlier quoted context omitted.

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…

Why aren't you writing unit tests just because AI wrote the function? Unit tests should be written regardless of the skill of the developer. Ironically, unit tests are also one area where AI really does help move faster. High level design, rough outlines and approaches, is the worst place to use AI. The other place AI is pretty good is surfacing api call or function calls you might not know about if you're new to the…

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 negative).

Re: GitHub cuts AI deals with Google, Anthropic

#319

Post by throttlebody »

thih9 wrote: post #239
MuffinFlavored wrote: post #224

Earlier quoted context omitted.

> in practice I’m not noticing a productivity boost. How can this be possible if you literally admit its tab completion is mindblowing? Isn't really good tab completion good enough for at least a 5% producitvity boost? 10%? 20%? Select line of code, prompt it to refactor, verify they are good, accept the changes

> How can this be possible if you literally admit its tab completion is mindblowing? What about it makes it impossible? I’m impressed by what AI assistants can do - and in practice it doesn’t help me personally. > Select line of code, prompt it to refactor, verify they are good, accept the changes. It’s the “verify” part that I find tricky. Do it too fast and you spend more time debugging than you originally gained.…

How does AI learn from it's mistakes ? Genuine question as i have only briefly used ChatGpt and found it interesting but not usefull.

Re: GitHub cuts AI deals with Google, Anthropic

#320

Post by __float »

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…

I'm not sure how many people are like me, but my attempts to use Copilot have largely been the context of writing code as usual, occasionally getting end-of-line or handful-of-lines completions from it. I suspect there's probably a bigger shift needed, but I haven't seen anyone (besides AI "influencers" I don't trust..?) showing what their day-to-day workflows look like.

Is there a Vimcasts equivalent for learning the AI editor tips and tricks?

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