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GitHub cuts AI deals with Google, Anthropic

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Re: GitHub cuts AI deals with Google, Anthropic

#461

Post by epolanski »

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 …

Maybe you should set the right expectations to find the right use.

There's plenty of copilot and cursor users out there, and developers are really not the kind of crowd that likes to pay for development tools.

Re: GitHub cuts AI deals with Google, Anthropic

#462

Post by fullstackchris »

pama wrote: post #421
0xFACEFEED wrote: post #354

Earlier quoted context omitted.

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…

Finally found a comment down here that I like. I'm also with the notion of tests and also iterating until you get to a solution you like. I also don't see anything particularly "terrifying" that many other comments suggest.

At the end of the day, we're engineers that write complex symbols on a 2d canvas, for something that is (ultimately, even if the code being written is machine to machine or something) used for some human purpose.

Now, if those complex symbols are readable, fully covered in tests, and meets requirements / specifications, I don't see why I should care if a human, an AI, or a monkey generated those symbols. If it meets the spec, it meets the spec.

Seems like most people in these threads are making arguments against others who are describing usage of these tools in a grossly incorrect manner from the get go.

I've said it before in other AI threads that I think (at least half?) of the noise and disagreement around AI generated code is like a bunch of people trying to use a hammer when they needed a screwdriver and then complaining that the hammer didnt work like a screwdriver!!! I just don't get it. When you're dealing with complex systems, i.e, reality, these tools (or any tool for that matter) will never work like a magic wand.

Re: GitHub cuts AI deals with Google, Anthropic

#463

Post by SoftTalker »

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…

> The alternative, I fear, is 90% of the software we use exhibiting subtle goofy behavior and just being overall unpleasant to use.

This sounds like most software honestly.

Re: GitHub cuts AI deals with Google, Anthropic

#464

Post by Bjartr »

bongodongobob wrote: post #338
tomrod wrote: post #297

Earlier quoted context omitted.

How long are you willing to iterate to get things right?

If it takes almost no cognitive energy, quite a while. Even if it's a little slower than what I can do, I don't care because I didn't have to focus deeply on it and have plenty of energy left to keep on pushing.

I'm constantly having to go back and tell the AI about every mistake it makes and remind it not to reintroduce mistakes that were previously fixed. "no cognitive energy" is definitely not how I would describe that experience.

Re: GitHub cuts AI deals with Google, Anthropic

#465

Post by enumjorge »

AIorNot wrote: post #427

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 ma…

I'm not sure why people can't be humble enough to accept that we don't really know what the future will hold. Just because people have underestimated some new technology in the past doesn't mean that will continue to be true for all new technologies.

The fact that LLMs currently do not really understand the answers they're giving you is a pretty significant limitation they have. It doesn't make them useless, but it means they're not as useful at a lot of tasks that people think they can handle. And that limitation is also fundamental to how LLMs work. Can that be overcome? Maybe. There's certainly a ton of money behind it and a lot of smart people are working on it. But is it guaranteed?

Perhaps I'm wrong and we already know that it's simply a matter of time. I'd love to read an technical explanation for why that is, but I mostly see people rolling their eyes at us mere mortals who don't see how this will obviously change everything as if we're too small minded to understand what's going on.

To be extra clear, I'm not saying LLMs won't be a technological innovation as seismic as the invention of the car. My confusion is why for some there doesn't seem to be room for doubt.

Re: GitHub cuts AI deals with Google, Anthropic

#466

Post by hhdhdbdb »

AIorNot wrote: post #427

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 ma…

I dont see a young/old divide when it comes to AI. Altough there is a young/old divide in familial responsibilies and willingness to be a chip on the VC's roulette table.

Re: GitHub cuts AI deals with Google, Anthropic

#467

Post by WgaqPdNr7PGLGVW »

outworlder wrote: post #253
WgaqPdNr7PGLGVW wrote: post #223

Earlier quoted context omitted.

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.

It's worse than that. Now the balls of mud are distributed. We get incredibly complex interactions between services which need a lot of infrastructure to enable them, that requires more observability, which requires more infrastructure...

Yeah. You can fit a lot of business logic into a 100kloc monolith written by skilled developers.

Once you start shifting it to micro services the business logic gets spread out and duplicated.

At the same time each micro-service now has its own code to handle rest, graphql, grpc endpoints.

And each downstream call needs error handling and retry logic.

And of course now you need distributed tracing.

And of course now your auth becomes much more complex.

And of course now each service might be called multiple times for the one request - better make them idempotent.

And each service will drift in terms of underlying libraries.

And so on.

Now we have been adding in LLM solutions so there is no consistency in any of the above services.

Each dev rather than look at the existing approaches instead asks Claude and it provides a slightly different way each time - often pulling in additional libraries we have to support.

These days I see so much bad code like a single microservice with 3 different approaches to making a http request.

Re: GitHub cuts AI deals with Google, Anthropic

#468

Post by dham »

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,…

With React, the guesses it makes around what props / types I want where, especially moving from file to file, is worth the price of admission. Everything else it does it icing on the cake. The new import suggestion is much quicker than the Typescript compiler lmao. And it's always the right one, instead of suggesting ones that aren't relevant.

Composer can be hit or miss, but I've found it really good at game programming.

Re: GitHub cuts AI deals with Google, Anthropic

#469

Post by malux85 »

Nullabillity wrote: post #453
malux85 wrote: post #447

Earlier quoted context omitted.

Theres a big difference between being a happy customer and being a shill.

Holding stock is not being a "happy customer". I may be happy with the headset that I bought, but the difference is that I don't make money if you buy an identical one.

I wasnt talking about holding stock, I was responding to this comment you said:

> 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.

Oxford dictionary defines a shill as "an accomplice of a confidence trickster or swindler who poses as a genuine customer to entice or encourage others."

So the difference between someone shilling and being a satisfied customer is an intent to decieve. How is it "difficult to not pose as a genuine customer to entice or encourage others" ?

Re: GitHub cuts AI deals with Google, Anthropic

#470

Post by ENGNR »

AIorNot wrote: post #427

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 ma…

I think a lot of the criticism is constructive. Many of the limitations won’t just magically go away - we’ll have to build tooling and processes and adjust our way of thinking to get there. Most devs will jump across to anything useful the second it’s ready, I would think
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