I do a lot of my streaming with Apple TV, but the worst parts about the Apple TV app are in my opinion are:
- Too many promos of other shows before watching a show. This is often for shows I've already watched and am watching. Apple knows which shows I watch. It shouldn't need to give me promos for shows I've watched or am actively watching.
- Poor UX for "Play Next Episode" functionality. If I just finished an episode of a show and I click to watch the next episode, I don't need to see the recap of the previous episode or the intro.
- Speaking of intro, when you click to skip, it usually leaves you somewhere between 5 and 10 seconds from the end of the into, not actually after it.
I haven't been involved in Angular for quite some time. As someone who uses other JavaScript frameworks (Vue, React, Svelte), what am I missing out on? I'd be curious to hear from people who would pick Angular over any of the other big frameworks.
I would just say in general Angular is best if you basically want to build an old school application as a website.. and especially if you kind of hate javascript and web development but focus on the backend as the main part.
In my experience, this is far below the cost the average dev will incur per month so this seems very reasonable to me. And, no doubt there are exceptions for heavy users so they can get some extra token usage when they need it.
unless they changed something in the like 2 months (edit: besides implementing a cap for claude code specifically, since other tools already had caps) since ive left my job there im pretty sure 1500$ is the very max you can use after maxing out free calls, initial budget, then 2 extensions individually reviewed by your manager
higher ups pushed for these last 2 years to be AI focused so I don't think this restriction is a measure of "don't use too much AI" as much as it is a measure of "don't use only 'manual' AI tooling" since we had a dozen more specialized tools in-house running locally or otherwise that didn't count towards the budget
I don’t have experience with the tools Cloudflare has been shipping this year so I can’t speak about the quality, but they have really been pushing out a lot new products and services, no doubt due to agentic coding.
“A lot of people seem convinced that the point of AI coding is to write low-quality code as fast as possible.”
A lot of people think a lot of things, but I don’t think the majority of people think the point of using LLMs is so they can produce low-quality code. Do they produce low-quality code sometimes or often? Of course. But they also produce high-quality code very often. And sometimes they just a “fine”
job.
One of the promises - and there are plenty of cases where it’s met and where it falls drastically short - is that agentic coding tools can help us code faster that is just as good or better than what a human can. One of the other big ideal payoffs is that agentic coding can allow non-programmers to create things that previously required programmers to create.
We can debate as to how successful we’ve been toward the two goals above, but I think it’s misguided to say that the majority of people think LLMs should produce lower quality code.
> We can debate as to how successful we’ve been toward the two goals above, but I think it’s misguided to say that the majority of people think LLMs should produce lower quality code.
Guessing you’re not at FAANG or similar company. For the last 6 months at least there’s been tremendous pressure from leadership (including highly experienced IC engineers) to let AI take the reigns, assumption being that future AI assistants will be able to deal with any level of complexity and tech debt created today.
Given that everyone agrees that reviewing all AI-generated code is impractical (if you let the agents rip at maximum available bandwidth), and that “harness engineering” is at best immature and at worst complete snake oil when it comes to ensuring system stability, maintainability, and quality, I do believe that it’s fair to claim that most engineers are, in fact, supportive of low quality code generated by LLMs.
Fwiw I do see pushback here and there, but only from the lowest rungs on the career ladder - ICs with enough experience to see where this train is headed, but no ability to save it. Management needs to see the results of their policies first, and that will take months or even years to fully play out.
Hopefully not, but there was recent thread with multiple posters arguing that code quality doesn't matter, and quality produced by humans in the past was often terrible. So who cares, ship it was the sentiment. Let the AIs handle the growing maintenance cost, I guess?
Kind of a shocking thing to see argued on HN. Maybe it's just the vibe coders.
The vast majority of corporate-employed programmers write bad code. I think maybe 10% of the people I’ve come across have shown any interest or care in the quality of code they write.
There will be a large majority of people who hold these opinions, because they weren’t capable of or didn’t care enough to write good code in the before times
The real problem with these conversations is that code quality isn’t something we have any kind of consensus on.
To a lot of engineers code quality means upper-case C Clean Code. Other engineers are in the Grug brain camp where they think that premature abstraction is the worst kind of code.
But to your point I think the majority of engineers think they high quality code is anything that compiles or passes their (almost definitely insufficient) test suite.
> arguing that code quality doesn't matter, and quality produced by humans in the past was often terrible
You're conflating two different things. I'm one of the people arguing for the latter, but not because I don't think code quality matters but as a counter to to sudden idealization of handcrafted code.
> A lot of people think a lot of things, but I don’t think the majority of people think the point of using LLMs is so they can produce low-quality code.
Hence "seem". Of course people are not in the habit of describing their process output as "low quality", let alone supposing that that's the point. But when people clearly prioritize speed, and when the result is low quality, it's easy to get the impression of intent.
Eh, I definitely do think that it has become a mainstream take. Not necessarily that we want lower-quality code, but simply that humans shouldn't be reviewing AI code for quality at all - that is, that code quality doesn't really matter and what matters is that the software works.
This is the entire premise of the concept of "vibe coding", and the concept of non-programmers using coding agents. The idea that there aren't large amounts of people and companies doing these things and/or who consider it "the future" is hard to argue.
But how do I know if something works if I don't know how it works? By testing (literally) all use cases, every single permutation of of variables? For complex programs there might not be enough time and energy in the universe to do that.
If I know what addition is, I can look at at a line that does addition and reason about it. If I just check "if it works", for all I know, the actual code is something like
Sure, I can use an LLM to check on the first LLM, and then a third LLM to check on the second, and so on ad infinitum, but none of that, at no point, can give me what "knowing what addition is" gives me.
It's kinda like cheap/fake concrete: If you know something about concrete and what concrete is being used, you can roughly tell if it will last, what it will withstand. If you just go by "seems to work", "looks good", you get collapsing bridges and buildings after a few years, during heavy rainfall etc.
> We can debate as to how successful we’ve been toward the two goals above
No not really. These are separate questions from what the article posits. The argument is about how do we use these tools, our approach as developers, and if the results are going to be as rosy as advertised.
I’m not a CPA, but aren’t there plenty of legal ways to divest in a business where you’re not directly involved, but where you can still get a share of any profits?
When people read these links, I encourage them to assume that the author/creator left out part of the story for convenience or due to lack of knowledge (specifically the language and customs around legal issues in Japan).
Her story does not jibe with any of my experiences, direct or indirect, with law enforcement in Japan.
- Too many promos of other shows before watching a show. This is often for shows I've already watched and am watching. Apple knows which shows I watch. It shouldn't need to give me promos for shows I've watched or am actively watching. - Poor UX for "Play Next Episode" functionality. If I just finished an episode of a show and I click to watch the next episode, I don't need to see the recap of the previous episode or the intro. - Speaking of intro, when you click to skip, it usually leaves you somewhere between 5 and 10 seconds from the end of the into, not actually after it.
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