I'm sorry but that data does not at all square with my experience. I'm seeing 2 days+ as the average and I haven't seen sub-24hrs in months. I oversee ~20 apps and I can tell you iOS review times have been trending upwards for the last few months.
Apologies, I used to use appreviewtimes .com [dead], which scraped tweets and was pretty accurate, but is dead now. I posted what seemed to be a decent replacement, but will take your word it’s not.
Edit: was going to update the earlier comment but just hit the 2 hr mark.
For all I know it is accurate for them but I encourage you to hover on the bars and see the min/max. That's where the issue is. I wrote more about it here [0] but the TL;DR is that it's wildly inconsistent, sometimes it can take a few hours or <12 hours and sometimes it can take a couple days. It's impossible to plan around and nothing drives me crazier than having a fix written but waiting for Apple to get around to reviewing it.
Easily solved by adding an interstitial whenever a URI becomes replaced and is therefore no longer immutable, and showing the history of what it used to point to as well (in case you're coming along from an old link). By default, after 5 seconds, it could redirect to the current destination.
it’s infinitely easier to become an alcoholic by buying alcohol at a grocery store. brewing is pretty much the least direct most delayed gratification way to get drunk. i guess it can be pretty cheap if you optimize for that but it sounds like jim made enough money and high flying friends it’s unlikely to be major factor.
Note: I apologize and rescind my previous comment about not arguing in good faith.
My point isn't that home brewing makes alcohol easier to obtain; clearly it doesn't, as you pointed out.
Rather, it provides a respectable rationale for having a beer (e.g. testing a batch, checking the bottle fermentation, seeing how it pairs with a meal).
Drinking is now part of a productive, interesting hobby. For most people that's harmless, but for a vulnerable individual, the hobby supplies frequent opportunities, a steady supply, and an intellectually respectable reason to consume. That's all.
Though, after you've home brewed the beer, you've now got potentially gallons of beer in a giant pot that you have to bottle yourself. Or you could be lazy and just drink it yourself. True, you could just go down to the store and grab a 30-rack of mass produced beer if you wanted to be an alcoholic, but having a vat of beer in your kitchen that isn't going to drink itself and is gonna go bad if you don't, is a different kind of peer pressure.
You can get handles of vodka for 11 dollars. You can buy listerine for even cheaper and drink that. People brewing their own beer may be alcoholics but they are doing it for the hobby or to customize the flavor. Real down in the throes of addiction alcoholics are not becoming chemists for their fix with how cheap the mass produced stuff is.
If you want to find people doing that you look for the illegal drugs that haven't had wide spread industries drive down the price, like meth.
Kegerators are easy and quite affordable to build.
I absolutely have friends who stopped home brewing because they realized that having a tap of readily available beer in their house wasn't a good idea.
You must not drink or like beer. Brewing something until it ferments into alcohol is the most basic thing ever. There is the very simple problem of taste that is the issue.
I've been noticing that many new projects that would have been written in Python or Node a year ago are starting to be written in Go, Rust, etc.
Theory: people realized there’s little benefit to Python for agents. As Zep wrote, an “agent is a long-running, concurrent, I/O-bound process that spends most of its time waiting on a model, a tool, or a human[1]” — not a particular strength of Python.
I'm wondering if you'd considered Go (or others—Go’s just my fav ) before landing on Node, and more broadly whether you've noticed a similar pattern?
> As Zep wrote, an “agent is a long-running, concurrent, I/O-bound process that spends most of its time waiting on a model, a tool, or a human[1]” — not a particular strength of Python.
That sounds exactly like a strength of Python, no? Python is excellent at working IO blocks and waiting in general being interpreted language with first-class async support.
Right. Python is excellent at waiting on things instead of actually doing things, and on the off case it does do things, most of the time it's really juggling strings around the thing instead of doing it.
s/
I generally don't write Python, but like others, I disagree with GP too. In fact, a lot of my work involves Python being written now, simply because that's what LLMs like to write.
Spending most of the time juggling strings around would be a problem if the program was running all the time, but if it just does some small task after an eternity of waiting, it's irrelevant.
Fully agree with you, and I didn't make my point well — I should have been more clear.
While Python and Node have undoubtedly seen a huge spike since the advent of mainstream AI, relatively recently I've begun to notice a small but growing trend of people switching away from or back to languages like Go and Rust. In an absolute sense, yes, Python is still dominating and growing.
The trend I have noticed is a very small but growing cohort of folks who are coming back to languages like Go and Rust.
I suspect a lot of the Python and TypeScript code is getting prompted by folks who don't know any difference between dynamically typed and statically typed.
Are you familiar with the Go standard library? It’s notorious for its comprehensiveness and how often you can write zero dependency applications as a result.
And there’s a reason: the Go designers were huge Python fans, so leaned on its design quite a bit. They essentially wanted to make a modern Python with first class support for static typing and highly scalable parallelism, not just concurrency.
It's too late to edit, but in retrospect I realize that the first sentence of that comment sounded awfully snarky, and I didn't mean it to. I apologize, and please trust it was asked in good faith.
In the early days of LLM coding, it seemed to be much better at Python for whatever reason. I was never a big Python guy, but I got better results so I ran with it. That definitely doesn't seem to be the case anymore. Last week I asked Codex to mash up Super Mario Bros and Contra ROMs and it just did everything in straight assembly and absolutely crushed it. It couldn't do that 2 years ago. Python is just momentum and I think it's going to die down now that the models are much better.
I agree with that — One of Go's biggest strengths is the flip side of an arguable weakness: it's not a very expressive language.
The positive of that is that if you ask three people to write the same function, it'll most likely end up nearly identical. You don't get codebases where different areas are written using different styles and different patterns.
This same effect applies equally to coding agents.
I think it's because python is far more approachable/ubiquitous than go/rust. It's the entry level language for many people from all disciplines of life. Scientific community uses it, data science uses it.
Golang/rust however are very convenient to distribute. Small, portable, fast exe's are very nice. With agentic coding golang/rust are now accessible to a lot more people.
I see where you're coming from, but to be honest I respectfully disagree. If all you mean to do is writing small one-off scripts then sure Python may be the right tool[1], but when you're doing something more complicated Go is just simpler. And for an LLM, Go is even better for all the reasons mentioned in sibling comments and OP.
Yes, now that humans write less than 99% of code, the most important criteria for a language isn't readability, which I'd argue was always Python's main selling point, but the underlying runtime. There are practical limits to how fast a Python program can run either under I/O or CPU bound compared to other popular and mature languages with extensive libraries, like Elixir, Go or C++, depending on your use case.
I actually don't read any code! For generation I use simulations to ensure satisfactory error rates, for deterministic code I use test suites, and for user interfaces I use good ol' intuition! So I guess you could say I just write extra code that makes reading the code unnecessary. I find it quite strange to be honest! But this is the most effective way for me to ship now.
So you're fine with your code having unintended behaviour, as long as that unintended behaviour passes a test that the agent wrote?
My preferred approach is to read and understand everything the LLM produces AND have it create test suites (which I also read and understand). The LLM can help you with that too - just have it breakdown and explain the code at each iteration.
If it's code for a pacemaker, it should be reviewed by multiple humans. If it's code for an unimportant side project, I will never read it. Between those extremes are shades of grey.
Part of our job in this new era is to understand the worst-case consequences of a bug given how the code interacts with the world, then allocate our effort based on that understanding. This can only be done on a case by case basis.
Not really. I test the output thoroughly, I examine the thinking process, I go through the diff to see if anything jumps out but I my thinking process/the way I work has changed. Low level programming thinking has gotten atrophied it seems.
Ironic phrasing, given the Catholic Church wants authority to decide what is demonic while acting like demons. Why is the comment so plainly aggrieved? Is the Catholic Church a victim here?
Even as your sanitized claim, where is the evidence?
I'm not a Catholic (nor religious at all), and do question whether schools truly are worse than churches in terms of how children are treated.
But that's not the point. You made up a quote I didn't say ("demonization"), and accused the former poster of doing something they weren't: defending the church.
Saying that schools are worse yet ignored is not defending the church. It may also be incorrect, but that's a separate assertion.
That was in the comment that started this chain. Are you using an alt? I'm not sure why this is so hard for you to follow. If I were you I would take a breath and read the chain again.
Here I'll help you:
> Just about every kid goes to school though, so people just prefer to sweep that under the rug and focus on targeting organizations they are not a part of or disagree with because they're easier to demonize and make fun of.
In what world is that useful to your sanitized claim? Is it not an obviously underhanded apology for the conduct of the church? Is the aggrieved nature of this really lost on you?
Some HN users probably are, but not all, and I doubt not a majority. A majority might not be religious, but not being religious does not automatically mean anti-religion. There are occasionally comments that show an espousal of a god that do get upvotes.
Calling someone's god, an "imaginary friend" is probably a trait of someone very anti-religious though. I haven't read all the different religious texts, but I highly doubt any of them call their god a friend. Perhaps Jesus could be considered friendly, but I don't think the Bible says that a Christian must consider Jesus as their friend. I think it's more like how parents should be parents and not friends. I imagine in most if not all relgions, gods should be gods and not friends.
Please tell me which part of your brain is engaged when you converse with your imaginary friend?
Is that really the best reply you could conjure? Maybe you can produce some evidence absolving the Catholic Church here? Or are you also an apologist for institutions that call themselves sacred engaging in systemic sex abuse?
While I am as anti religious as you, probably not the best discussion method.
Instead ask them if their church ever taught them anything on how to prevent sexual abuse, in both children or adults. Quickly you'll find the apologist for the church saying it's not the churches job even though they are in charge of children and vulnerable adults almost all the time.
FWIW, the Catholic Church and the other Church I go to, both require training on how to prevent abuse, sexual and otherwise, towards children, if you're in a ministry that works with children. That's why their rates of abuse are lower than other institutions such as schools.
I must be misunderstanding something, because I can't imagine that training would-be predators would significantly reduce the rates of abuse.
Perhaps I'm mischaracterizing it, and it's about training those around potential abusers on how to recognize signs of abuse and adopt tactics that prevent it? Or it's about training _children_ to recognize what's unacceptable and how to report it safely? Or something else entirely?
Regardless, your conviction in the efficacy of the training grabs my interest. Could you share more about it so I'm not working off of incorrect assumptions?
You also mentioned that their abuse rates are lower than schools. Do you happen to have a source for that — I’d be interested in educating myself on that as well!
Truly enjoyed this article, but hate to admit one thing: I'm so burned by AI slop that once I noticed this seems to have been "assisted" by an LLM, I got irrationally angry because I felt tricked.
It hit me at the end, when I read this:
> The idea behind Ambiance is simple: the model's priors [...] Everything else here is just in service of that.
I've noticed "in service of" take off similar to "load-bearing" with LLMs, and the whole structure just pattern matched to Claude for me.
I went back and scanned it over again, and noticed several other tells:
* "Think of U/L [Unix / Linux] as a motivating analogy rather than a direct comparison."
* "Priors" _and_ "a priori" used in the same article.
* "A real kernel […]. The Ambiance Kernel […]. The Kernel […]." — LLMs love this pattern.
To be abundantly clear, *I'm not calling this AI SLOP*; it's obvious that a human put a lot of thought into this, gives a shit about the topic, and shared interesting ideas leading to a productive discussion. I really did like it.
There's just something empty or hollow about the LLM style; paraphrasing Joni Mitchell "there's something lost and some thing gained" [1] when using AI. Your writing, your code is more consistent, more structured, more planned out — generally better but in a way that loses the character behind human writing.
[1]: From "Both Sides Now", a great song about looking something from two perspectives: youthful innocence, and jaded cynicism. Listen to the original 1969 version first, and then the 2000 remake as you can tell she's singing from the respective perspectives. Deeply meaningful song!
I experience this too, but the danger is is making assumptions based on "tells" which might just be how the user wrote the post. It's a situation now where if someone authentically writes something, but happens to rub up against some arbitrary "tell," they flip a bit in the reader and get their work rejected. For example, I used em dashes fairly regularly in my writing before AI started convincing everyone that the mere presence of an em dash is the AI tell, so I actually stopped using them, just to avoid this backlash.
I hear you. Coincidentally, I was actually called out just last night for a message with em dashes:
“Are you AI-ing me? Em dash giving you away”
It’s a pretty load-bearing (lol) example, yet it was clear in context it wasn’t serious. I’m beginning to notice people getting pretty good at detecting AI content, which I find reassuring.
It makes sense: AI-written prose is basically the homogenization of all styles of writing into a single voice, so it’ll stand out against the unique personalities we are used to seeing. It is just taking a minute for the average person to gain literacy — but it seems to be happening rather quickly, again unsurprising since we’re such social monkeys with a lot of our 15 watt brains dedicated to socialization and identity recognition.
I believe you and OP are in agreement — they were saying that the 2019 book had them, therefore the terms _do_ predate AI. Your point that AI was being trained on material than is load-bearing (lol) but in agreement with OP, not contradictory.
Only mentioning because your "actually" may imply you thought you were disagreeing, when in fact it's one big happy family!
If you're actively looking for a job, you should have some familiarity with the common dev stack when you're looking. Today you should be comfortable working on a Mac, know Bash / Zsh, a little bit of Vim for SSHing, git, docker, react, postgres, etc.
If you don't, spend a few weeks before you start your search. You're almost definitely going to need them. Unless you're in a niche where the common stack is different.
This isn't me gatekeeping or something, it's just common sense. When 80% of the jobs are Python + Javascript / Typescript, running in Docker, using Postgres, using React on the frontend, FastAPI on the backend, and git plus github for deploying and reviewing, you're going to stumble without cursory knowledge. You don't need to be an expert in it all…
> This isn't me gatekeeping or something, it's just common sense. When 80% of the jobs are Python + Javascript / Typescript, running in Docker, using Postgres, using React on the frontend, FastAPI on the backend, and git plus github for deploying and reviewing,
Then I don't apply. I'm not interested in working with garbage tech.
Interesting! I'd love to hear what type of work you do where you can get away without any of those because frankly I think most of those are pretty garbage too.
Postgres is decent for a free ($$$) database, although it's lack of clustered indexes and in-place updates (its MVCC approach) sucks for many use cases. I find it a sensible default but not the best at any one use case.
Python, frankly, sucks nowawadays. Maybe it had its time, but there are so many better lingos now. It's got type hints that are ignored, really bad patterns ("dependency injection" that's really just the singleton pattern, FastAPI encourages you to open a db connection and a transaction at the front of every request and commit at the end while you're making other requests, writing to disk, etc), and it's slow in both user experience and runtime (no real parallelism).
But generally I have to make some trades to get a great job. I love Go, personally, and the incredible simplicity it encourages.
Seriously, if you'd be willing to share, I'd love to hear what you do!
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