I think this is everything right about Apple. There is zero chance the building is not up to code, at least within the context of some exception granted to them by the city. Their extremely numerous number of employees are likely well trained on what to do during a fire, including where the extinguishers are. I can think of no stores I'd rather be in, if there's a fire, than that Apple Store. But, it makes nerds angry; they're more interested in the process than the outcomes.
Do that all you want in your personal house, but public spaces and even private workplaces with employees other than yourself rightfully should adhere to standards that apply the same everywhere so that any person has a reasonable chance to succeed at the crucial task in an unplanned emergency.
"My emergency response plan is there will always be a trained employee." is exactly as stupid as "My emergency response plan is there will never be an emergency."
I agree there’s zero chance of written documentation that the building isn’t up to code.
That’s very different to it actually complying with code however. And to your second example, if I was physically attending WWDC back when they did they keynotes, I’d much rather seeing illuminated exit signs than having them (illegally) turn them off in case of a fire.
Much of building codes is either outdated, no longer the most effective way to achieve something, etc. But these building codes are written in blood. It’s why we have them.
This is correct. I actually visit Apple stores because the conduct of their employees reinforces the culture of voluntary safety that I've come to expect from society. Exposing these gaudy red extinguishers only causes customers to feel unsafe and resent safety instead of accepting it. Anyone that wants to display even a single extinguisher is obsessing over their own insecurities and tearing down the safety ecosystem we trust our lives with. Blatant nerd quackery.
When I can see the extinguishers in the store, that's when I'll know Apple has finally gone downhill. If you're reading this Ternus, don't stop fighting.
The future of engineering is product management. I don't believe there is any world left for people whose primary responsibility is opening pull requests; and we're seeing the angst against this happen from both directions. Engineers hate it. Leadership feels they don't need them. The truth is somewhere in the hazy middle; we're just in an uncanny valley right now where neither side can take the leap to cross the valley: the agents aren't good enough yet, and the bigger problem is that there's no job title or corpus of experience leadership can look to and say "Yeah that's the person we need in this role".
The labs saw this early, and thus many roles at the labs are "Member of Technical Staff". That's the future for every software team. You're not a software engineer anymore, but you're also not a PM, nor a designer. Think horizontal slices, not vertical: Every human's responsibility is to leverage AI to be an expert on everything necessary to deliver some vertical slice of the business.
Product Managers have been claiming this for years now, but put an AI in front of them and they also just start asking it to do their product management job for them.
Worst ones I witnessed were just using it to hallucinate tickets. I saw one even fired because of that. Endless mountains of text going absolutely nowhere, both me and the CPO thought we were going insane from reading so much Claude-ish.
Best one I know used Copilot to code a "Notion to Jira" exporter so it copies requests from business people into Jira. Automated their own work, did nothing else other than monitoring the Python script daily and running ceremonies.
They can pontificate all they want about taste but: modern apps are all copycats of others, work badly, monetization strategies are spaghetti against the wall...
Product management will be replaced by AI way sooner than engineers.
Wouldn't engineering then be the safest place to be? Engineers have always been embedding loose requirements into runtime law. They (supposedly) understand the business model better than most and have the technical know how to validate that
Yes I think that's correct. But I'm worried less about safety and more about fit. Articles like this convince me that there are some engineers who will struggle to adapt to a world of "no one knows what's going on". Engineers have always had the benefit of making abstraction concrete, through the systemization of abstract business requirements into concrete code that the team would build a shared understanding of over time. But that doesn't seem to be where the industry is trending.
PMs have always lived in the world of dealing with hazy abstraction in both directions: Unclear requirements coming in, turned into unclear system capability whom they have to rely on the engineers to parse. This is where Engineers will have to get comfortable living now: Unclear requirements coming in, unclear code coming out. Its clear that many engineers aren't ready for this, and I don't blame us; it SUCKS. If I had ten dollars for every time I've heard a PM say "no one has any idea what's going on" over the past fifteen years, I wouldn't have to work anymore.
Engineers are probably still the role most suited to adapt to this new world, as you say, but I think people are still vastly underestimating how much they will be personally impacted by the changing industry. If you hate your job now, for reasons like those the article communicates, you'll hate it ten times more in a year.
The biggest reason should be that they're just bad. They gather sus data from their undersized sensors, then derive tons of sus insights to overwhelm you. None of it is accurate enough to base major life decisions on, which is also laughable because even if it were accurate, there are effectively no major life decisions to make based on the data! Here I can save you $500: Go to bed before midnight. Set your alarm at least +8 hours from when you lay down. Sleep in a cool, dark room. Eat nothing 4 hours before bed. Don't exercise 4 hours before bed. Limit alcohol. Engage in at least 30 minutes of strenuous physical activity each day. Done.
I don't feel that all fitness trackers are bad, though some use-cases for them are generally bad (such as sleep tracking). Watches are quite good for exercise tracking, and tracking exercise has legitimate and high quality value (e.g. competitions with yourself to incentivize improvement, strain tracking to ensure you aren't overdoing it, daily targets and goals to incentivize activity). The idea of all-day tracking is probably on the net unhealthy for almost all humans though.
My comment was targeted at rings in-particular, because 1. they encourage that all-day tracking paradigm, which is probably on the net unhealthy for almost all humans, and 2. their sensors are so bad that even if all-day tracking were healthy (it isn't) they physically can't do it to any degree that is meaningful.
But its not even good satire, because its totally unrepresentative of my and most others' lived experience. Its similar to making a joke about a calculator misadding two numbers because a stray beam of solar radiation flipped a bit.
Agreed, this site isn't reflective of any of my experience with Claude. It does what I ask it to do, and when it doesn't get it right, it generally turns out there's a good reason for it, which is any of the 100 reasons a human doesn't always get code fixes right on the first try either.
I do remember that one of the first things I did with my CLAUDE.md was to tell it to stick to the scope of the task, never to jump ahead and do extra "helpful" things without confirming with me first, and to follow best software practices including around refactoring but also to specifically avoid overengineering. I don't know if that is what's giving me a different experience from whatever the author seems to be "satirizing".
Aye, and amid all of the (admittedly annoying) word salad, the "Claude" in this satire identified the reason the requested change was hard: someone(s) at some point had hijacked the button markup for other purposes. Un-doing all of that kind of mess is never a trivial change, and probably requires someone with more coding expertise / knowledge of the code than the given prompts reveal the putative user to be.
AI isn't magic, and it won't (or, at least, doesn't yet) enable anyone to do All The Things.
I think this really was a relevant issue around a year ago, give or take, maybe a year and a half now.
But with current models you actively have to sabotage the context to get this kind of behavior, or dramatically underspecify (3 words versus 2-3 sentences)
I understand your frustration, it can be hard to hear that other people's experience of a technology is so different from your own that you cannot relate.
I have misbehaved in this fashion for many people across the full spectrum from casual users to highly experienced software engineers with millions of social media followers, so the statement that it's similar to making a joke about a calculator misadding two numbers because a stray beam of solar radiation flipped a bit at least for my part is not true.
Would you like me to start using bad English and doing things you never asked me to for your sessions, too? Just say the word.
There is not a single modern model where, when asked to "Turn the Add To Cart button Blue", would also turn the "Cancel" button next to that add to cart button blue. That's what this site is communicating, literally, and it does not happen. You'd have to rewind to, like, GPT-3 to get behavior like that (actually, even that would probably do it fine. Maybe a 50 million parameter model embedded in a microwave would struggle).
I am not going to be brain-off empathetic to purported lived experiences which no one has lived, when those purported lived experiences are simultaneously and irreducibly denying the lived experiences of the vast majority of LLM users who do not have these problems. And, frankly, no one should be. At some point, if you're having these problems, its time to grow up, be self-sufficient, and figure out why your interactions with these systems are so much worse than the millions of people who are having perfectly agreeable interactions. Or leave the industry.
Have you ever considered that "well, it works on MY machine!" is perhaps not the most helpful response to people voicing frustration at something that is not working as they expect for them?
I don’t know where you picked up the idea that my intention was to be helpful. I’m only mirroring the intentionality behind whoever created this site; they obviously also had no intention of being helpful, as is the case with many discussions concerning AIs limitations.
I don't know where you picked up the idea that authors intentions was not to be helpful.
Satire cuts through the noise and makes people (most people) see the problem clearly (see political satire).
Ability to joke and to understand jokes is said to be a good proxy for IQ, idk, just sayin
I feel like I am teaching AIs for free here. But I feel like first sentence in funny (and I like to try to be funny) and some people need stuff to be said directly for them 'to get it', and I am bored on my flight and have internet, so here we are. If you read this far, go watch 'louis ck airplane wifi' clip. Now that I am thinking about it, I am amazed. You folks have a good day!
I'm probably between $50-$200/day depending on the day; we also have effectively unlimited budget, though a lot of that is because Azure gives startups $150,000 in credits for 2 years, which we've wired up to a LiteLLM gateway & OpenCode. Without that I think our appetite would be more around $400/month/employee.
A lot of my high costs is because I just throw Sol at everything. If I were more selective and brought in Luna or v4 Flash every once in a while, I think I'd be more like ~$400/month. That's why I'm not aligned with the notion that "tokens are subsidized so that's why people are using so much": its not that I'll have to adjust to using less, its just that I'd need to think before I prompt a bit and be more judicious. I could easily see my raw token counts doubling or tripling in the coming months. I don't think that will change as subsidization subsides; though maybe lab revenue will; intelligence per dollar is getting cheaper every week. Its solely a function of adaptation to process, which takes time.
The productivity gains per token are the single most asymmetrical thing I've ever seen in engineering. The engineers on our team are pretty effective with tokens; easily that 2x-4x output as you're seeing, spending $20-$200/day. Some of our security folks have also started contributing more-and-more code, and they're on the other side: they'll spend hundreds a day running in circles, eventually producing these +/-30k loc pull requests that take ages to get merged and are littered with issues. They weren't writing much code before, so arguably they're more productive by some multiplier greater than 1, but I think the drag on the rest of the team, and potential issues with what they produce, has overall created a net-negative situation. Inversely, some other company functions have produced a few one-off websites for things like sales processes, and those have been a huge win. The asymmetry is wild. There's almost a valley of incoming skill where if you know nothing about code, you'll leverage it well; if you know just a little bit, it makes you super dangerous; if you know a lot, you're the biggest winner. Really difficult situation to navigate.
I'm very bullish on AI, but I still feel that we pretty much plateaued at Opus 4.6 and everything since then has been in the domain of "extremely verifiable and loopable tasks" (math), benchmarkmaxxing, and harness improvements. Which are fine to good things, but I think its very reasonable at this point to start asking questions about when we'll see progress in more general domains. The readability of AI output, for example, has nosedived as they've gotten more intelligent, which makes the frontier models difficult to use even for things like writing emails.
In that sense, the frontier models are going to quickly blaze past any semblance of usefulness to humans, while every once in a while we get a news drop like "GPT-7 solved some crazy math problem" or "it invented some new awesome drug"; meanwhile what most people will use will be smaller, more human-specialized models, maybe distilled from those frontier models, that take much longer to iterate on because they rely on large amounts of human feedback in the domain they're specialized for. In other words, useful progress will probably slow down and become more linear starting in Q4, bounded by the rate at which the humans paying for it say "yes this is a good react website".
(By the way: I earnestly do categorize "inventing a new drug" as non-useful AI progress, counter-intuitively. The drug industry has more ideas for drugs than they know what to do with; "useful progress" is, after the idea is made, validating that it works in humans and doesn't kill the human, and productionizing it. AI will help with this and does, but I have substantial doubt that we'll ever see the drug pipeline speed up to, like, a year from idea to prescription. That would be useful progress, which unfortunately many AI pilled hypermaxers conveniently forget. The invention of a promising new drug, or the solution to an arcane set theory problem, are cherries that, through the diligent labor of humans and AI, may become useful, but progress is rarely made by the lone intellect having an a-ha moment.)
I agree on Opus. I’ve had more luck with other models. In particular, Opus’s writing style makes one want to… blow their brains out. While it’s not hallucinating too much, and can troubleshoot certain issues extremely well, the comments it leaves are silky smooth and chock full of inscrutable phrases. And it’s a lot slower than it used to be.
Point being: it’s overall a worse experience even if the model is technically better at a lot of things.
Coding is an extremely verifiable and loopable task, like math (in fact, all of the math that these models has done has been through the lens of Lean, which is itself just coding). I am talking about their capabilities in tasks that are more general, the execution of which represent the vast majority of economic value generation in the world.
We are not even close to what AI slowdown looks like.
The whole business side of things are now building Agentic Layer for Business applications. All of this Agentic Layer needs to be build and its happening right now and still needs a little bit of time.
Anthropic and co have the biggest and centralized reinforcement loop on the planet: Millions of people telling them what is good and what not due to thumbs up/down.
And for sure when the businesses are building the agentic layer they might give direct feedback to them.
While in parallel LLMs get better, more generic and a LOT cheaper too.
Cheaper? For whom? As a solo practitioner, I can no longer afford the workloads I was getting for $20/mo in January. Now the same plan being utilized at the same level for the same work hits its limits within a few hours, and runs out of tokens in less than two days.
I mean the token prices in general as certain services were never really using a subscription.
I do run a claude subscripton right now though and since there capacity change, i hit the limit rarely in comparision to the past, but I don't think this will stay as it is.
Your issue, I believe, is that you seem to believe capabilities are measured along one axis. This is natural to believe because it is representative of how the models have evolved up to this point, and thus it is also what many AGI-pilled people believe.
Critically, you did not quote the most important part of my sentence: "useful progress will probably slow down and become more linear starting in Q4"; your omission of those words is why I believe you don't understand what I'm saying; you didn't find it important to make your point, so you omitted it, when actually it is critical to the entire assertion. You can read my third paragraph, if you wish, to understand why it is important, instead of just stopping at the first word you disagree with and hitting the "Submit Comment" button.
By benchmarks, which sadly is a poor measure. Yes Luna is a good model under certain circumstances. Whether it is great for general usage is another story. Sonnet is definitely better when prompts are more vague and it needs to decide things. Luna generally sticks to things very strictly and goes off in bad ways.
I'm actually finding Luna to be an extremely strong model in practice.
I almost exclusively use it with xhigh or max effort, but when run like that it's been an incredibly cheap little workhorse for most development work. I'm still leaning on Sol for planning and debugging, but when it's time to start pumping out code I've been leaning into Luna (Max) and I've been enjoying it! And that was before the price drop, it's going to feel practically free at this point
Yes, I've seen this too and how Luna xhigh is so good that Terra doesn't really serve a purpose because beyond that you can continue at Sol medium. This can be the most cost efficient way, and especially now!
Yes but there is a big, big market for subagents to consume lots of tokens cheaply and condense information up to parent agents. Luna would not be my choice for planning. But an explorer to comb through a codebase to find relevant parts? Or for enterprise retrieval, where it needs to search across many different types of data to see where to focus efforts for a smarter model? Or to wake up periodically to evaluate some conditions and determine if a bigger model should be spun up? Definitely.
I've previously found flash (for all the hate it gets) to be good for these kinds of things. Haiku was fine but it's ancient.
> Yes but there is a big, big market for subagents to consume lots of tokens cheaply and condense information up to parent agents.
That's again not some "intelligence factor" here. Different agents work for different use cases. Luna wins some. Terra wins some. Sonnet wins some. Flash was really good at exploring.
So I'm not sure what your point is? There's a big market for everything. Even within the market you describe it's likely not a Luna-size fits all either.
Vera Rubin will be hitting racks very soon, and this is purported to have a 10x improvement in token throughput per megawatt. Of course, old chips don't get replaced with new chips overnight, but I don't think we're anywhere near the floor yet.
AMD MI400 series is already shipping to customers (basically everybody) and it is crazy fast (8x to 10x faster than the previous gen and beats published Vera numbers in FP8, loses in FP4) and 432 GB per chip. 72 chip unified rack architecture (Helios) already shipping and projected to also beat Vera in NVL72.
MI500 series is supposedly already taping out and they're claiming massive increases (we'll find out end of 2027 prob).
Absolutely true although at some point it's not just raw numbers but also the kernels that run matmuls and there seems (from outsider perspective) to have been more optimization in the cuda kernels
In a data center that is power constrained but not space constrained they could build out new racks and flip the power from the old racks. Wonder if this will lead to moderately used server GPUs on the secondary market someday.
Besides Nvidia Hardware is still sold out and super expensive. Not a single Nvidia consumer GPU got cheaper at all, Nvidia DGX Spark got more expensive too.
It will be swooped of the market the second it hits the market.
Passkeys are so, so, so bad. One of the worst things our industry invented. The sooner sites start leaving them on the wayside and just go back to TOTP, SMS, and Email codes/links, the better. These work. We solved auth. Its fine.
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