It’s likely because the quick thought is that auth is just user table with hashed password.
Then when you really start thinking about it, the list of requirements grows.
Of course it’s still totally doable for an average developer, but takes time and mistakes can be catastrophic. And maybe the time is better spent developing stuff that differentiates you from others.
I was just referring to specifically the cruise control which seems useful only in traffic conditions. As soon as the road gets a bit cleared up it has a tendency to accelerate too much, and a bit too eagerly.
But we have similar conditions, 2kids and in need of space and Sealion 7 won over many other EVs for number of features, platform, and especially price.
It goes for all professions really, people who do it for work and people who care.
Apply to any profession, plumbers, doctors, carpenters, cleaners, etc etc. Most of us have experienced both types and I haven’t heard of anyone preferring the ”do it for work” over the ones who care. And like those other professions, in software we accept the worse of the two because finding people who care is both time consuming and often much more expensive.
"Space datacenter" -> overpriced starlink with some shitty edge compute -> "look guys, we built a space datacenter; earnings results to follow" -> number go up.
it's boiling the frog method. Moving too fast means backlash, but a slow, step by step transition where each step seems reasonable, but ultimately end up with a locked down device, is how they aim to achieve it. And people would be too lazy to complain until the last few steps, by which time it would be too late.
The so called AI job loses are not due to AI. I don't think there is anyone out there to argue otherwise.
In a year but probably sooner, when software systems start collapsing, and they will, hiring in tech sector will skyrocket. In fact, I don't believe the world have enough developers to backfill for the AI deficiencies.
To me the math is obvious. Assuming humans touch a 1% of all software systems created, something we know it is simply never going to be true given the current state and upcoming regulations, the 47 million developers world-wide (and that includes all kinds of developers) are simply not enough.
However, although jobs will be back and it will be better payed, programming will "suck" even more and I don't think it will be for everyone. If you are not the kind of person that enjoys reversing a piece of tangled mess it might not be for you.
If AI is everything and AI is software then everything is software and everyone would like to have a piece of that software.
I agree. I come back to it all the time when I need a little inspiration for how to deal with a gnarly codebase. Usually there is something in there I can apply directly to get me out of a pinch. When there is not the reminder of how malleable code is suffices.
If AI turns out to be a bust, ignoring it could become a significant win. One possible outcome of AI adoption is that existing code bases are degraded, and existing programmer capability is allowed to atrophy. In that situation, companies that adopt AI lose out relative to companies that eschew it.
This. There is definitely a ratio. A year ago, it was 50/50. It felt better because the hard things it did fast while I sipped coffee outweighed in my mind the negatives.
Now that ratio is swinging way over towards the LLMs favor.
Scrambling? Seems to me xAI built too much capacity (for what they can use in 2026). Does that mean OpenAI built the right amount? I don't see how this proves that just because we see one AI company willing to sell compute. We don't even know the terms/pricing.
As the co-author of the project: the whole reason was to allow everybody to hallucinate what they want. If it was their will to research such things on there, then it shall be. But yes, it is kinda sad.
If technological innovation is to liberate us from poverty then it should be a celebration that everytime that a job is automated. Since that is not happening, it implies something deeply wrong about how we structure our society.
> Average price inflation of a big mac in the US for the past 25 years is 4% versus average CPI inflation of 2.29%. So instead of increasing in price by 65% it increased 166%.
Because a big mac isn't a TV or smartphone. It doesn't get those juicy negative adjusted inflation values applied to it because of "more features". CPI for ground beef is ~4% YoY. Processed cheese? 4%. I don't doubt some of it is price raises just because they can, but let's not just compare two difference averages as if they represent the same thing.
I think it’s worth recognizing that people’s issues with LLMs isn’t that they make mistakes. And I think hammering the argument that humans also make mistakes indicates a bit of a disconnect with the more common reasons there is frustration with LLM use.
Ultimately I think people find it frustrating because many of us have spent years refining our communication so that it is deliberate and precise. LLMs essentially represent a layer of indirection to both of those goals. If I prepare some communication (email, code, a blog post, etc) and try to use an LLM more actively, I find at best I end up with something that more or less captures what I probably was going to communicate but doesn’t quite feel like an extension of my own thoughts as much as an slightly blurred approximation.
I think this also explains to some degree why it seems folks who were never particularly critical of their own communication have a hard time comprehending why anyone could be upset about this.
There is of course the flip side where now when receiving communication that I have to attempt to deduce if I’m reading a 5 paragraph, meticulously formatted email (or 200 line, meticulously tested function) because whoever sent it was too lazy to more concisely write 2-3 well thought out sentences (or make a 15-line diff to an existing function). And of course the answer here for the AI pragmatist is that I should consider having an AI summarize these extensive communications back down to an easily digestible 2-3 sentence summary (or employ an AI to do code review for me).
For those that value precise communications, this experience is pretty exhausting.
I'm absolutely tired at work on how many people are writing with em-dashes with obvious AI prose. I feel a little bit insulted but then I remember we all participate in this charade.
I would be curious to understand whether they implemented this from scratch or whether they got a whitelabel solution from someone else (and if so, who).
I was shocked recently when I looked into this to find out the number of solutions out there.
Maybe I am not doing something right... It failed me at a repetitive task that I have been doing since 5 months now. After a long, verbose chat, it finally delivered only to immediately fail next week.
