I'm saying the reasons given for certain architectural choices do not make much sense to me. And I'm also using this example to call out people who make claims that SQLite is on par with PostgreSQL for production use.
There is a reason I moved to Debian; it is not like I just like the sound of it better.
If I am distributing an app that uses the installed SQLite, you expect me to build a special version of SQLite and bundle it with my app?? Or require some weird extensions?
Unicode is about 300,000 characters at most.
Someone should post that article instead, lol. I'd love to discuss why I am able to comprehend and read a language almost fully but cannot speak it.
Remember this the next time someone suggests that SQLite is almost as good as (or even, cough, better than) PostgreSQL for production use.I was bit by this today while busily engaged in some related work on my web app project. What the heck?!
These new batch of people are not randomly selected; they are thought of as more suitable to rule due to their being academics and scientific/technical experts, rather than lifetime politicians. Same as the old politicians who were cut from a certain cloth.
The cloth is now different, but a cloth it remains.
Should probably be: "known to the state of California to be a class N carcinogen"
High-speed is a descriptor of the type of train, not their current speed.
Just like a racing cars is still such even when stationary.
You rarely hear of such in Japan.
Many people hate or fear flying. Some might also just prefer the laid back, retro, travel style. Not all are in a mad rush to get somewhere.
But I guess the market might be too small for regularly scheduled trips.
Although, I guess rogue waves can appear anywhere deep and rough.
If the coding was nothing, every good marketing guy could go solo and start large software businesses. It does not happen. You mostly see successful technical founders, or usually a marriage of technical and business cofounders.
Finding a fit between viable business opportunities and the tech to address it is what's hard, and requires several skills: technical, marketing, communication, product design, etc.
https://news.ycombinator.com/item?id=50220976
https://news.ycombinator.com/item?id=50165791
https://news.ycombinator.com/item?id=50159827
The first links shows a basic failure of reasoning, which would have gone unnoticed if I was just vibe-coding.
The second link shows weak architectural sense and an inability to see the big picture.
The last link in particular is telling: the agents worked with me (over weeks to months) to implement a db abstraction layer without ever bringing up the fact that as it stands, that would have never worked with any indexes at all. I did not constrain them to my choices, but they never stopped me with that design. It took my eagle-eyed attention to their offhand comments to notice this problem, which then required a lot of rework to fix.
Absolutely not at all. Every single day that I work with Claude, there is abundant evidence that AI sucks at these. Ask me for examples if you need them.
Case in point: I am building a digital files archive organizer platform.
This is simply not the kind of product you do a quick prototype of, get it to market quickly, and iterate on based on any failures or issues.
There are an almost infinite number of ways to get the product wrong, in a technical, architectural, and business/market sense. It requires a lot of deep thinking and internal prototyping to even get at what would actually be useful and address the walled-content-silos problem tech vendors love to foist on us. it requires careful implementation to not mess up user data. It requires a ton of architectural and UX design to get a performant product that is easy to understand. I have mulled over architectural decisions for months and thrown them out totally after mounting evidence they were not right, without a single user yet (except myself).
Just quickly coding up the first ideas that come to mind in this space is almost guaranteed to be wasted effort, because I could try a 100 approaches in the market and all could be bad. Do not let the users do your work for you. Make sure you actually understand what you are building and why it is important. Then let the user's experiences tell you how to tweak it to be better.
What some of us are saying is that AI is poor at figuring out what to build, how best to architecture it, and what to avoid.
There is a method to it that produces good results (definitely better than the machines) with little effort. To start with, I pre-soak the clothes in good washing powder. I also do not let clothes pile up. I wash a bit at a time.
It's like anything goes in most human endeavors. Society is winging it; duct-taped solutions abound. Most people lack taste or a keen eye for quality, and only notice when there is something seriously wrong. Even then, politics and all sorts of other concerns skews how people respond to things. This is why we complain about AI slop in the fields we know about, while the public at large think AI is the best thing after sliced bread.
Faced with this, unless someone is really passionate about their work, they eventually kind of tune out, and then look for how to expend the least effort possible to get whatever (uncertain or politicized) reward they can in their endeavors.
It is a failure of imagination to think that there is no longer much challenge. But I guess all humans have a problem with tunnel vision, to various extents.