"coding is the prime use case for this where you can make money"
Is it?
I have the impression GenAI deteriorates the internet both from a content and tech perspective.
Bots that waste your time because they don't work well or because they are pushing an agenda, and low quality content that floods social media from people who want to make a quick buck.
GitHub and AWS became increasingly unstable. X, Instagram, and WhatsApp are suddenly sprinkled with subtle bugs.
Everything just got faster and we got more of it, but nothing of it is good anymore because everyone tries to replace 90% of their work with GenAI instead ofmaybe starting at 10-20% and then add more when you're sure it works.
I fear people will just get used to it. Nobody gets tailored clothing anyhmore and people don't question that we have standardized sizes that don't really fit anyone properly. People commonly buy standardized furniture and rarely get something to a specific for their room. If cheaper software (I mean thats mostly what it is) gets the job done, we will probably just keep doing that, even if that means we lose something in the process.
This has been the story for over a decade. Thins are easier. The cloud, more CPU, more RAM. No one really pays attention to performance, detail, and the little things. There is no craft in anything - just FEATURES.
AI will just make this so much worse - a race to the bottom of dull mediocrity.
Yeah but buying a sofa from Ikea doesn't let people steal my banking passwords. There are serious consequences to software bugs that there aren't in cheaper ready-made clothing.
It's the opposite, it becomes economically viable to produce tailor-made software for more narrow purposes. Coding becomes cheaper, resources free up for adjusting to the customer's problem more precisely.
Your analogy is one indirection from being a fit. Factories usually get custom solutions for their production facilities, tailor made by specialist engineers. They then run the production and deliver mass produced goods to the markets. We software engineers aren’t delivering tailor made solutions straight to the consumer markets. We are much more like the engineers who set up the machinery in the production facility, and our software is much closer to that machinery then it is to the mass produced table you buy at Ikea.
That's kind of my concern so far. We haven't seen a lot of big AI deployment success cases, but of the few mildly successful ones we HAVE heard of, they're 100% about cost saving / perceived efficiency and never about actually making a _better_ product or service.
I think it factors into why public perception is increasingly anti-AI. It'd be one thing if people were losing jobs, but on the other hand, their daily chores were done by a robot. Instead, people are losing (or fearing losing) their jobs, while increasingly having to fight with AI chatbots for customer support and similar cost-center use cases.
It's like AI is the "high fructose corn syrup" of tech. Nobody's arguing the output is better--it's just a lot cheaper and faster to get there, so that's its legacy. Making things cheaper and worse.
I am old enough to remember the outages of aws, gcp and azure which predate the gen ai thing. And of course the countless, endless, hopeless procession of bugs in just about anything else.
I am running it in a large mid cap company (~25bn revenue). For the first time we are releasing stuff which does not suck, and we are releasing it 5x faster than before. Its real for us, produces real, measureable economic value.
Now, how does anthropic or google make any money on those 250 p/m subs i have no idea.
Well tbh I think it's like cloud in 2007-2009. I was highly skeptical and heckling while running on managed bare metal everytime there was an outage. But now cloud is the standard model for anything really. And I think AI becomes the gold standard for code in the long term. So yea right now lots of outages. In a couple years it'll be much better. And in ten years people will always default to automation via AI.
Depends on what cryptography you're talking about, the Web Crypto API exists for quite some time, so I'd say that fits in (usually) with "The standard library in JS/CSS is great".
Yes, the issues is that LLMs sometimes fill semantic gaps.
When I write an article and I notice that there are steps missing for a conclusion then I do some research and fill them in.
These gaps often only show up when drafting, so if the LLM drafts, it might see a need to fill them in. You read the draft and see no steps are missing, but since you didn't do the research for the filled in steps, and they "look good to you", you might miss errors.
I liked that model a lot, but it made me a bit sad too.
All my life I was bad at being a loser, somehow I never really felt I fit in. I thought this was because of psychopathic tendencies or something. However, after reading this I realized there was another option and I was just clueless.
It is perhaps crucial to note that Venkat Rao, the author, himself found an escape from the system under study here; he’s been consulting or otherwise feral for about 15 years.
Being clueless can be admirable, I think. These are the people you work with who put in the work even when it won't lead to a fatter paycheck for themselves. The essay makes them out to all be useless middle managers, but the actual top contributers to a team also fit most closely with this category.
I mean, insurance is basically basically betting that bad things happen to you.
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