HolyLampshade
Joined 11 years ago
Joined 11 years ago
But you’re absolutely right, it’s hard to compromise something that moves at such an absolutely glacial pace.
Best a hacker could probably achieve is sending some sketchy emails or messages, but even there people are just going to confirm by verbally communicating with him.
Banks are actually the worst analogy for this sort of thing because there is a ridiculous amount of system federation and ultra-conservative system controls. It can take a month to get a simple route or firewall port opened on controlled networks (god I hate change committees).
I’m going to sound like an ass, but is this the sort of crap we’re going to see published in 10yr when all these crypto folk grow up a bit and start reflecting on their “glorious revolution”?
At least the Beanie Baby people realized it was ridiculous.
I guess the better comparison is dotcom folks, and they were pretty insufferable for quite a while
I cannot look at how these companies are run with anything but derision. It’s institutional laziness, and it’s sloppy.
Watching crypto rediscover 100yr of financial regulation and system/process design has never not been amusing to me, esp as someone who works in an asset that has solved the custodianship problem (not that people in the industry aren’t actively attempting to light those safety rails on fire to make a few extra bucks).
The value in buying a product or service from someone else is access to expertise, an expectation of support, and on some level the distribution of legal and financial/time risk in developing a new product. If you can do it all with some LLM then especially that risk of building a bespoke product is all but obliterated.
Anecdotally I started to see this at my last gig where bizdev folks were writing their own tools and in some cases their own little micro products (things 15-20yr ago they would have had to purchase from a third party, or get internal dev to work on). Now, I certainly don’t want to deal with that sort of technical debt, but plenty of firms don’t feel the same way (clearly given how much layoffs have been impacting everyone on the SWE side).
Efficient and tight markets are almost entirely predicated on being able to determine that any informational asymmetry is irrelevant over differing time horizons.
It’s something like a cargo cult. We have this system because of course we need this system and it “insists upon itself”.
The further development is removed from the final “product” of the company the more this crap piles up.
So, I agree that in some instances it’s intentionally obfuscated, but there are others where the bloat simply cannot be calculated.
And that isn’t meant to denigrate the oil change person. There are millions of that person to every one person working for an F1 team, and it’s important work. But, obviously very different things.
The other issue I’ve been mulling over is two part. What in the hell have all these SWEs been actually doing? (As in, what software were the vast majority contributing to?) By extension, were many of these projects critical to the bottom line?
I guess what I’m getting at is if you can have a robot do a sloppy job of what you were doing before, and have that still be ok for the organization, maybe what you were doing in the first place wasn’t critical.
I’m not saying it’s not short sighted (I think many orgs are subjugating themselves to external entities, and are going to be violently bit in the ass when suddenly no one left in the firm has any comprehension of how all of their systems work), but, and I don’t say this lightly, maybe the SWE “profession” has a bit of bloat it can afford to shed?
Even ones that cannot be easily dismissed (like the agent at the top of Google search) are often subtly wrong in a way that requires significantly more effort on my end to parse the loquacious output to determine where the inconsistencies are.
Look, can they be useful to generate the html or jscript for humanity’s 9 billionth iteration of a web form? Sure. But man, I wish sanity had reigned and people had applied ML models in general to more substantive and beneficial projects.
(Before anyone chimes in, I’m familiar with implementations of ML applied to esoteric domains; but by their very nature these don’t get all the news cycles, or hiring, or any of the other absolute insanity that the domain seems to contain)
Thanks for all the work you put into making sure this place isn’t a cess pool.