Work wants to add that new whiz-bang agentic AI into a scheduling service that I have been tasked with building, but in the dumbest way possible kind of similar to the Jet’s text-a-pizza-order thing that worked like shit. I need to find an entirely new profession, everyone in software now is fucking deranged.
Q: what do you call a tool that works 90% of the time? A: broken
Friend texted me this one. Reader’s Digest of course was AI slop before AI took off.
:surprised-pikachu:
Even the most dysfunctional team would have spent time developing some kind of standard here from my (admittedly limited) experience.
My experience has been vastly different. Prior to LLMs I have seen all sorts of horrors of this sort and others writ large across many codebases. It’s so awesome that LLMs offer the ability to make the same sorts of code but at a much faster speed. In times past it used to take devs years to build up the kind of tech debt that LLMs can give you in days.
That this comes from the Saudi Royal Family is especially rich because of the amount of plain-ol’ sycophancy around Neom.
“I did the AI that people largely hate, but the next guy, HE’S the real AI CEO. Just remember him, not me, the guy who did the stuff.”
Is it going to be a bunch of ArmV8 cores shoved into the same package? Probably going to be a bunch of ArmV8 cores shoved into the same package. You know, for AI.
Chicago always wanted a 9/11 of its own.
“Congratulations guys, we did it. Job well done. You’re all fired.”
I find it very unsatisfactory to sneer at skeets from the above author. It’s just junkfood at this point and not like good junkfood, just like stale off-brand popcorn in a bag that has a picture of a sad clown on it. Why is the clown sad? Because the clown has to constantly look at different variations on the same theme written by people whose brains are melted by LinkedIn.
Man, if only I had enough optimism left to aspire to that level of silliness, as opposed to be sliding further and further in to the maw of computer stupidity.
AI was going to give us all universal healthcare but we didn’t believe hard enough and now all we have is this.
“Selling your soul to the company store is not just fun, it is also invigorating!”
I was trying to put this into perspective by comparing this to the flow rate of the Des Plaines river. At the high end, 8 million gallons a day is something like 12.4 cubic feet per second constantly. Currently the Des Plaines has a discharge rate of 86-87 cubic feet per second, so a bit above 14% of the Des Plaines per data center.
If only it was a gong show. It’s more like shoveling coal into a dead horse and expecting a locomotive to spring forth
I feel this, I was dealing with this at a prior employer.
Like I ever stopped…
I just had one of those “brain-doing-brain-stuff-good” moments (I think normal people call them delusions?) pondering about why it is that AI code extruders are seeing widening adoption.
tl;dr - there’s a bunch of people uncurious about the nature of the abstractions they use and it’s a tragedy.
First a moment of background: My first software dev position was using Lisp and one of the most powerful concepts built into the language runtime was the macro facility, the ability to write code that writes code. The main downsides of Lisp are obsequious Lisp developers and hard-to-master C foreign function interfaces, so what you have is a toolchain of abandoned dependencies made by some real annoying characters, but I digress. The ability to write code that writes code is a powerful concept.
I moved on to working with .Net which sometime around the 4.6 version release got enhancements to built-in language utilities. This led to better code-generators for numerous purposes (certain DI containers started to do dependency resolution at build time for example).
I did Scala for a time, which had a macro facility that was hot garbage and was rewritten between 2 and 3, so I never bothered to learn it. Around this time the orgs I worked for were placing an emphasis on OpenAPI / swagger specs for reasons I don’t know because while there was tooling that could be used to generate both the entire http client and the set of interfaces used by the surface, we did neither (where I am at right now we still do neither form of code gen).
Anyways, things like code generation whether via external tooling or internal facilities is magical but it is deterministic magic: Identical input should yield the same result. It is also hard to use well. The ergonomics of the OpenAPI / Swagger codegen tooling is pretty bad though not impossible, and the whole thing under the hood is powered by mustache templates. The .Net stuff is still there and works well, but I don’t think many work places want to invest in really understanding that tooling and how it can be employed. Lisp well always be Lisp, good job Lisp. There are other examples of code generation used for practical ends I am sure.
The point is that code generation requires being able to think and define certain forms of abstractions outside of the target functionality of a single program and while it’s not hard to do that thinking, it’s just high enough of a bar that your typical enterprise engineer won’t engage with that (but will always be amazed by the results!).
AI Code Extruders change the cognitive burden that would be required for code generation into something that I guess appeals to engineers. You can specify something in the abstract and a Do-What-I-Mean machine may churn up something minimally useful, determinism be damned. Not only would an engineer not need to consider the abstraction layer between their input and the code but they would be unable to fully interrogate that abstraction because the code extruder does not need to show its work.
Just a thought. Probably a very silly thought.
This NPR article opens with a banger of a line:
The things still fucking hallucinate, it’s not a feature that’s separable from the model.