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In most cases, LLMs will not replace humans or reduce labor costs as companies hope. They will •increase• labor costs, in the form of tedious clean-up and rebuilding customer trust.
After a brief sugar high in which LLMs rapidly and easily create messes that look like successes, a whole lot of orgs are going to find themselves climbing out of deep holes of their own digging.
Example from @Joshsharp:
https://aus.social/@Joshsharp/112646263257692603
Those who’ve worked in software will immediate recognize the phenomenon of “messes that look like successes.”
One of my old Paulisms is that the real purpose of a whole lot of software processes is to make large-scale failure look like a string of small successes.
The crisp “even an executive can understand it” version of the OP is:
AI increases labor costs
(“Why?” “Because it’s labor-intensive to clean up its messes.”)
I said “the purpose of a whole lot of software processes is to make large-scale failure look like a string of small successes.”
Huh? What does that look like??
It looks like this:
Meetings held Plan signed off Tests passed Iterations iterated Velocity increased Thing implemented Checkpoints checked Thing released Blinkenlights blink Line goes up Thing updated
Software never •really• solves the problem it was supposed to solve in the first place, creates more problems
or Problem the project was supposed to solve in the first place was the wrong problem
or Nobody actually wanted it
or We totally failed to understand the real effect of implementing this
or The goal was designed to benefit some individual / faction within the company, not the mission
or The goal was designed to benefit the bottom line / investors / some horrid systemic evil, and is net harmful to humanity / the world
(Yes, I consider that last one a failure too.)
@inthehands okay I'm booking this whole thread, it's so succinct and relatable. Honestly a nice reminder of the scope at play.
I'm curious, how pervasive would you say this is? Is this like every project in every org? Or half of half? Struggling to see past my own experiences, which are honestly a lot of this on repeat.
@geoffreyconley
I remember many years ago having an animated discussion with coworkers about what percentage of all corporate software projects are hoaxes (where “hoax” means “never really succeeds, even if it’s presented as a success).
Our conclusion is that we have no idea, and no way of finding out. Too many projects, wildly different places, no way of evaluating the question.
Truly, I have no idea. I just know this: it’s not rare.
@geoffreyconley@floss.social@inthehands that seems fair enough! Thanks for your response!!
Sorry to ask, but in terms of personal philosophy, do you aim to find projects and employers that AREN'T this way? Do you end up accepting that it happens, and just do your part?
@geoffreyconley
The main things I look for in choosing a project:
- Cool people
- Worthy goal
- Fun problems to solve
With 1/3 I can survive. 2/3 is a great project.
I suppose I do consider the odds of the project being truly successful — but mostly I take a kind of Camusesque perspective: it’s necessary for orgs to try things, for projects to crash and burn, for people to explore what turn out to be dead ends. In the end, I just want to have been glad to have done the work.
@geoffreyconley
For example, with the downthread story about Megacorp Y, my main regret is •not• about the CEO pulling the plug on everything I did a year after I left. No, that’s just hilarious!
My regret is that I found out later one of the managers had been really emotionally abusive to some of the other devs, especially the one woman on the team, when I wasn’t present. I wish I’d realized that while I was there! I wish I’d fought back! But I was oblivious to it. Big regret.