It’s allowed a sludge of internal tools to spin up, and more bloat. The ability to sand bag and over build these tools has gotten 2-10x worse.

Only solution I can think of is to drastically cut headcount so productivity is back to prior levels, and profitability is raised. Big Tech is mostly market constrained with not much room to grow beyond the market itself growing.

As for startups, seems like AI tools have drastically reduced their time to market and accelerated their growth curves.

I mean as in living through the industrial revolution would have been wild. So whether we have an AI revolution or an AI bubble it's bound to be a roller coaster.

And that's without accounting for the various wars (and resultant economic impacts) that are already in progress. A large part of what drove the meat grinder of WWI was (very approximately) the various actors repeatedly misjudging the overall situation and being overly enthusiastic to try out their shiny new weapons systems. If one or more superpowers decide to have a showdown the only thing that might minimize loss of life this time around is (ironically enough) the rise of autonomous weapons systems. Even in that case as we know from WWII the logical outcome is a decimated economy and manufacturing sector regardless of anything else that might happen.

Imagine you're a typesetter and they just invented computerized printing.

I have one that serves a few functions- Tracks certificates and licenses (you can export certs in any of the majorly requested formats), a dashboard that tells you when licenses and certs are close to expiring, a user count, a notification system for alerts (otherwise it's a mostly buried Teams channel most people miss), a Downtime Tracker that doesn't require people to input easily calculatable fields, a way for teams to reset their service account password and manage permissions, as well as add, remove, switch which project is sponsoring which person, edit points of contact, verify project statuses, and a lot more. It even has some quick charts that pull from our Jira helpdesk queue- charts that people used to run once a week for a meeting are just live now in one place. It also has application statuses and links, and a lot more.

I'd been fighting to make this for two years and kept getting told no. I got claude to make a PoC in a day, then got management support to continue for a couple weeks. It's super beneficial, and targets so many of our pain points that really bog us down.

The ones I can mention.. one that watches a specific web site until an offer that is listed expires and then clicks renew (happens about once a day, but there is no automated way in the system to do it and having the app do it saves it being unlisted for hours and saves someone logging in to do it). Several that download specific combinations of documents from several different portals, where the user would just suck it up previously and right-click on each one to save it (this has a bunch of heuristics because it really required a human before to determine which links to click and in what order, but Claude was able to determine a solid algo for it). Another one that opens PDFs and pulls the titles and dates from the first page of the documents, which again was just done manually before, but now sends the docs via Gemma4 free API on Google to extract the data (the docs are a mess of thousands of different layouts).

It's almost always a CRUD app or dashboard that no one uses while being extremely overkill for their use case.

edit: LOL called it, a bunch of useless garbage that no one really cares about but used to justify corporate jobs programs.

I'll throw this out as something where it has saved literally weeks of work: debugging pathological behaviour in third-party code. Prompt example: "Today, when I did U, V, and W. I ended up with X happening. I fixed it by doing Y. The second time I tried, Z happened instead (which was the expected behaviour). Can you work out a plausible explanation for why X happened the first time and why Y fixed it? Please keep track of the specific lines of code where the behaviour difference shows up."

This is in a real-time stateful system, not a system where I'd necessarily expect the exact same thing to happen every time. I just wanted to understand why it behaved differently because there wasn't any obvious reason, to me, why it would.

The explanation it came back with was pretty wild. It essentially boiled down to a module not being adequately initialized before it was used the first time and then it maintained its state from then on out. The narrative touched a lot of code, and the source references it provided did an excellent job of walking me through the narrative. I independently validated the explanation using some telemetry data that the LLM didn't have access to. It was correct. This would have taken me a very long time to work out by hand.

Edit: I have done this multiple times and have been blown away each time.

I answered this in a different comment below, but a lot of the friction is around the amount of time it takes to test/review/submit etc, and a lot of this is centered around tooling that no one has had the time to improve, perf problems in clunky processes that have been around longer than anyone individual, and other things of this nature. Addressing these issues is now approachable and doable in one's "spare time".

Creating stakeholder value

For me/my team, I use it to fix DevProd pain points that I would otherwise never get the investment to go solve. Just removed Webpack for Rspack, for example. Could easily do it myself, which is why I can prompt it correctly and review the output properly, but I can let it run while I’m in meetings over more important product or architectural decisions

>Such as?

it's crazy that the experiences are still so wildly varying that we get people that use this strategy as a 'valid' gotcha.

AI works for the vast majority of nowhere-near-the-edge CS work -- you know, all the stuff the majority of people have to do every day.

I don't touch any kind of SQL manually anymore. I don't touch iptables or UFW. I don't touch polkit, dbus, or any other human-hostile IPC anymore. I don't write cron jobs, or system unit files. I query for documentation rather than slogging through a stupid web wiki or equivalent. a decent LLM model does it all with fairly easy 5-10 word prompts.

ever do real work with a mic and speech-to-text? It's 50x'd by LLM support. Gone are the days of saying "H T T P COLON FORWARD SLASH FORWARD SLASH W W W".

this isn't some untested frontier land anymore. People that embrace it find it really empowering except on the edges, and even those state-of-the-art edge people are using it to do the crap work.

This whole "Yeah, well let me see the proof!" ostrich-head-in-the-sand thing works about as long as it takes for everyone to make you eat their dust.

There is a difference to just noticing and attributing it to and recognizing negative financial outcomes. Right now for most companies they are still adjusting to declining inflation. Their bottom lines are doing quite well because consumer price inflation is much stickier than supply inflation. We are coming off of one of the quickest and largest supply lead inflationary cycles. It may not be immediately apparent for many companies that new expenditures are a drag on profitability.

The real thing to look at is whether or not the future outlook for company AI spend is heading up or down?

What a finance team allocates on spend has nothing to do with what the tokens actually get used for.

Are they peeking over the shoulder of each team and individual? Of course not.

It can be the case that the spend is absolutely wasteful. Numbers don’t lie.

> Do you really think companies have started spending millions on tokens and no one from finance has been involved?

Oh, they were involved all right. They ran their analyses and realized that the increase in Acme Corp's share price from becoming "AI-enabled" will pay for the tokens several times over. For today. They plan to be retired before tomorrow.

More that there is a poor incentive structure. Just like how PE can make money by leveraged buyouts and running businesses into the ground. Many of the financial instruments that make both that and the current AI bubble possible were legal then made illegal within the lifetimes of the last 16 presidents.

Round-tripping used to be regulated. SPVs used to be regulated. If you need a loan you used to have to go to something called a bank, now it comes from ???? who knows drug cartels, child traffickers, blackstone, russians & chinese oligarchs. Even assuming it doesn't collapse tommorow why should they make double digit returns on AI datacenters built on the backs of Americans?

Internal tool Doesn’t have credential. Checkmate ;)

Its a bit of workspace politics, I would need to call that guy out to tell that he is not hyper-performer, but just pushed lots of low quality code which will produce lots of negative impact in a long term.

Also, I am not sure if it is trivial to implement. The code is injected into many scenarios and workflows, so replacement will be painful and risky if new solution break some edge case.

The problem was definitely because they didn't use enough AI fast enough. They should just try again

it will comprehend it well enough to complicate it further into a rats-nest that only Opus 4.9 can comprehend, and so on. Good luck if you run into a bug before the N+1 version launches.

How do you mean "barely keep up" and "running laps around them" ?

Are the juniors increasing economic productivity or just pushing lines of code?

</retired from being measured against a random number generator>

They aren't teaching themselves anything though are they, they are basically getting AI to do their work for them.