"I used AI. It worked. I hated it." by @mttaggart https://taggart-tech.com/reckoning/

This is a really good blogpost. And I"m sure it'll make some people unhappy to read whether they're pro or anti genAI. What's good about @mttaggart's blogpost is he talks honestly about how using Claude Code did actually solve the problem he set out to do. It needed various guardrails, but they were possible to set up, and the project worked. But the post is also completely clear and honest about how miserable it was:

- It removed the joy from the process
- If you aim to do the right thing and carefully evaluate the output, your job ends up eventually becoming "tapping the Y key"
- Ramifications on people learning things
- Plenty of other ethical analysis
- And the nagging wonder whether to use it next time, despite it being miserable.

I think this is important, because it *is* true that these tools are getting to the point where they can accomplish a lot of tasks, but the caveat space is very large (cotd)

I used AI. It worked. I hated it.

I used Claude Code to build a tool I needed. It worked great, but I was miserable. I need to reckon with what it means.

What I think is also good about the piece is that it shows how using this tech eventually funnels people down a particular direction. This is captured also by this exchange on lobste.rs: https://lobste.rs/s/7d8dxv/i_used_ai_it_worked_i_hated_it#c_7jirfk

The story that people start with vs where they go is very different:

- They're really just for experts, and are assistants, they don't write the code for you
- Okay the write a lot of the code for me, but I personally don't commit anything without reviewing
- YOLO mode

Which eventually leads you to becoming the drinky bird pressing the Y key from that Simpsons episode. (Funnily enough I wrote that in my comment on lobste.rs in reply to someone else before I had even gotten to the point where I saw that @mttaggart literally had that gif)

And at that point, you're checked out. All that's left is vibes.

And unfortunately, these systems don't survive that point very well. And neither do you, in your skills and abilities.

There are a lot of other concerns but I think since a lot of people on the fediverse are opposed to these tools, they might not be very familiar with where they're currently at ability-wise. @mttaggart provides a good description that they *are* capable of solving many problems you put in front of them... and that doesn't remove the other problems they generate or involved in their process.

The slop part isn't just the individual outputs, but the cumulation, and the effect on society itself.

Is that pushing the goalposts? It may be. I think "slop" used to be easier to dismiss when it came to code because it was obviously bad. Now when it's bad, it's non-obviously bad, which is part of its own problem. And cognitive debt, deskilling, and etc don't get factored into the quality of output aspect.

But unfortunately, the immediate reward aspects of these things are going to make it hard for society to recognize.

@cwebber

It kind of feels like its going to something big happening in the press to get people to stop.

I was thinking an AI caused Therac 25, but maybe a copilot worm that wipes all windows 11 computers might get some outlawing AI code legislation.

@alienghic @cwebber

The thing most likely to get people to stop is the end of the massive subsidies for its use that the VCs are currently pouring in.

Already firms are starting to panic a little about token use for things like Claude Code, and are putting limiters in their workers that really defeat the purpose of all of the "YOU MUST USE THIS OR BE FIRED" diktats. But operating indefinitely at those prices will bankrupt Anthropic soon.

So at some point the private equity love affair with everything AI will dry up (possibly because of a Iran war-induced financial crisis), and at that point it's going to be "my org can spend $50k annually on my personal Claude tokens to make me 20% more productive . . . or it could just hire a junior dev?"

There's a chance they manage to optimize this, or get it to work using a lighter weight model. But I think it's unlikely.

@MichaelTBacon @alienghic @cwebber I don't see a stopping in the near term. PE hasn't done a lot of real AI deals, I think that's blocked on a lack of proven playbooks. VCs are making bets but the actual end user value is pretty unclear. Having studied this area and its trajectory quite a bit over the last year I think the unit economics of API serving are already approximately sustainable, and the models and hardware designs continue to get cheaper for a given level of performance. ...
@MichaelTBacon @alienghic @cwebber ... Right now the big firms are loading up on cash and I think working hard to cut the cost of their subscription products (e.g. ChatGPT or Claude) to the point where they'll be able to run unsubsidized in the near future at something not far from the current output quality and pricing. Their priority appears to be to sell more seats at low cost (Claude Enterprise starts at $20 a seat) and hope that they can get entrenched before starting to ramp prices up.
@MichaelTBacon @alienghic @cwebber I haven't seen any hard data, but spending enough time in tech industry circles it seems to be working.

@mirth @alienghic @cwebber

So far, from what I've seen, any time one of the subscription AI places put up their prices to something resembling actual operating costs (nevermind paying back gigantic sunk capital costs), users have screamed and then bolted.

Honestly, doing the really heavy duty Claude Code stuff that's getting pushed now will easily run to $50k per developer at current costs. And no, I don't see that as something that enterprises will ultimately be willing to swallow. Nor do I see a path for them to get the GPU cycle burn down easily.

@MichaelTBacon @alienghic @cwebber That math sounds way off. Assuming a monthly usage of 5M tokens for day to day developer usage, at the current Claude API costs, and billing them all at the highest rate ($25 per M), that's $125 per month at current pricing. It's a long way from there to $50k, and surveying the trajectory over the last couple years as well as models from some of the Chinese labs it's pretty clear that model size necessary to do these tasks is trending down.