Posted by presbyterian 4 hours ago
What's Anthropic's optimization target??? Getting you the right answer as fast as possible! The variability in agent output is working against that goal, not serving it. If they could make it right 100% of the time, they would — and the "slot machine" nonsense disappears entirely. On capped plans, both you and Anthropic are incentivized to minimize interactions, not maximize them. That's the opposite of a casino. It's ... alignment (of a sort)
An unreliable tool that the manufacturer is actively trying to make more reliable is not a slot machine. It's a tool that isn't finished yet.
I've been building a space simulator for longer than some of the people diagnosing me have been programming. I built things obsessively before LLMs. I'll build things obsessively after.
The pathologizing of "person who likes making things chooses making things over Netflix" requires you to treat passive consumption as the healthy baseline, which is obviously a claim nobody in this conversation is bothering to defend.
Intermittent variable rewards, whether produced by design or merely as a byproduct, will induce compulsive behavior, no matter the optimization target. This applies to Claude
This is an incorrect understanding of intermittent variable reward research.
Claims that it "will induce compulsive behavior" are not consistent with the research. Most rewards in life are variable and intermittent and people aren't out there developing compulsive behavior for everything that fits that description.
There are many counter-examples, such as job searching: It's clearly an intermittent variable reward to apply for a job and get a good offer for it, but it doesn't turn people into compulsive job-applying robots.
The strongest addictions to drugs also have little to do with being intermittent or variable. Someone can take a precisely measured abuse-threshold dose of a drug on a strict schedule and still develop compulsions to take more. Compulsions at a level that eclipse any behavior they'd encounter naturally.
Intermittent variable reward schedules can be a factor in increasing anticipatory behavior and rewards, but claiming that they "will induce compulsive behavior" is a severe misunderstanding of the science.
Does this mean I should not garden because it's a variable reward? Of course not.
Sometimes I will go out fishing and I won't catch a damn thing. Should I stop fishing?
Obviously no.
So what's the difference? What is the precise mechanism here that you're pointing at? Because sometimes life is disappointing is a reason to do nothing. And yet.
Anthropic's optimization target is getting you to spend tokens, not produce the right answer. It's to produce an answer plausible enough but incomplete enough that you'll continue to spend as many tokens as possible for as long as possible. That's about as close to a slot machine as I can imagine. Slot rewards are designed to keep you interested as long as possible, on the premise that you _might_ get what you want, the jackpot, if you play long enough.
Anthropic's game isn't limited to a single spin either. The small wins (small prompts with well defined answers) are support for the big losses (trying to one shot a whole production grade program).
The majority of us are using their subscription plans with flat rate fees.
Their incentive is the precise opposite of what you say. The less we use the product, the more they benefit. It's like a gym membership.
I think all of the gambling addiction analogies in this thread are just so strained that I can't take them seriously. Even the basic facts aren't even consistent with the real situation.
they want me to not spend tokens. that way my subscription makes money for them rather than costing them electricity and degrading their GPUs
If you're on anything but their highest tier, it's not altogether unreasonable for them to optimize for the greatest number of plan upgrades (people who decide they need more tokens) while minimizing cancellations (people frustrated by the number of tokens they need). On the highest tier, this sort of falls apart but it's a problem easily solved by just adding more tiers :)
Of course, I don't think this is actually what's going on, but it's not irrational.
I mean this only works if Anthropic is the only game in town. In your analogy if anyone else builds a casino with a higher payout then they lose the game. With the rate of LLM improvement over the years, this doesn't seem like a stable means of business.
Dealing with organic and natural systems will, most of the time, have a variable reward. The real issue comes from systems and services designed to only be accessible through intermittent variable rewards.
Oh, and don't confuse Claude's artifacts working most of the time with them actually optimizing to be that way. They're optimizing to ensure token usage. I.E. LLMs have been fine-tuned to default to verbose responses. They are impressive to less experienced developers, often easier to detect certain types of errors (eg. Improper typing), and will make you use more tokens.
The variability in eg soccer kicks or basketball throws is also there but clearly there is a skill element and a potential for progress. Same with many other activities. Coding with LLMs is not so different. There are clearly ways you can do it better and it's not pure randomness.
So you're saying businesses shouldn't hire people either?
There is absolutely no incentive to do that, for any of these companies. The incentive is to make the model just bad enough you keep coming back, but not so bad you go to a competitor.
We've already seen this play out. We know Google made their search results worse to drive up and revenue. Exact same incentives are at play here, only worse.
IF I USE LESS TOKENS, ANTHROPIC GETS MORE MONEY! You are blindly pattern matching to "corporation bad!" without actually considering the underlying structure of the situation. I believe there's a phrase for this to do with probabilistic avians?
Are you totally sure they are not measuring/optimizing engagement metrics? Because at least I can bet OpenAI is doing that with every product they have to offer.
The analogy was too strained to make sense.
Despite being framed as a helpful plea to gambling addicts, I think it’s clear this post was actually targeted at an anti-LLM audience. It’s supposed to make the reader feel good for choosing not to use them by portraying LLM users as poor gambling addicts.
To the bluesky poster's point: Pulling out a laptop at a party feels awkward for most; pulling out your phone to respond to claude barely registers. That’s what makes it dangerous: It's so easy to feel some sense of progress now. Even when you’re tired and burned out, you can still make progress by just sending off a quick message. The quality will, of course, slip over time; but far less than it did previously.
Add in a weak labor market and people feel pressure to stay working all the time. Partly because everyone else is (and nobody wants to be at the bottom of the stack ranking), and partly because it’s easier than ever to avoid hitting a wall by just "one more message". Steve Yegge's point about AI vampires rings true to me: A lot of coworkers I’ve talked to feel burned out after just a few months of going hard with AI tools. Those same people are the ones working nights and weekends because "I can just have a back-and-forth with Claude while I'm watching a show now".
The likely result is the usual pattern for increases in labor productivity. People who can’t keep up get pushed out, people who can keep up stay stuck grinding, and companies get to claim the increase in productivity while reducing expenses. Steve's suggestion for shorter workdays sound nice in theory, but I would bet significant amounts of money the 40-hour work week remains the standard for a long time to come.
This isn't generally true at all. The "all tech companies are going to 996" meme comes up a lot here but all of the links and anecdotes go back to the same few sources.
It is very true that the tech job market is competitive again after the post-COVID period where virtually nobody was getting fired and jobs were easy to find.
I do not think it's true that the median or even 90th percentile tech job is becoming so overbearing that personal time is disappearing. If you're at a job where they're trying to normalize overwork as something everyone is doing, they're just lying to you to extract more work.
It starts with people who feel they’ve got more to lose (like those supporting a family) working extra to avoid looking like a low performer, whether that fear is reasonable or not. People aren’t perfectly rational, and job-loss anxiety makes them push harder than they otherwise would. Especially now, when "pushing harder" might just mean sending chat messages to claude during your personal time.
Totally anecdotal (strike 1), and I'm at a FAANG which is definitely not the median tech job (strike 2), but it’s become pretty normal for me to come back Monday to a pile of messages sent by peers over the weekend. A couple years ago even that was extremely unusual; even if people were working on the weekend they at least kept up a facade that they weren't.
It's more like being hooked on a slot machine which pays out 95% of the time because you know how to trick it.
(I saw "no actual evidence pointing to these improvements" with a footnote and didn't even need to click that footnote to know it was the METR thing. I wish AI holdouts would find a few more studies.)
Steve Yegge of all people published something the other day that has similar conclusions to this piece - that the productivity boost for coding agents can lead to burnout, especially if companies use it to drive their employees to work in unsustainable ways: https://steve-yegge.medium.com/the-ai-vampire-eda6e4f07163
Yeah I really feel that!
I recently learned the term "cognitive debt" for this from https://margaretstorey.com/blog/2026/02/09/cognitive-debt/ and I think it's a great way to capture this effect.
I can churn out features faster, but that means I don't get time to fully absorb each feature and think through its consequences and relationships to other existing or future features.
But for what I've seen both validating my and others coding agents outputs I'd estimate a much lower percentage (Data Engineering/Science work). And, oh boy, some colleages are hooked to generating no matter the quality. Workslop is a very real phenomenon.
I was really impressed with how it parsed the structured checklist. I was not at all impressed by how it digested the paper. Lots of disguised errors.
There's also this article on hbr.org https://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies...
This is a real thing, and it looks like classic addiction.
Claude Code wasting my time with nonsense output one in twenty times seems roughly correct. The rest of the time it's hitting jackpots.
Right but the <100% chance is actually why slot machines are addictive. If it pays out continuously the behaviour does not persist as long. It's called the partial reinforcement extinction effect.
“It’s not like a slot machine, it’s like… a slot machine… that I feel good using”
That aside if a slot machine is doing your job correctly 95% of the time it seems like either you aren’t noticing when it’s doing your job poorly or you’ve shifted the way that you work to only allow yourself to do work that the slot machine is good at.
If you are unfamiliar with the various ways that naive code would fail in production, you could be fooled into thinking generated code is all you need.
If you try to hold the hand of the coding agents to bring code to a point where it is production ready, be prepared for a frustrating cycle of models responding with ‘Fixed it!’ while only having introduced further issues.
And to another point: work life balance is a huge challenge. Burnout happens in all departments, not just engineering. Managers can get burnout just as easily. If you manage AI agents, you'll just get burnout from that too.
My paraphrase of their caveats:
- experts on their own open source proj are not representative of most software dev
- measuring time undervalues trading time for effort
- tools are noticeably better than they were a year ago when the study was conducted
- it really does take months of use to get the hang of it (or did then, less so now)
Before you respond to these points, please look at the full study’s treatment of the caveats! It’s fantastic, and it’s clear almost no one citing the study actually read it.
[0]: https://metr.org/blog/2025-07-10-early-2025-ai-experienced-o...
Maybe someone can show me how you're supposed to do it, because I have seen no evidence that AI can write code at all.
Step 2: download Zed and paste in your API Key
Step 3: Give detailed instructions to the assistant, including writing ReadMe files on the goal of the project and the current state of the project
Step 4: stop the robot when it's making a dumb decision
Step 5: keep an eye on context size and start a new conversation every time you're half full. The more stuff in the context the dumber it gets.
I spent about 500 dollars and 16 hours of conversation to get an MVP static marketplace [0], a ruby app that can be crawled into static (and js-free!) files, without writing a single line of code myself, because I don't know ruby. This included a rather convoluted data import process, loading the database from XML files of a couple different schemas.
Only thing I had to figure out on my own was how to upload the 140,000 pages to cloudflare free tier.
Yeah I can't stop myself when I'm about to make a dumb decision, just look at my github repo. I ported Forth to a 1980s sampler and wrote DSP code on an 8-bit Arduino.
How am I going to stop a robot making dumb decisions?
Also, this all sounds like I'm doing a lot of skivvy work typing stuff in (which I hate) and not actually writing much code (which is the bit I like).
It is at this point where you can say “NONONO YOU ABSOLUTE DONKEY stop that we just want a FastAPI endpoint!!” And it will go “You’re absolutely right, I was over complicating this!”
1. If you don't use it soon enough, they keep it (shame on them, do the things you need to in order to be a money transmitter, you have billions of dollars)
2. Pay-go with billing warning and limits. You can use Claude like this through Google VertexAI
When it works for pure generation it's beautiful, when it doesn't it's ruinous enough to make me take two steps back. I'll have another go at getting with all the pure agentic rage everyone's talking about soon enough.
when its actually writing code its pretty hands off, unless you need to course correct to point it in a better direction