[dpcan]

I cannot figure out what people are doing to spend all this money.

I have used a $60 per month Cursor plan on auto, and have never come close to using up my included usage, and I probably have it planning and coding and working for me all through the evenings 4 nights a week.

What on earth are people doing differently that it's costing them so much?

Maybe enabling on-demand usage or other paid models, or on higher modes? What are you doing that requires this? The output from Auto for me is crazy good for the tasks I'm working on, and have yet to run into an issue where it couldn't perform at a high enough level.

We have been interviewing people at work to join our team and they tell us they use $2K per month in tokens with their current employers.... I can't even fathom what's going on here where that would be happening.

[isubkhankulov]

Claude enterprise plans are 30-40x more expensive vs the consumer plans.

I used to spend $200/mth on the Max plan at a small startup. Now spending single digit thousands on Claude enterprise with the same usage levels.

Anthropic is subsidizing consumer usage, and also charging a nice margin for enterprises for zero data retention (ZDR)

[cubano]

> and they tell us they use $2K per month in tokens with their current employers...

perhaps they are simply trying to impress you with their mad prompting skills and like, what self-respecting engineer would be caught dead using less then $2k/month?

giving the context of your interaction with those people, it probably is the simplest answer to your rather baffling question. for the life of me the idea of using $2k/month doesn't even seem possible unless your telling it to waste credits.

[galaxyLogic]

Sounds about right. Those people seem to want to create the impression that they are "AI Power Users". That gives them more power inside the organization. People come to them to ask for advice. Also if their output is not good they can claim that is because the AI budget didn't allow them to do more.

[shepherdjerred]

If you can give your agent broad access and an effective feedback loop, you just need to steer it and do a final check on outputs.

As an example I might have an agent with access to a browser, logs, metrics, GitHub& CI logs etc. and ask it to implement a new feature.

In Slack I have a few bug reports so I spin up a few more agents. A PM needs a UI tweak so I spin up an agent. You can imagine that a lot of work a dev does isn’t necessarily that complicated and I just need to be there to review the final PR and leave comments as if it were a colleagues (and then my agent goes back, fixes the comments, requests a new review…)

While that’s happening I might be using my actual attention for a meaty feature, design doc, data analysis, etc.

I spend $300/mo for personal use, and a couple thousand at work. Agents can be really transformative and well worth the cost.

Would my company rather pay a few thousand per month, or a several hundred thousand per year for an extra fully loaded engineer? At this point it is _at least_ a 2x multiplier for myself

[jmkni]

Totally agree, but then a lot of the same people will be talking about all of the custom instructions/rules/skills/features etc they have set up, so that's eating up a lot of the context window before you even start

When I do use AI, it's just the pure tool itself, and the context is the exact code I'm working with (because I'm trying to see if it can help me solve a specific problem), and I understand the rest of the codebase well enough to know if it's giving me good answers or bad ones

[sbochins]

To be honest I’m not doing too much. I’m just on one of the $200 plans, but always hit limits. I only use the best models and mostly use it for various software projects I always wanted to build, but didn’t have time for. I just closely monitor the usage caps and have something running on a Ralph loop most of the time, unless I get near the cap. The post here is more about how I’d start a self-funded software company, if I wasn’t already working full time.

[rjh29]

A few things imo, 1) not prompting precisely enough (narrowing scope) means your agent will scan your entire code-base and sometimes get stuck looking at things repeatedly. 2) not checking the output is usually fine but sometimes it produces junk because it doesn't understand, and you cannot prompt your way out of it without reading the code and figuring out the problem. If you leave it on auto it will burn tokens.

Plenty of low level things can trip agents up, too. I just had one inexplicably refuse to read an error about a function needing a bool return value - trying about 10 variations of the same thing before I interrupted it. Skills probably cause issues too, it loves to for example read the source code of libraries I'm using if I give it permission. That's a rabbit hole.

[therealdrag0]

Cursor on Auto will use Composer a lot, right?, which is much more efficient than frontier models people spend a lot of money on.

Besides that it’s simply reading or writing a lot of code. The only time I spend 1k/mo was when I built a green field 20k Loc service with 2 other people (while also doing antagonistic code reviews etc)(mostly using Opus). So it took $3-5k to build a 20k loc production grade service in a critical domain.

But most of the time I’m not doing that. As they say most engineering isn’t coding.