131–140 of 321 posts
What are people doing at home? I have like 5 different apps I code on the $20/month Claude plan and like sure I can hit rate limits but - What are people doing to burn through $3k in tokens?
I suspect the people that burn through tokens have several subagents and 50 skills loaded and 40 MCP tools. All those load up the context on every single turn.
I feel like I must have plateued and don't know what to do next to level up. I'm currently on the $100/month codex plan and it seems fine using 5.5-xhigh all the time. I think of what to do next, have a chat session to determine exactly what to ask for up to the point of being ready to implement, and then codex churns on a commit-sized task whereupon I briefly check it on my local dev server. If necessary I ask for a…
I feel like I must have plateued and don't know what to do next to level up. I'm currently on the $100/month codex plan and it seems fine using 5.5-xhigh all the time. I think of what to do next, have a chat session to determine exactly what to ask for up to the point of being ready to implement, and then codex churns on a commit-sized task whereupon I briefly check it on my local dev server. If necessary I ask for a…
Patches to existing sizable codebases and reverse engineering binaries both can run a long time and use a lot of tokens without wandering off into the weeds.
> The first is to self host. You buy the machine, run open source models locally, and pay nothing per token after that. Power is not free. What I’ve found is that you’re basically paying a premium for privacy, and that’s worth it for me.
Luckily I needed a new laptop and I bought an M1 Max secondhand from a friend quite cheaply because it was fast enough to recompile something else I am interested in. So for me, there is no additional hardware cost; it was acquired in replacement. I run the AI models at home on this kit because I want to; I'll use openrouter if I need to. I accept the economics of this article are right. But I feel so incredibly sad…
> The first is to self host. You buy the machine, run open source models locally, and pay nothing per token after that. Power is not free. What I’ve found is that you’re basically paying a premium for privacy, and that’s worth it for me.
Luckily I needed a new laptop and I bought an M1 Max secondhand from a friend quite cheaply because it was fast enough to recompile something else I am interested in. So for me, there is no additional hardware cost; it was acquired in replacement. I run the AI models at home on this kit because I want to; I'll use openrouter if I need to. I accept the economics of this article are right. But I feel so incredibly sad…
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.
Is spending (metered money) even worth it? Perhaps for most I mean "beyond like a 30 bucks a month," but for me I'm literally not spending more money beyond my very cheapo 16gb video card. No clue what y'all are doing, perhaps because I'm hobbying, and also I'm old and can perhaps do more of this by hand. But I'm basically just doing what I did before, plus ollama self hosted and sometimes gemini and I feel like I'm…
If you hunt in the settings you can restrict your account to only use EU servers for inference... Which means you can't use a lot of the US frontier models, but you can use all the Chinese ones, albeit within EU GDPR, etc.
This to me is a good compromise between privacy and cost.
I feel like I must have plateued and don't know what to do next to level up. I'm currently on the $100/month codex plan and it seems fine using 5.5-xhigh all the time. I think of what to do next, have a chat session to determine exactly what to ask for up to the point of being ready to implement, and then codex churns on a commit-sized task whereupon I briefly check it on my local dev server. If necessary I ask for a…
As everyone trying to do real work is finding, that's the actual bottleneck. If the system is keeping up with your thinking, you're doing fine. You can't "level up" your thinking by paying for more tokens. The people doing more automatic stuff are probably outpacing their own thinking, and that will bite them eventually.
> The first is to self host. You buy the machine, run open source models locally, and pay nothing per token after that. Power is not free. What I’ve found is that you’re basically paying a premium for privacy, and that’s worth it for me.
>> Power is not free. There's actually an interesting thought experiment here: if it takes you a full day to build something that AI would otherwise build in a day, do you end up using more power, or less? What is the break-even point, purely from a power consumption perspective?
I've run the napkin math, and assuming LLMs make humans even 5% more efficient, the power and water savings over time are significant, largely because humans are so resource intensive: https://news.ycombinator.com/item?id=46984659