Is the industry ready for tokens-constrained work?

cebert

I have similar concerns about this. The past year or so, software engineers have been encouraged by employers to adopt AI tooling and agentic coding. Now, many enterprises, including mine, are starting to crack down on token spend. I’ve learned how to fully embrace agentic tooling to do tasks like keeping up with vulnerability reports, initially triaging defects that come in, etc. It would be hard for me to do things the old way at this point when I know tools are available that could make me more productive for a particular category of tasks. My employer is considered capping all engineers at $200 or $500/mo of token spend depending on level. I regularly spend over $1k/mo today, but believe I can make a strong business justification for the value those tokens are creating. At this point, I think engineers may be asking what token budgets are when considering new roles.

Aboutplants

I tend to think this will end up being a good thing. It will force people to actually think about the best use cases and utilization of tokens while others will push to optimize models and tools to improve cost and efficiency. “Life finds a way”

stephbook

You know what happened the last years when the internet went down and there were no emails, no Microsoft Teams, no "npm install", no stackoverflow, no Google, no coordination with other locations? You know what happened when a PC broke? You know what happens at a construction site when the excavator breaks down? Exactly nothing — and that's okay.

sokoloff

Rationing tokens on a spend level or count makes no sense to me. Why would I pay $10-20K/mo to employ a software engineer and then balk at a $500, $1000, or even $2000 monthly AI bill, assuming they were even vaguely trying to use the tokens productively? I’m not an AI-maximalist, but “work a few days with AI and the rest of the month without because of cost” sounds literally crazy to me. (If you think AI is low/zero/negative net value, don’t do the first half; if it has net value, don’t do the second half.)

deadbabe

I don't think people understand, tokens must never be constrained. Right now, LLMs are the worst they'll ever be, but imagine what they will be like at the peak: Anything you want to code, coded instantly. Not waiting for code to stream in or wait hours for some agents to crunch through loops and planned: it just appears on the screen instantly like the way a webpage loads. Then imagine it can be done locally, on your device. Need an entire new custom operating system from scratch for some obscure hardware? Done. Here it is. That's going to be like pure crack to anyone who needs to do absolutely anything. That's going to be like our generation's version of "today's supercomputers will someday be in everyone's pocket".

toofy

this will mirror what happened in the past. if i’m not mistaken, in the past, people had limited time on “the mainframe”. so eventually they brought in what would be the equivalence of a local model… small computers that could do smaller tasks locally so they didn’t have to keep shelling out money to the mainframe gods and be handcuffed for usable time. i could absolutely be mistaken that this is how it worked, it was before my time. but this is how people explain it worked for them. i don’t think most work gives a shit about soa. smaller repeatable tasks can absolutely be run just fine on smaller local models. sure, we’ll upgrade models occasionally just like we went from suitcase sized laptops to whatever we use today. this idea the hypedorks are pushing that soa is the only way is hilarious. hobbyists spend stupid money on classic cars, tools for woodworking, or whatever. spending money to do a hobby at home has never stopped wonks and their hobbies and businesses will do the same, spend to run models locally. the sooner the hypeTrash does what hype always does, fades to irrelevance, the sooner we can get back to work.

theanonymousone

In my personal anecdotes, Luna has changed calculations, once again; I'm _almost_ unconstrained in spending (my employer's Copilot subscription) tokens as long as its Luna. And it works more than good enough.

unified101

The elephant in the room is that the choice today is llm limits. Tomorrow 2 engineers at 50% token time will change to 1 engineer with 100% token time for the same work.. the latter is too cost effective.

skybrian

I’m using Luna all the time now since it seems quite good enough for everyday programming and so that my $20/month ChatGPT subscription doesn’t hit the weekly limit. It’s an artificial constraint. I could afford to spend more on my hobbyist programming but I choose not to. I suspect that I’m adapting to the model by giving it more concrete guidance and guardrails. I read code more and I tell it to refactor code that I don’t like. Working within constraints isn’t all bad.

Taikhoom2010

Simply put token spending is way overblown, and prices have fallen and should continue to do so, as the pricing power of frontier Labs dissapate. https://s-1.vercel.app/posts/the-struggle-of-openai/

variadix

On-prem AI is another solution. I’m surprised more companies aren’t leaning in this direction due to security/IP concerns. My employer is planning to spend several million on local AI hardware.

ironqcold

I think we're still in the early days of figuring out how to use AI as a daily work tool. It's going to take time to develop the right practices. I do see the point in having token limits, they force you to be intentional. My guess is that eventually we'll end up with small, local LLMs that are unlimited for routine stuff, and we'll save the big expensive models (with quotas) for the heavy lifting.

jgmedr

Currently navigating this situation at my employer. We went from virtually unlimited token spend per software engineer, to $150 per month due the recent change in billing terms from GitHub Copilot. Rationed over a month, about $7.50 per day. Basically, a couple bad apples spoiled the bunch (contractors using Opus to center divs). We're 15 days into this new policy and its going ~okay~. Engineers adapt as they do, and have been leaning on `gpt-5.6-luna xhigh`. Some contractors have already hit their budget limit for the month. A couple observations here: 1. Because LLMs/agents are tools, limiting their usage becomes a distraction and ends up being more of a drag on each individual's productivity. Instead of "just doing the work" engineers are now wasting time tinkering with setups (graphs, caveman skills, etc.). 2. Skill atrophy is real. Engineers that hit their budgets are seemingly less productive and less capable which is deeply concerning. 3. There are legitimate conversations happening now to explore open source harnesses (opencode/pi) and open weight models at the company in order offset the costs associated with going through a standard provider. 4. Token prices are venture capital subsidies. Its essentially free samples to get the market hooked on their addictive white collar drug. Remember when an Uber cost $7? As soon as OpenAI and Anthropic go public, they will need to begin showing progress toward profitability. That is when the true price of a token will be revealed.

fullautomation

I'm sorry to see that the post has been removed by HN moderation for literally no reason considering the tones of the article and the discussion here: https://news.social-protocols.org/stats?id=49319582