I didn’t realize how important putting meetings on your calendar for one-off work conversations you have are when you at work uses AI productivity monitoring. I need to do a better job of that.
GitHub can’t focus on the basics like a stable platform. However, when they release stack commits a few weeks ago somebody had time to make the hamburger menu an unprofessional stack of pancakes…cute.
While i get the sentiment and the frustration, I highly doubt an SRE worked on the hamburger menu.
In my experience some teams move a lot faster than others and that leads to asymmetric quality. If all devs could pick up a new language and skillset overnigh then companies would have a lot more flexibility in their roadmaps, but humans don't scale that way - with or without AI.
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.
Maybe a dumb question, but what are you doing/seeing others do that uses that many tokens? I find myself pressing the weekly caps on the $20/month plan only when I'm really having the LLMs go wild with the Xtra high effort on the newest/biggest models on abstract problems or where I don't really understand the problem well. (E.g. improving ML models, planning creative molecule synthesis pipelines, identifying subtle performance problems etc)
Generic CRUD/Config stuff I do for work (and assume most software jobs entail? Maybe not correct) doesn't use a significant amount of tokens.
I routinely hit the limits on a Claude pro max 20 account for personal projects. For context I have 26 years of professional experience and have been programming for around 40 years.
In addition I have virtually unconstrained usage at work (for now).
Tasks that I do on my personal account:
- building stuff for my wife's business
- analyzing and experimentation and building harnesses to test other models/services
- processing interesting research papers that publish without code or sufficient data to replicate the work
And that's besides simple stuff like exploring new topics I am interested in, and building learning assistants and personal tooling, and eliminating technical chores.
At least for myself personally: Opus 5 Ultra spreading out hundreds of subagents on specific tasks can gobble tokens like mad. Recently I did a custom OCR pipeline in a day and some Revit automation, extremely large datasets, but I definitely spent good money to make it happen so fast.
I almost certainly wasted tokens, but right now things are subsidized, so it works.
> Maybe a dumb question, but what are you doing/seeing others do that uses that many tokens? I find myself pressing the weekly caps on the $20/month plan
I don’t run into many issue with my personal subscription plans. However, at work while companies like Anthropic offer “Enterprise” plans, you still get billed at API rates which are quite high. The subscription plans are an incredible deal and subsidize these tokens, but these plans aren’t offered to large organizations.
It's also kind of odd because even a junior engineer has to cost a company around 10 grand a month in salary, taxes, and other costs. So if the company thinks it makes you 10% more effective it seems like it should be an easy choice. So either the companies are shooting themselves in the foot limiting spending or they aren't seeing the productivity boost.
Fully loaded employee cost is typically around 2x their actual salary. Junior employees making only $60k/yr is absolutely nothing. It’s lowish even in most parts of the western world.
You can also get cheap devs in Central or South America or Eastern Europe too. Doesn’t make it untrue that large parts of the world have junior devs much more expensive than that.
The software development world and ecosystem. I’d say all of the US, major parts of Canada, and major parts of Europe constitute a large part of software developers.
They were talking about what it costs the company, not just the salary. There are taxes, insurances, equipment costs, etc.
10k might be a bit too high, but it's far from "absolutely ridiculous" amounts of being too high. An employee with a 5k salary can easily cost the employer 7-8k
In the US, it’s really difficult to live a middle class lifestyle if you’re not making at least low to mid 100k. I don’t see any starting software salaries at good companies below 100k even in the Midwest.
Sure in the US. But people are throwing token caps in 500, 1000, 2000 dollar range here. That is a very significant expense on top of salary, taxes and benefis. It's only justifiable if they observe 20% 30% or more productivity increases across the board.
If you have huge salaries, yeah sure 500 dollars its okay even if you only get 5 10% more productive.
On business side orgs are now absorbing costs of tokens to their own local budgets...so the calculus soon will be:1 extra engineer or extra token spend for existing ones. Tbh, when the productivity payoff becomes more obvious I would happily take the latter.
Most "user generated content" is no longer user generated, or at least not in the traditional sense. It is mostly advertiser generated these days. There are multiple competing ad agencies that poison the well on sites like this with content that is designed to look like word of mouth, but is actually an ad.
The em dash in the subject was a sign of an llm generated post and the community avoided it? Now reposted in a technical manner and getting community reaction /s, maybe
