I realize the subscription rates are running at a loss for the LLM providers, but… costs are also dropping. Anyway, the Claude $200 per month subscription rate is more tokens than I could practically use doing heavy software engineering 40 hours a week. If I saturated it with jobs around the clock I could use up all the tokens in the $200/month subscription in about a week, but that’s 168 hours. Working a 40 hour schedule, even at 4.33 weeks per month that’s only 173 hours… I’d hope people spend at least 5 hours a month doing something besides babysitting their LLM console.
Now, one way to burn tokens at an epic rate is to launch multiple projects in parallel, three or even four sessions open at one time working on different things, or possibly different aspects of the same thing. That’s also a good way to completely lose the picture of what the LLM is building and have no idea how a thing works when it gets done. I’m sure there are plenty of software development houses trying to “optimize” their workforce this way - I suspect their risks are… significant.
The vetting for those offshore programmers ain’t worth it tbh.
How many will you go through till you get a competent one? I worked at a company with an office in India and… Maybe 20% of the staff there were gifted and hardworking, 80% were a net detriment to the product we were building.
The office was closed. I hope they kept on the people who were actually good as remote employees but I have no idea.
Sad reality, I’m using LLMs to review the work of our offshore programmers, and as you say: some are good, some are not - and sadly, the ones who are not are also not learning to leverage LLMs to improve their work products. Without LLM review, I’d be advocating to find some of our offshore programmers “more productive ways to apply their skills.” With four rounds of LLM review, I’m effectively rewriting (the bad ones’) code for them… every… single… pull request.
My best offshore coder figured out how to use the LLMs to review his own code, we have architecture discussions about the best things to do and never have issues with how they are done.
My worst offshore coder “doesn’t believe in using AI” and continues to submit code for merge to master branch with obvious race conditions, panic crashes, etc.
Yeah, like the rest of LLM output, I’d say 80% of an average code review is worth considering - and if that includes anything you might have otherwise missed, that’s a win compared to learning about the problem post-launch.
We are getting there - with 4,33 weeks a month that’s $866 a month in AI costs. You may get a programmer for that in some offshore countries
I realize the subscription rates are running at a loss for the LLM providers, but… costs are also dropping. Anyway, the Claude $200 per month subscription rate is more tokens than I could practically use doing heavy software engineering 40 hours a week. If I saturated it with jobs around the clock I could use up all the tokens in the $200/month subscription in about a week, but that’s 168 hours. Working a 40 hour schedule, even at 4.33 weeks per month that’s only 173 hours… I’d hope people spend at least 5 hours a month doing something besides babysitting their LLM console.
Now, one way to burn tokens at an epic rate is to launch multiple projects in parallel, three or even four sessions open at one time working on different things, or possibly different aspects of the same thing. That’s also a good way to completely lose the picture of what the LLM is building and have no idea how a thing works when it gets done. I’m sure there are plenty of software development houses trying to “optimize” their workforce this way - I suspect their risks are… significant.
The vetting for those offshore programmers ain’t worth it tbh.
How many will you go through till you get a competent one? I worked at a company with an office in India and… Maybe 20% of the staff there were gifted and hardworking, 80% were a net detriment to the product we were building.
The office was closed. I hope they kept on the people who were actually good as remote employees but I have no idea.
Sad reality, I’m using LLMs to review the work of our offshore programmers, and as you say: some are good, some are not - and sadly, the ones who are not are also not learning to leverage LLMs to improve their work products. Without LLM review, I’d be advocating to find some of our offshore programmers “more productive ways to apply their skills.” With four rounds of LLM review, I’m effectively rewriting (the bad ones’) code for them… every… single… pull request.
My best offshore coder figured out how to use the LLMs to review his own code, we have architecture discussions about the best things to do and never have issues with how they are done.
My worst offshore coder “doesn’t believe in using AI” and continues to submit code for merge to master branch with obvious race conditions, panic crashes, etc.
Yeah, regardless of what one’s stance on AI generated code is, it’s a very useful tool for catching anything you might’ve missed.
Of course it can also be great at getting stuck on red herrings lol. That’s why I gave up on Mistral
Yeah, like the rest of LLM output, I’d say 80% of an average code review is worth considering - and if that includes anything you might have otherwise missed, that’s a win compared to learning about the problem post-launch.
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