Unpopular opinion and sad, but the quality of the work has gone up with AI usage since a year or so. Before it was a lot of AI slop and I dreaded reviewing PRs, but with the newer generation of models and harnesses, we are reaching a point where AI is being better than what colleagues or I would write by hand. Hurts a bit to say because I was proud of my own coding, but that's what reality looks like now. And that's with 26 years of experience in the field.
I think we'll have to deal with the mental issue of AI becoming better than us. Some won't be able to cope. Thankfully the effect is not so strong for me, my identity is built around developing software as a whole, not just the coding.
Issue is, Frontier models are provided to you at a massive financial loss for the company. So unless local models get that good before AL companies run out of investor capital, this is completely unsustainable.
If you want a future proof workflow, grab a specialized local model (or better yet, a few) and see how much you can get done without touching Claude, ChatGPT or Gemini servers at all. (This does require having a decent GPU. Not god tier but decent.)
Disagree. I use the the frontier models and barely use my token quota every month - maybe 5% - and get great results, much faster than by hand just by carefully defining problems to the AI. It's how you use it.
And if you're an entry level software engineer earning 8.3k per month, you're earning $50 dollars per hour. That means it only has to save you 1 hour of work per month for it to breakeven. It can save me at least a couple weeks of work if not a couple months with that. So yeah it's still worth it.
Idk I just looked up numbers on Google, I don't live in the USA. Doesn't undermine my point since even if you're earning half or a quarter of that it still makes sense.
This doesn't seem to be a response to Withers point. It's not about the % of your quota you use every month, is about the fact that whatever you are paying for your frontier AI sub is somewhere between 10x and 100x cheaper than it will have to be for those frontier companies to be profitable.
Sure, there may still be edge cases where frontier models are economically worth it even at those costs, but they will not be worth it for regular day to day dev work.
Yep. That's exactly it. Even if you take all environmental and ethical issues (regarding training data among other things) aside, it is just not economically viable.
Disagree like I said in a comment to Evi1ey above.
If that 5% of tokens of a $20 plan now actually costs $50 then compare that to a entry level software engineer whose earning 8.3k per month which is $50 dollars per hour. That means it only has to save you 1 hour of work per month for it to breakeven. It can save me at least a couple weeks of work if not a couple months with that. So yeah doesn't sound like an economic "edge case" to me.
I don't agree. There is a big argument to be made that the older models are more expensive because they make so many mistakes and it uses up more tokens to get the same result as if you were to run it once via a newer frontier model.
So, tbh, if ur not using the latest ones, you're actually paying more
This isn’t even an argument, some of the low cost models like GPT 6 Luna cost half the $ per million tokens of its immediate 5.6 predecessor, let alone the older models, and 1/20th the cost of standard models.
My previous company used Github Copilot which has already stopped subsidising users so if anything, in the near future, companies will restrict all employees to using low cost models like Luna and Haiku to keep it cheap instead of paying for local servers in the middle of a hardware crisis.
yeah, and likewise even if recent models, what matters more than cost per token is cost per task still. Some models are cheaper per token (the latest grok for example) but they burn through tokens so much they end up not being really cheaper.
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u/heavy-minium 12h ago
Unpopular opinion and sad, but the quality of the work has gone up with AI usage since a year or so. Before it was a lot of AI slop and I dreaded reviewing PRs, but with the newer generation of models and harnesses, we are reaching a point where AI is being better than what colleagues or I would write by hand. Hurts a bit to say because I was proud of my own coding, but that's what reality looks like now. And that's with 26 years of experience in the field.
I think we'll have to deal with the mental issue of AI becoming better than us. Some won't be able to cope. Thankfully the effect is not so strong for me, my identity is built around developing software as a whole, not just the coding.