421–430 of 819 posts
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Are you saying there are only 30 million people employed in white collar jobs in the world?
About 30 million software developers. At least that's what a quick web search says.
https://openai.com/index/codex-for-every-role-tool-workflow/
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The examples I gave, and the arguments that usually support them don’t really translate into “building complicated systems”. I was talking about the arguments in support of variable naming flamewars, etc. I’m not proponent of AI generating everything without any supervision as of now. But willing to change my mind when it gets better. Most software engineering jobs are not cutting-edge tech, or research, or solving u…
So I accept that “nonsense arguments are nonsense”, but with some minor differences of opinion. Naming of things matters insofar as you care as a human to actually conceptualize the system you’re building. You can call all of this stuff minutiae, and on some level I kind of agree, except for the general vibe of _caring about the quality of the stuff you produce_. That is something that still matters whether it “works…
Generally we've modified our timelines heavily, systems are working as intended, company is still making money. There are some AI-authored commits that had mistakes that we didn't catch, but I'm sure this could've been an issue even if all were human-authored. I know first-hand multiple other companies who are doing exactly the same thing.
I agree with "slow is smooth, and smooth is fast" for mission critical systems. But super majority of systems are, indeed, not mission critical.
Just to put this in context. If every company did this, all over the world, with that same limit, we are talking about something around $45B monthly in revenue for all AI companies to share.
I think the main thing companies should try to understand is avoiding the use of 'claude -p'. I definitely have written a goal file, and then just ran claude in a loop over the goal in order to 'token max'... why not? I'm doing research and have some clear KPIs where research into all kinds of techniques / tuning can improve the results. I can spend my budget on a "experiment with blah blah blah to improve blah blah"…
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The issue is he’s not actually balanced at all. I’ve never seen him say anything negative about an AI product.
Days ago he said… “I'm finding that coding agents can take me from a vague idea to a working solution, one with tests and documentation and that looks like a carefully considered project evolved over the course of many weeks... in less than an hour. Even if the code is rock solid, there's a limit to how many projects like that I can sensibly care for - and if they're instantly abandoned, what value was there from cre…
Note that it's not surprising that he finds his own usage (described in the quote) negative, since his real job is as a blogger, not anything else.
Just to put this in context. If every company did this, all over the world, with that same limit, we are talking about something around $45B monthly in revenue for all AI companies to share.
And the obvious question: what it's the cost of that revenue? Because it looks huge but ...
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Isn't all the "knowledge" just text files? I've transitioned between services easily by simply copying the text files.
You can even just instruct the LLM to create a context file for you! They are surprisingly good at that as well.
That's a lot. On my usual day I burn less than $1 on Opus. I could get beyond $10 only if I have a complex and well-defined problem, which is rare (the second part at least).
Why there are so many people that still believe that AI coding is a fad? It's something that started less than two years ago and companies are already paying thousands per seat. I know one that gives you 5k per month. Which other tool went from nothing to this level of acceptance so quickly?
Because companies are betting that this spending will allow them to reduce cost by firing people. Right now the AI LLM PRs we're seeing are just introducing more work for other people, while these so-called builders are looking good with their new dashboards and functionality they're demoing. But you can't talk to them about the flow of the code. You can't ask them for their thinking as to why certain things are. It'…
There are plenty of valid criticisms or warnings about over-reliance on AI coding, but this is not one of them. Today, I am using a semi-autonomous agentic coding system which has an `interview` functionality built in - when it spits out the PR from the input, if you have questions about the motivation or context for a particular choice, you can start up a clone of the original agent in a sandbox to question it.
Now, you might claim that those responses aren't always reliable, accurate, or consistent, and that claim has a little more weight (though, in my experience, decreasingly so) - but it is _certainly_ not the case that you cannot interview an agent about choices made. I'm literally doing it every day.
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Today's frontier models will be tomorrows low-end option. I think whatever model you are using today will be less expensive to use a year or two from now.
Last year's o3 was more expensive than 5.5 is. Whatever model we are using now is probably be more expensive than next year's leading models will be.