It's not though. It's fundamentally different because TurboTax will still work with clear deterministic algorithms. We need to see that the jump to AI is not a jump from hand written math to calculators. It's a jump from understanding how the math works to another world of depending on magic machines that spit out numbers that sort of work 90% of the time.
They probably wouldn't think that the calculator makes them faster either
If we assume that there are 50 weeks per year, this gives us about 400-500 lines of code per week. Even at long average 65 chars per line, it goes not higher than 33K bytes per week. Your comment is about 1250 bytes long, if you write four such comments per day whole week, you would exceed that 33K bytes limit.
I find this amusing.
My software engineering experience longs almost 37 years now (December will be anniversary), six-to-seven years more than Earth's human population median age. I had two burnouts through that time, but no carpal tunnel syndrome symptoms at all. When I code, I prefer to factor subproblems out, it reduces typing and support costs.
That said, I am also actively experimenting with VTT solutions which are getting quite good.
So only the old hands allowed from now on, or how are we going to provide these learning opportunities at scale for new developers?
Serious question.
Employers were already refusing to hire juniors, even when 0.5-1 years' salary for a junior would be cheaper than spending the same on hiring a senior.
They'll never accept intentionally "slower" development for the greater good.
That comes post Chernobyl.
my last summer intern did everything the manual way, except for a chunk where I wanted him to get something done fast without having to learn all the underlying chunks
Always happy to mentor people at stagex and hashbang (orgs I founded).
Also being a maintainer of an influential open source project goes on a resume, and helps you get seen in a crowded market while boosting your skills and making the world better. Win/win all around.
I don't think SWE is a promising career to get started in today.
But pro-AI posts never seem to pin themselves down on whether code checked in will be read and understood by a human. Perhaps a lot of engineers work in “vibe-codeable” domains, but a huge amount of domains deal with money, health, financial reporting, etc. Then there are domains those domains use as infrastructure (OS, cloud, databases, networking, etc.)
Even where it is non-critical, such as a social media site, whether that site runs and serves ads (and bills for them correctly) is critical for that company.
you dont notice it when you are only looking at your own harness results, but the llm bakes so very much of your own skills and opinions into what it does.
LLMs still regurgitate a ton.
We have a completely broken internet with almost nothing using memory encryption, deterministic builds, full source bootstrapping, secure enclaves, end to end encryption, remote attestation, hardware security auth, or proper code review.
Decades of human cognitive work to be done here even with LLM help because the LLMs were trained to keep doing things the old way unless we direct them to do otherwise from our own base of experience on cutting edge security research no models are trained on sufficiently.
I suppose it's like bandwidth cost in the 90s. At some point, it becomes a commodity.
That is exactly been the situation for years. Once graduated accountants are not doing maths. They are using software (Exel, Xero etc.). They do need to know some basic formulas eg. NPV.
What they need to know is the law, current business practices etc.
If that's true, then you likely used to produce slop for code. :-(
> I did things the old way for 25 years and my carpal tunnels are wearing out.
You wrote so much code as to wear out your carpal tunner? Are you sure it isn't the documentation and the online chatter with your peers? :-(
... anyway, I know it's corny to say, but - you should have, and shoudl now, improve the ergonomics of your setup. Play with things like the depth of your keyboard on your desk, the height of the chair and the desk, with/without chair handrests, keyboard angle, etc.
> Job one of everyone I mentor is to build Linux from scratch
"from scratch" can mean any number of things.
Local models are quite good now, and can jump right in to projects I coded by hand, and add new features to them in my voice and style exactly the way I would have, and with more tests than I probably would have had time to write by hand.
Three months ago I thought this was not possible, but local models are getting shockingly good now. Even the best rust programmers I know look at output now and go "well, shit, that is how I would have written it too"
That is a hard thing to admit, but at some point one must accept reality.
> anyway, I know it's corny to say, but - you should have, and shoudl now, improve the ergonomics of your setup. Play with things like the depth of your keyboard on your desk, the height of the chair and the desk, with/without chair handrests, keyboard angle, etc.
I already type with colemak on a split keyboard with each half separated and tented 45 degrees on a saddle stool, with sit/stand desk I alternate. I have read all the research and applied all of it that I can. Without having done all that I probably would have had to change careers.
> "from scratch" can mean any number of things.
As far as I know I was the first person alive to deterministically build linux from 180 bytes of machine code, up to tinycc, to gcc, to a complete llvm native linux distribution.
When I say from scratch, I mean from scratch. Also, all of this before AI without any help from AI, but I sure do appreciate it to help with package maintenance and debugging while I am sleeping.