Hardly, if you worked with the web in the mid 90’s, modern tooling is a much larger improvement than what LLMs bring to the table on their own. Of course they aren’t on their own, people are leveraging generations of improvements and then stacking yet another boost on top of them.
Programming today is literally hundreds of times more productive than in 1950. It doesn’t feel that way because of scope creep, but imagine someone trying to create a modern AAA game using only assembly and nothing else. C didn’t show up until the 70’s, and even Fortran was a late 50’s invention. Go far enough back and people would set toggle switches and insert commands that way no keyboards whatsoever.
Move forward to the 1960’s and people coded on stacks of punch cards and would need to wait for access to a compiler overnight. So just imagine the productivity boost of a text editor and a compiler. I’m not taking an IDE with syntax checks etc, just a simple text editor was a huge step up.
Well, even with more primitive tools people would crete an abstraction of their own for the game - even in very old games you will find some rudimentary scripting languages and abstractions.
Yes that's the point. You needed to do this (accidental) work, in order to do what you actually wanted to achieve. Hence there was less time spend on the actual (~business) problem and hence the whole thing was less productive
Oh I disagree. Like the GP, I’ve been round the block too. And there’s entire areas of computing that we take for granted as being code free now but that used to require technical expertise.
Django/Rails-like platforms revolutionised programming for the web, people take web frameworks for granted now but it wasn't always like that.
And PHP (the programming language) just before that, that was a huge change in "democratising" programming and making it easier, we wouldn't have had the web of the last 20-25 years without PHP.
From what I have seen LLMs are the worst (by far) in terms of gained productivity. I'd rate the simple but type correct auto complete higher than what I get from the "AI" (code that makes little sense and/or doesn't comply)
Supermaven recently suggested that I comment a new file with “This file belongs to {competitor’s URL}.” So, it’s definitely not at the point you can just blindly follow it.
That said, it’s a really nice tool. AI will probably be part of most developer’s toolkits moving forward the way LSP and basic IDE features are.
I wish my ide would type correct the llm. When the funchion doesn't exist look for one with a similar name (often case is differnt or someother thing), also show me the prarmeter option because the llm never gets order right and often skips one.
Going from punched cards to interactive terminals surely must have been a big productivity boost. And going from text based CAD to what is possible on modern workstations has probably also helped a bit in that field.
In that view I'd say the productivity boost by LLMs is somewhat disappointing, especially with respect to how amazing they are.
I think the field is too new and the successful stories too private atm. However I think the best apples to apples example in this context is Amz's codebase update project that they've blogged about.
From memory, they took some old java projects, and had some LLM driven "agents" update the codebase to recent java. I don't know java enough to know how "hard" this task is, but asking around I've heard that "analog" tools for this exist, but aren't that good, bork often, are hardcoded and so on.
Amz reported ~70% of code that came out passed code review, presumably the rest had to be tweaked by humans. I don't know if there are any "classical" tools that can do that ootb. So yeah, that's already imrpessive and "available today" so to speak.
Java is intent as code. It’s so verbose that you have to use an IDE to not go crazy with all the typings. And when using an IDE, you autocomplete more than you type because of all the information that exists in the code
quantifying programmer productivity has been a problem since its inception. lines of code is a terrible metric. so is Jira ticket points. I can tell you that using an LLM, I can make a chrome extension to put a div that says "hello world" at the top of every webpage far quicker than if I had to read the specifications of extension manifests and how to do it manually but how do you quantify that generically? how do you quantify that vs the wasted time because it doesn't understand some nuance of what I'm asking it to do, or when it gets confused about something and goes in circles?
The problem is not what ai can do rather most people in the workforce don't how to use the current generation of Ai. As the children that grew up with using chat gpt etc get into the workforce then only will we see the real benefits of AI.
Oh yeah, the "digital native" myth. I'm not convinced children using ChatGPT to do their homework will actually make them more productive workers. More likely it's going to have the opposite effect, as they're going to lack deeper understanding that you can build only through doing the homework yourself.
Really it's not about just using technology, but how you use it. Lots of adults expected kids with smartphones to be generally good with technology, but that's not what we're witnessing now. It turns out browsing TikTok and Snapchat doesn't teach you much about things like file system, text editing, spreadsheets, skills that you actually need as a typical office worker.
That's different from what I talking about it's the problem of inertia people already in jobs are used to doing them in a particular way. New curious driven people that get into the work force would optimize a lot of office work. A 10-12 year old that has learned how to use Ai from the very start will be using an AI that has 12-15 years of incremental improvements when he or she gets into the work force.
A lot of people here on hacker news disparage newer generations. But how many of you can run a tube based or punched based computer. So if you don't know are you an idiot?
