I was recently replaced by a young developer and the only thing that keeps me smiling is that they still haven’t fixed the part of the application I raised concerns about (because the young dev decided to write on a fresh non-compatible stack even after my warnings). I hope eventually it leads to their own loss of career since that’s what they did to me. All of that to say that Llms have made people into over confident morons.
That being said, I can't see this entire field existing in five years anymore. I'm hoping for at least two more years, but who knows?
This stuff is coming for all white collar, the barrier to entry is completely gone now. Maybe not the barrier to mastery (yet), but the bottom has fallen out.
And I’m wondering if this isn’t the enormous amount of organizational debt from having security second to everything finally coming calling.
I _am_ a craftsman - software, wood, and a few more domains. There is a lot of personal satisfaction I find in woodcraft through the motion and the exercise. I love that this is a luxury hobby instead of a personal necessity. The difference there is that if I take my time on personal necessity where the market isn't paying for it, I may take food out of my kids' mouths or lose the roof over their head. Luxury craft hobbies face only self-imposed pressures.
AI is letting me build similarly. I can continue to craft my Rust and my Python and my Typescript and my Fortran to my heart's content - and those skills help in the day to day - yet I'm also able to compete in the market and build things that were really infeasible before.
It's still valuable to deeply understand parts of a program, but we don't have any tooling that helps us do that. We just have to raw-dog it by thinking really really hard and remembering how all the code connects together.
I want a tool that gives programmers a place to record their thoughts. Developers need a place to draw and write, and also interleave blocks of code that automatically update to match the actual state of the code.
The closest thing I know to this is org-babel, part of Emacs, which allows you to push code blocks out of an org file into an actual source files, or pull them in from actual source files. This is mostly done manually by invoking functions called `tangle` and `detangle`.
I intend to investigate this further in Emacs, since I'm an Emacs user, but Emacs is never going to be the friendly UI we need to make this tooling common.
Now, when someone sends a working PR in, even high quality and well tested, they may actually have no idea how it works.
I left software and went into violin making and I couldn't be happier (though of course I'm extremely fortunate to have saved up enough in my software career to comfortably make the transition). In violin making a tenth of a millimeter is considered a lot and we endlessly stress over details like the corner shape and the f-holes. And while some of this nitpicking is certainly excessive, it serves more as proof to show that we're extremely careful with the details so that stuff that really matter, like tonal quality and playability, will also get enough detailed focus.
Wrote a post some time ago on how we'd be helped by segmenting and ranking the domains of our systems so we can be deliberate about where we stop short of full automation: https://ljtn.github.io/epiq/blog/cost-of-cognitive-debt.html
Offering hobbies, which require ppl to already be supporting themselves, is like a slap in the face.
This is like telling a coal miner that if they enjoyed the work they did in their career, they can go digging tunnels in chalk cliffs after renewable energy destroys the demand for coal.
cool to see it come full circle and see another person thrown into the industry by the work of another forum member.
What I think we're likely to witness here, or at least what AI investors ultimately are hoping to see happen, is the displacement of code as we know it (often already sorely lacking in quality and craft) displaced not by more of the same, but a massive profusion of shittier, more homogenous code. It won't have to win by being better; it'll be able to do that by being cheaper alone. And we're frankly kidding ourselves if we think that doesn't mean a profound deskilling and potentially deprofessionalization across the whole class.
The problem with this outlook (not with you personally) is that the increase in accessibility for you comes at a cost, but the way things work these days the cost is not paid by you but by someone else — someone you'll probably never even meet. The cost has been abstracted away from you and foisted onto somebody else against their will. This shows up as people adversely affected by local data centers (increased pollution, higher electricity prices), people displaced in the workforce (author of the article), people of the future who will not understand things because it's easier to skip understanding for now (students, early learners), and so many more.
It's very liberating — so long as you are given the ability to not think about the consequences for these other people, and the abstraction process by which AI companies are providing their services gives you that freedom by design. At the very least, it is something about which you perhaps ought to be wary.
I do it differently, I focus on better recording what the user wanted, the so-called "user intent". To do this, I record all messages typed by the user since the start of the project, whether 3,000 or 10,000 messages. An LLM can churn through them in 10 minutes and derive a fresh, up-to-date interpretation from the raw data. This can be used to judge whether the implementation has diverged from the intent, or, in other words, to realign the code and tests. The messages the user writes are usually designs or corrections, a very rich, compact signal. If the user struggles with something, it could result in a tool, a skill, updates to the project docs, or new tests.
Could be just defining the methods without filling them but depending on the mood I code more by hand or less.
Part of woe is that once you've reviewed, validated, and comprehended a piece... Later gets casually mangled by some other LLM-generated urgent change.
techgnosis•43m ago
I'm less pessimistic than the author though. There is always room for people who know what they are talking about. Take a deep breath.
kypro•30m ago
derektank•18m ago
sampullman•12m ago
I'm not sure how it plays out in 5 or 10 years, but that's how it is now.
Icathian•12m ago
oxmo456•11m ago
fancyfredbot•8m ago
Knowledge has been available just by asking Google for decades now. The LLM makes it easier but it's a difference of degree not of kind
Until the models are 100% reliable knowledge will be required in order to quickly spot issues and work efficiently with the model to address them.
kphorn•13m ago
jaapz•7m ago
But what will their day to day look like? Meetings?
Previously, I'd have to work days undisturbed to get important stuff out of the door. There was effort involved to reach an elegant solution that fit business need.
Now I'm a meat bag pressing enter on a "recommended" option Claude already figured out was the best approach.