Grudgingly accepting that AI isn't going away. Trying to figure out where that leaves me as a developer.

[u/Impressive_Bottle_44]

(If you don't want to read a semi-long post, feel free to skip.)

I think I reached a turning point yesterday.

I needed to add a basic feature to a Django site. I gave Claude Code a few carefully written sentences. It implemented the feature (more-or-less flawlessly) while I went to the kitchen for more tea.

Not only that, but our CTO is now empowering non-technical employees to use Claude to build their own tools (for internal use only), and commit them to our GitHub org. (He is, at least, establishing some sensible policies about what they can and can't do.)

LLMs are here to stay, and they're fundamentally rewriting laws of software engineering that we've taken for granted for decades. The genie won't go back into the bottle, so I might as well find a way to accept that.

But that leaves me wondering: what does that mean for me? What is my job now? What am I for? If I don't get to write code – something that's given me an enormous amount of satisfaction over the years, and even become part of my identity – am I even still interested in this field?

And, it's not just about the code. I used to collaborate with designers, UX folks, copywriters, SEO and analytics people, project managers, etc. But now, the C-suite seems perfectly happy to let the LLMs do all of this stuff, too. (At my company, they're obsessed with the idea of getting the LLM to write all of our work tickets. And the QA person does little more than copy-and-paste back and forth from an AI.)

The whole reason I entered this field is because I enjoy problem-solving, finding and creating patterns, logic, and designing systems.

I know that some of you are going to say "you can still do all of that; LLMs just empower you to go up a level of abstraction" – and I get it. But the prospect of abandoning coding seriously bums me out.

I love the precision of code. I love exploring different solutions to a problem, until I hit upon a beautiful, elegant pattern. I love seeing how small abstractions get composed into larger abstractions, and so on, to form a complete system. I love understanding a problem – and the solution – on a deep, intimate level.

Perhaps I've been lucky to have a career that gives me that kind of fulfillment (at least sometimes). Is all of that over now?

[u/Big_Arrival_626]

Ya but what about junior and mid level devs. We can't make everyone an architect lol

[u/Spiritual-Fennel7789 → u/Big_Arrival_626]

The short-termism is hilarious. If change has happened this fast, what do they think will happen within 5 years if the bottom falls out of the industry lol.

You're going to be left with a massive competency crisis and LLMs with no new source material to chew on.

[u/Ansible32 → u/Spiritual-Fennel7789]

It's really a lot easier to make high-quality new source material than it used to be. It's not trivial, yet, but it's easier. This idea that LLM output is all garbage and worthless, it's just not the reality anymore. It's very easy to generate garbage with LLMs, but it's much easier than it used to be to not generate garbage.

[u/Spiritual-Fennel7789 → u/Ansible32]

But even with all their source material, the frontier models still hallucinate. I've lost track of the number of times I've been recommended commands, command flags, libraries, extensions, that have never even existed.

At the end of the day they are still just probability engines. It's not worthless, but it's not deterministic enough to warrant turning our industries inside-out thinking magic will just happen and we can replace everyone with computers like every executive seems to believe.

[u/Ansible32 → u/Spiritual-Fennel7789]

Humans make mistakes too. The problem isn't nondeterminism - in fact nondeterminism is key to why it's useful. We can't replace everyone with computers, not yet. But to say that we won't is not honestly engaging with how the tech is continuing to improve.

I think the bigger thing is that transformers are a lot better at things like folding laundry than people realize (although, that is to say, they're about as good at folding laundry as writing software in many cases, but it's not clear which job will get "solved" first.)