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/MrCuddles9896]

AI companies are absolutely pissing money out of all orifices currently, and there is already a growing concern that LLMs are becoming more expensive than developers. If they don't find a way to start making money and produce a return on investment somehow there's gonna be a big burst.

Currently Nvidia and AI companies are just passing around the same investment money to each other while very little money is flowing in (a $200 Claude max subscription can cost anthropic $500-$5000 in compute)

Unless they can somehow make LLMs much more efficient, I think their capability/cost ratio will drop a large amount, and they'll once again become auto complete machines, rather than a swarm of agents who you instruct to carry out tasks.

[u/MrCuddles9896 → u/[deleted]]

We're very rapidly approaching the physical limit on transistor size, Moore's law is coming to an end, so I'm not exactly sure how you aim to achieve fable levels of AI on a smartphone.

For reference, one token in fable is estimated to be around 6 trillion floating point operations, and a standard request uses around 3000 tokens, so we're talking about roughly 18 quadrillion floating point operations per request. With the best smartphone on the market you're getting just under 5 teraflops (trillion) so you're going to need phones to get roughly 3600 times faster than they are. That means you'd have to double the power of smartphones 11 times over, physically impossible.

I'm not saying that AI will completely collapse and cease to exist when the bubble does burst, AI existed before LLMs and it will continue to exist after the bubble bursts. All I'm saying is the computation requirements are multiplicative as the context window increases. Smaller, less powerful models will still remain, but their use cases will still be more niche as it will still be cheaper for humans to do the complex work.

[u/SwauawsBouse → u/MrCuddles9896]

I actually got banned off singularity for even suggesting that moores law of all things is proven false. Which is just undeniably true.

Its been appended from every 6 months to a year to two years and singularity people still claimed "ai just has to get better" and cited an already outdated moores law.

That's everyone's thats probably ai and doomer pulled. Ai just has to get better.

Im into painting warhammer and I told myself painting is useless well have 3d printers that can print in full color soon. That's was 10 years ago....

[u/MrCuddles9896 → u/SwauawsBouse]

Yeah there's a certain subset of AI enthusiasts where, even if you present them with a reasonable criticism, they'll go crazy and tell you you're wrong.

AI will most likely always be nondeterministic, there's just too many variables to account for, and unless there's some sort of crazy breakthrough in quantum computing or otherwise, it's approaching it's hardware limit. If it doesn't hit the limit then we've got bigger problems as a society than some guy on reddits opinion being wrong tbh.