Throw-away account because my original one is easily identifiable.
Does any starts to feel depressed about AI push and hype? I'm around ~45 and have been happily hacking and delivering stuff for 25 years.
I use AI daily — it's a useful tool. But the gap between the marketing and reality for many of us is hard to describe. The people and corporations and all those LinkedIn gurus, podcasters declaring our obsolescence are overwhelmingly people who've never built or maintained anything complex in their lives. I'm sick of posts showing developers as awesome managers orchestrating fleets of Codex and Claude Code instances — I don't know a single person who actually has access to unlimited quotas for that. I'm now scared to publish open source because some random AI agent might spam my repo with garbage PRs and issues. Are we really expected to deliver mediocre C compilers while emitting millions of tons of CO2 into the atmosphere just to make a handful of rich people even more rich? And suddenly we have something like Moltbook to pollute our planet even more. Where are we going with this?
Anybody feels something like that? I seriously thinking about leaving the industry to keep my mental health in control or switch to some tech that is hard for AI.
Then I decided to build something complex using Claude, and within a week I realized that whoever claims "90% of code is written by LLMs" is not being totally honest, the parts left out from such posts tell a different story: programming is going to get harder, not easier.
The project started great but turned into a large ball of spaghetti. It became really hard to extend, every feature you want to add requires Claude to rearrange large portions of the codebase. Debugging and reading logs are also very expensive tasks. If you don't have a mental model of the codebase, you have to rely on the LLM to read logs and figure things out for you.
Overall, my impression is that we need to use this as just another tool and get proficient at it, instead of thinking it will do everything.
Also, the recent Anthropic partnership with Accenture suggests otherwise [0]. If AI could do it all, why train humans?
So please don't leave the industry. I think it will get worse before it gets better. We need to stick around longer and plan for all this hype period.
[0] https://www.anthropic.com/news/anthropic-accenture-partnersh...
In order to combat that worry, I'm trying to focus on gratitude that I have had a career where I got paid for doing fun things (programming), rather than worrying about what if my career stops being fun. Many people never get that chance, after all, and live their entire lives working menial jobs just to put food on the table. I'm also trying to make my career less important to my own mental happiness by focusing on other things that are good and will not go away even if my career stops being fun (for me, that means my marriage and my faith).
It's not easy to do, at all. And it also doesn't help the worry that I might even lose my job entirely because the industry abandons sense and fires people in favor of LLMs. But it does help a little, and I'm hoping that with practice the mental discipline will get easier and I can let go of the anxiety some.
Even though I don't personally find AI terribly useful for my own actual work, I keep people happy by talking about it where possible. If someone has a suggestion involving something something fairly repetitive, I tell them "that sounds like a great use case for an AI agent", even if it is, in fact, a great use case for a shell script.
If someone has an inane question, I tell them "Have you tried asking copilot about this?" - it's the new "Let me google that for you...".
If someone has a request to add a new feature that seems useless and counterproductive, I tell them "That's a great idea! How about you do that, using AI?", instead of getting into a debate about why it won't work in practice.
I'm finding that mentioning AI in these contexts keeps people happy enough, without extensive personal use, for now at least.
I’ve been actively trying to apply AI to our field, but the friction is real. We require determinism, whereas AI fundamentally operates on probability.
The issue is the Pareto Principle in overdrive: AI gets you to 90% instantly, but in our environment, anything less than 100% is often a failure. Bridging that final 10% reliability gap is the real challenge.
Still, I view total replacement as inevitable. We are currently in a transition period where our job is to rigorously experiment and figure out how to safely cross that gap.
Good luck!
That said, I have a hunch we're heading toward a world where we stop reading AI-generated code the same way we stopped reading assembly. Not today, not tomorrow, but the direction feels clear.
Until then — yes, we need to understand every bit of what the AI writes.
I really, really love programming. I love learning about computers. I'm so lucky to get to do this for work and get paid pretty well to do it. It engages left and right brain. Yes, it's logic, math, all that; but writing code is creative, too. There are endless ways to solve a given problem, and you get to decide what approach is going to be cleanest, and readable, and maintainable, and just _feels_ right.
Honestly though, doing code reviews isn't my favorite part of the job. It's fine, but the fun part for me is actually _doing_ it. Understanding the problem space in front of me and the constraints and all the other factors, and then generating _my own_ ideas and putting them into the editor, and iterating.
So yeah, if the job becomes essentially reviewing AI code.. I don't know if I will still enjoy doing this. I mean, I'll do what I have to, I have a family, but it's not an exciting prospect.
I'm not anti-AI at all and I use it to speed me up in plenty of ways. I'll have it give me snippets of code here and there for stuff I need, I'm using Claude Code here when the use case is right, that's all fine. I haven't had much luck with it implementing entire features or doing anything at ~medium complexity or higher. I don't _want_ it to do that anyway. I want to do that stuff. That's the fun part.
I am concerned about its energy consumption too, and the hype is quite irritating as well. On both of those fronts, there's an opportunity for us to step back and consider what LLMs are actually good at, and use them where appropriate, instead of trying to infuse everything with AI.
I'm probably just getting old and grumpy. But yeah, it's a little depressing.
https://www.reddit.com/r/recruitinghell/comments/j1vm8j/gold...
You said it yourself, these are overwhelmingly people who've never built or maintained anything complex in their lives. If you're going to listen to what people on the Internet say, why not seek out people who can earn your respect?
I do not fear that some agents will pollute my repos with their PR. In opposite, I suppose that we will end at a point where for each question, task, or problem, one will find many (AI-coded) solutions, making it impossible to choose a right, solid, reliable one. I recently thought about having a database of tools per task so that a comparison would be possible. But the maintenance costs of something like this are enormous when including benchmarks, comparisons, etc. on different qualities.
But, I don't like hype or having things forced down my throat, and there's a lot of that going on.
Psychologically, the part that seems depressing is that everything just seems totally disposable now. It's hard to even see the point of learning the latest and greatest AI tools/models, because they'll be replaced in about 3 months, and it's hard to see the point in trying to build anything with, or without AI, given the deluge of AI slop it will be up against.
I like the idea of spending a bit of time to learn something, like how to use a shell, how to ride a bike, how to drive a car, how to program in C or C++, and use the skill for years or decades, if not a lifetime. AI seems to have taken that away now everything is brand new and disposable, and everyone is an amateur.
Meanwhile, some of us were over here, building embedded systems with C and C++. The big switch was from Green Hills or VxWorks to embedded Linux. The time scale was more "OS of the decade". There's hype and fads, and there's stuff that lasts.
I'm not opposed to new things, but I guess I want incremental improvement on the old thing, and more on the timescale of years than weeks.