I agree. It really is not a difficult “skill” to learn. It took me probably 4 days to configure agents to break down requirements, write tests, write code, open PRs, review and merge PRs. Learned how to use skills, MCP, AGENTS.md. It is really not complicated. It’s just…writing well. Knowing how to decompose problems. Trying out different tools. I also learn new things every day but I sincerely do not think I would be X times more effective with these tools had I started a year ago.
Mix in exhaustion from previous hype cycles (NFTs?) and folks pushing the narrative that if you currently write any code manually, you’re obsolete and it’s hard to not want to push back negatively. Even if you find the tech interesting/useful.
It’s a tricky philosophy to put into practice. I have oscillated between this approach (“owning” the effort) and “owning” the outcome. I have found that taking ownership of the outcome leads to better results because I have a personal stake in the outcome and I tend to think through the problem more deeply, but I am almost always left feeling more stressed and “empty” when the work is finished. When I focus on doing the best I can and let go of the outcome, the end result is almost always subpar which leaves me feeling frustrated, because I know it could have been better had I taken on more responsibility.
Coaxed into dead-end architecture is the exact issue I have had when trying agentic coding. I find that I have the greatest success when I plan everything out and document the implementation plan as precisely as possible before handing it off to the agent. At which point, the hard part is already done. Generating the code was not really the bottleneck.
Using LLMs to generate documentation for the code that I write, explaining data sheets to me, and writing boilerplate code does save me a lot of time, though.
> I’m no longer an artisan enjoying the journey of creating
me the first time my boss forced me to unit test my code
...
The best thing you can do is listen to your gut and try to act as rationally as you can.
Talk with trusted mentors if you've got them. Don't listen to me and for the love of god don't listen to people on HN or reddit or Youtube or any other social media.
Nobody knows what they're talking about and they certainly don't know how it'll impact you.
If somebody is making you feel afraid, left behind/out, inferior -- they're trying to sell you shit. Don't listen to the bullies and con artists.
You're entitled to your opinion. If you think AI output is crap, it's crap. Don't be pressured to conform. This is supposed to be hackernews after all. There are plenty of companies using java 8 today. You won't be unhireable.
I appreciate your reply. My tone was a little dismissive; I'm currently deep deep in the trenches trying to unwind a tremendous amount of LLM slop in my team's codebase so I'm a little sensitive.
I use Claude every day. It is definitely impressive, but in my experience only marginally more impressive than ChatGPT was a few years ago. It hallucinates less and compiles more reliably, but still produces really poor designs. It really is an overconfident junior developer.
The real risk, and what I am seeing daily, is colleagues falling for the "if you aren't using Cursor you're going to be left behind" FUD. So they learn Cursor, discover that it's an easy way to close tickets without using your brain, and end up polluting the codebase with very questionable designs.
It's 60-80% as good as Stack Overflow copy-pasting programmers, sure, but those programmers were already providing questionable value.
It's nowhere near as good as someone actually building and maintaining systems. It's barely able to vomit out an MVP and it's almost never capable of making a meaningful change to that MVP.
If your experiences have been different that's fine, but in my day job I am spending more and more time just fixing crappy LLM code produced and merged by STAFF engineers. I really don't see that changing any time soon.
We use C for embedded products at work. My gut feeling is that Rust or Zig would require way too much time investment to learn and use properly, then you'd still have to deal with interop problems.
No. I use AI as a fast but stupid research assistant. It aggregates information to point me in the right direction but I don't trust it at face value. I tried copilot for the first time last week and found it useful for writing bash boilerplate but not much else.
Wake up to my kid scream whispering at my baby to stop kicking me in the throat, change diapers make coffee and eggs, read a couple headlines about how it's the worst time in history to be alive, make lunches clean up breakfast and leave for work late to attend the daily all company hour long standup.
In all seriousness, sans young baby the most productive time of my life has been fitting exercise/side project time in between 4:30-6am. I made some real gains during that time and plan to get back into that routine once sleep isn't so rare.
Funny enough I had an interview today with a dynamic programming whiteboard problem. I feel like if I hadn't been putting in my leetcode hours I would have totally bombed
I'm really curious, how do you factor in time to learn ("up skill")?
I'm a self taught dev with 2 young kids. I've always had a healthy approach to work, but now I'm feeling quite a lot of pressure to learn new things on my own time, whether to make sure I'm prepared for the interview circuit if I get laid off, or to patch my skills that are needed at work.
I'm starting to feel burnout creep in, getting an hour of study in the morning, taking care of family, and then working 8 hours.
We're a documentation-heavy org and having to open Confluence, find the right root page, drill down to where I need to be, and deal with ~1s page loads drives me nuts.