frje1400

> It seems like the idea of the macro, and more generally of expressing code succinctly, is the closest to obsolete in my memory?

That seems true in a world where we completely stop looking at code. Right now my reality is giant verbose PRs written by agents in Java, and it sucks to review.

You're welcome. I now feel inspired to try to change your mind, if you don't mind.

I would argue that "concepts" actually are more important than ever. Let's take my structured concurrency example. It doesn't matter here exactly what is, but if it ends up being as important as I think it will be, I likely want to write most concurrent code that way going forward.

However, it will likely be years until agents go to it unless deliberately steered in that direction. And if I want to make agents write it, I need to review it, and if I'm going to review, I need to understand it.

I think this is why I'm not pessimistic about the profession, it still feels like what I'm doing and learning matters.

Yes, as an example structured concurrency in Java (final release in Java 28 perhaps). I think that could totally change how we write concurrent code in that language.

I just upgraded a less important service to Java 27, a few days after its release (several nice features). It's cool how easy it is to upgrade nowadays.

That an agent writes most of the code doesn't mean anything to me here.

My examples are Java because that is the main language where I work.

Same. Claude consistently ignores my instructions related to comments, and continues to be extremely verbose, often irrelevant, or too specific in terms of the current task. When called out on it, it says sorry.

I've resorted to having a final pass where comments are evaluated separately. This is much more successful than trying to get it to write good comments while writing the code.

Data infrastructure in the real world, for non-trivial systems, moves slowly. Migrations are costly and risky. If you need to optimize query performance, you are likely working on one of those non-trivial systems. We have some MongoDB clusters at work (one in my team). Would we have picked it today? Maybe not, because the mindshare isn't there. Does it work fine right now though? Yes, definitely, we have no issues really (the suck in that system is elsewhere).

There's a reason why Orbstack can charge money: it just works, and podman doesn't (on macos).

It is likely still the best environment to read and debug Java code, which you still need in addition to whatever agentic tooling you have. Advanced editing features have clearly lost value though. Is it still worth the money? I don't pay for it myself so I don't know, but probably for Java at least. But obviously it doesn't make sense to pay for it if you just use it as an occasional text editor.

Taking wider responsibility, doing both dev and ops. Learning more about k8s since my company uses it. Trying to think more about testing and verification in general because I think that's what the bottleneck will be.

Obviously lots and lots of companies. Do you think a mature company just migrates to a different database unless it is absolutely necessary? That's a multi year project. I'm at a smaller company (around a 100 devs) and we have easily a dozen different production instances, some small and some larger with many replicas, etc.

New projects get MySQL too because we know it and it works.

So in this solution, you run the backend on a single node that reads/writes from an SQLite file, and that is the entire system?

> If your writes are fast, doing them serially does not cause anyone to wait.

Why impose such a limitation on your system when you don't have to by using some other database actually designed for multi user systems (Postgres, MySQL, etc)?

> And if you are starting a new project, why would you pick Java over Kotlin?

Because in 5-10 years you'll have a Java project that people can still maintain as if it's any other Java project. If you pick Kotlin, that might at that point no longer be a popular language in whatever niche you are in. What used to be the cool Kotlin project is now seen as a burden. See: Groovy, Clojure, Scala. Of course, I recognize that not all projects work on these kinds of timelines, but many do, including most things that I work on.

I think that you are describing an ideal scenario that does not reflect what I see in reality. In the "enterprise applications" that I work on, long functions evolve poorly. Meaning, even if a long function follows the ideal of "single thread, step by step" when it's first written, when devs add new code, they will typically add their next 5 lintes to the same function because it's already there. Then after 5 years you have a monster.

> You mention "var", why would we ever want in Java to hold a variable that you can't read immediately what is the type?

var items = new HashMap();

Instead of

HashMap items = new HashMap();

That's the point of var. It reduces noise a lot in some situations.

Orbstack is worth every penny. It's simply amazingly solid compared to Podman on macOS (a year ago at least, I don't know if Podman has improved). We migrated 100+ devs to Orbstack and it was like a collective sigh of relief that we finally had something that actually worked.

great, well-grounded, discussion. highly recommended.

In software? I don't see how high stakes infrastructure changes can be done by current AI technologies. It's different from programming in that you might only get one chance to do the things that you need to do in the right order with the right configuration for your environment. You might use AI for initial brain storming, but then you need to dig in to the official documentation for your specific version of e.g. a database, and then validate each individual step, and so on.

> On the consumer side, almost certainly not. Nvidia is a HUGE brand name, it doesn't matter how good and cheap AMD makes their consumer GPUs, people will buy Nvidia GPUs for the brand and prebuilts will stick with Nvidia for the name.

I think that AMD could do it, but they choose not to. If you look at their most recent lineup of cards (various SKUs of 9070 and 9060), they are not so much better than Nvidia at each price point that they are a must buy. They even released an outright bad card a few weeks ago (9060 8 GB). I assume that the rationale is that even if they could somehow dominate the gamer market, that is peanuts compared to the potential in AI.

Perhaps "frameworks don't compose" and "frameworks shape how you code" are actually good features, not a problem. Where are frameworks the most popular? Probably for web services (e.g. Spring Boot for Java). You don't need them to compose because you will only have one.

That you are forced (or at least strongly nudged) to code in a certain way is good because that means that all your web services are at least superificially familiar to all developers at the organization. That special service composed from many libraries? Impossible to work on without significant time investment.

I suppose though that if you are in a domain where you actually would want a library, but all that's on offer are frameworks, and you actually need to compose them, then yes, that seems problematic.

You've described my job, but I've found some excitement in the "distributed systems" part of it. It's not trivial to make the right design decisions to make a microservices architecture run well. If it was trivial, we wouldn't have so many problems at work.

That said, I do kind of miss the programming itself being interesting. I did more difficult programming at university.

LLM output can't really be trusted so I need to "proof read" it and convince myself that it is correct. In the language I use every day and have a high degree of fluency, it's faster for me to simply write what's in my head than to proof read unknown code. So how can LLMs make me more productive in actual programming?

I use an LLM to generate ideas, to rubber duck, to get a lead on unknowns, and to generate boilerplate occasionally. So I do everything except replace the coding part because that's what requires the most precision, and LLMs are bad at precision. And yet, people claim massive productivity gains in specifically coding. What am I missing?

I'm at a mid sized SaaS company in the Nordics (European). No layoffs, but hiring has slowed down and we no longer actively try to recruit junior devs. We used to have lots of active job ads, now they're reduced to only the most in-demand roles. The company is profitable and we have big important projects going on so not too worried.

Here's a thought experiment: think about what you did at work in the last few weeks, but instead of you doing it, someone that doesn't know programming is given those tasks instead. They have state of the art LLMs to help them. How would they do?

In my particular case, they might make some progress on the React component I worked on. I did use ChatGPT myself to get some help with CSS (the part of my current stack that I'm least proficient in). They would make zero progress on our big Java service because it's simply too custom for an LLM to be of much help.

For the database stuff that I also did, it was mainly about reading official docs and testing assumptions and behaviour based on those, something that you would think an LLM would be great at, but the answers I got when I tried weren't really helpful. The issues were too specific to certain versions of dependencies and in some cases, the docs' recommendations were questionable. I then had to convince other devs that my findings were correct and that we could go ahead with the, potentially risky, change.

So no, I don't think programming is dead. Not yet anyway. Who knows what the future might bring.

I started a Bachelor's in CS in 2019, graduated in 2022 at age 38, and got a dev job that I really enjoy. I was one of the older students (but not the oldest!) and it felt like half the class was older than your typical university student.

I had only had fairly low skilled jobs (and lots of unemployment) earlier in life. I even dropped out of college when I was younger, just like you. I definitely graduated at just the right time, but I think that it can be done, and it's not as weird anymore to go back to school when you're older.

I was extremely motivated because I felt like it was my last shot, and I knew that I really enjoyed programming after doing a couple of MOOCs and such.

I think that one factor is that staying on old tech is a risky career move both for the individual and the business. At work we have an Angular (the old one) app and while many new devs pick up some React, they definitely don't play around with ancient Angular versions for fun. So now we're stuck with a pretty big app using tech no one is interested in anymore.

That your gamble could be competely wrong is the main risk. What if the next generation AI doesn't change things much and is just a minor incremental improvement over the current tech, and it takes 3 years to get there?

It reminds me of the peak of self driving car hype bubble 5 (?) years ago. If someone back then had asked if becoming a truck driver was a good idea, ppl like you would have said no because their job would be gone soon. Instead we have more need for truck drivers than ever probably due to all the packages order online. Sure, could a revolutionary self driving truck be released tomorrow that makes some high percentage of all truck drivers lose their job? Sure, I guess, but my bet is that it's not happening.

I look at the generative AI thing the same way. Could a product theoretically be released that makes my job as a dev obsolete over night? Yes, absolutely, but it seems unlikely due how messy the real world is. Other people will make a different call.

I find it amazing for turning data into markdown tables (which are tedious to write by hand), for documentation.

Because even if don't get more money you get to do more fun work with more autonomy if you are good at what you do.

What's the display quality on these 10+ year old laptops? Looking at a low res blurry display all day can't be fun even if the performance is good enough.

I'm in the EU as well and while I'm quite junior, I felt like I had lots of options during my recent job search. One company gave me a practical exercise (using Spring Boot) and since I'm not familiar with that framework there was simply no way for me to complete it in a reasonable amount of time (we didn't use Spring in the CS program at uni). I had to withdraw my application.

I can't preemptively learn every framework that someone might ask you to use in these practical assignments, but I still think that I'm a fairly strong candidate (let's say top 10% of my graduating class).

I ended up at a company that asked more generic (but harder) questions that I could actually answer.