Builds a straw-man of the left only to tear it down.
Technology is neither good nor bag; nor is it neutral. If you can't think of any reasons people may be critical of AI, given the amount of layoffs, then you're not very imaginative or informed.
Good advice. Personally I'm waiting until it is worthwhile to run these models locally, then I'm going to pin a version and just use that.
I'm only 5 years into this career, and I'm going to work manually and absorb as much knowledge as possible while I'm still able to do it. Yes, that means manually doing shit-kicker work. If AI does get so good that I need to use it, as you say, then I'll be running it locally on a version I can master and build tooling for.
I'm Aussie. Please explain to me; why should I care whether Chinese SOEs or the US tech companies are winning? Neither have my best interests at heart.
This is a cool exercise, but I would hesitate to choose files over SQLite or another Dockerised relational database in production.
They are overoptimising for the simplest part of writing the application; the beginning. They've half-implemented an actual database, with none of the safety features. There are a lot of potential headaches that this article has avoided talking about; perhaps because they haven't experienced them yet.
What happens when you need to start expanding the scope of this feature? Joining users on profiles, or users on orgs?
Ask yourself: how many shops have seriously written an application backed by files and stuck with it over the long-run? The answer is likely very few. Therefore, this is likely doubling up the work required.
There is a reason people reach for a database first. I'd strongly encourage anyone to avoid doing stuff like this.
and then there is a decent amount of software that's mostly "one and done" and has immense performance constraints - games and anything that has to do with real-time. for game engines, a custom data format from the very start makes a lot of sense because your budget is usually less than 17ms and 8 threads on low-end hardware and 8.(3)ms across 16 threads on high-end. there, "smart data structures and dumb code beat dumb data structures and smart algorithms" couldn't be more true.
yet, for a generic app or server, just don't fuck your brains and go with SQLite
How to avoid skill atrophy? Easy. Limit your use of LLMs. Intentionally practice. It's what I do.
You're losing if you're handing your brain over to LLMs right now, because companies would prefer to hire someone with more up-to-date coding skills, even if they then force them to use LLMs. So the winning move is to resist using LLMs for as long as possible.
Stop fanboying the industry's attempted commodification of your work, and get back to the basics.
Man its really sad to see that this place seems to embrace LLMs with open arms and seems to have no care for the implicit costs and side costs of it.
I have no interest in SWE - I focus on other fields. But, LLMs are a complete disaster of a product, as the more you use them the less you are engaging your own brain to tap into the knowledge you have to get shit done and move fast. LLMs are a mirage and the fatal flaw of a human is laziness.
This lack of brain engagement is deadly. People dont realise how tough it is to get back once you've started to lose it. Its akin to the gym and muscles.
1. No, implementing well defined requirements were not commoditized a decade ago. You still have to come up with the design and proper (efficient,correct,...) solution that respects the requirements. it was and still is the skill set of a L4/L5 SWE.
2. If you think LLMs cannot help with navigating ambiguity and requirements, you are wrong. it might not be able to 100% crack it (due to not having all the necessary context), but still help a lot.
You realize you are arguing my point? We are in complete agreement about #1.
As far as #2, I came into a large project at my new at the time company last year one week before having to fly out to a customer site. I threw everything I could find about the project into NotebookLM and started asking it questions like I would ask the customer. Tools like Gong are pretty good to at summarizing calls. I agree with you on #2.
I am at a point now where I am the first technical person after sales closes a deal and I lead (larger) projects and do smaller projects myself. But I realize remotely, my coworkers from Latin America are just as good as I am now and cheaper.
I’m working on moving to a sales role when I see the time coming. It’s high touch and the last thing that can’t be taken over.
I would never have trusted any L4 or L5 SWE I met at AWS anywhere near one of my customers (ProServe). But they also wouldn’t let me put code into a repo that ran an AWS service. Fair is fair
If I remember correctly, the leveling guidelines were (oversimplifying).
An L4 should be able to handle a well defined story
An L5 should be able to handle a well defined Epic where the what is known bit not how
An L6 should be able to lead a more ambiguous longer term project made of multiple Epics.
I was saying it was not commoditized a decade ago, but i feel it's getting commoditized *now*. So you seem to be basically saying SWE is over and it's time to move on to something that is primarily based on human-human interaction?
Yes it has to be. LLMs are getting to the point they can do everything else. What they can’t do, cheaper non US labor can.
For context, the software developer market in the US is very bimodal, most developers are on the enterprise dev side (including most startups like YC companies). I’m referring to this side - not FAANG and equivalent
By commoditization back then, I knew there was nothing I could do on that side of the market that would let me make more than around $150K-$165K. My plan then was to get on the other side of the market in 2020 after my youngest graduated and out of enterprise dev.
“Commodization” now means too many people chasing too few job. In 2016, I could throw my resume up in the air and get three or four random enterprise dev job offers within less than a month - now not so much.
I discovered AWS belatedly later that year and my thesis was changed to I want to do #1 that you said above - customer focused, using AWS as a tool, and bringing a developer mindset to cloud implementations.
It just magically happened in June 2020 that both felt into my lap - cloud consulting full time opportunity at BigTech (no longer there thankfully).
Well an LLM only helps you code, coding is not a competitive skill in 2026. If your “work” can be commoditized by a next word predictor, it was going to be commoditized by someone willing to work for less than you make anyway
That's pretty elegant, compared to a lot of the solutions in this thread. Honestly, it sounds like the what I'll be recommending. Using a logging tool to output JSON events.
But what happens if you need to manually update a record?
I'm 32 and submitted a photo of myself for age verification on Instagram and Threads. Was promptly banned, with no resource.
I do look a little younger than 32, due to a healthy lifestyle and religious use of sunscreen but I have a beard and moustache. It's a little insane that I was instantly banned with no way to move forward.
Technology is neither good nor bag; nor is it neutral. If you can't think of any reasons people may be critical of AI, given the amount of layoffs, then you're not very imaginative or informed.