I see no difference there except speed at the cost of whatever little understanding may have been gained by the manual inspection between steps.
Personally I've found LLM's suck at multi-threaded applications. (Because I've been tempted by the ~agentic loop~ and been burned. Then I hand code the core logic and all is well).
Woe to the developer who tries to prompt their way through this.
But seriously, lots of apps are just glorified NextJS apps which have tons of training data. Something like rust would likely churn out nonsense that compiles eventually but isn't optimal.
Agreed with the caveat that I think if you know what you're doing and are very cognizant, LLM generated Rust is amazing. I feel like it's hard compilation requirements gives a guardrails for a LLM and if it compiles, you're pretty safe against memory issues.
x=ctrl-c("output error report")
eval(ctrl-v(x))
sleep(10)
user("Input...")
You're basically describing my work day. My job went from interesting, highly skilled work to mostly horrible brain rot over the past year.
It's depressing and I don't know a way out. Other then a complete career change, throwing away 30 years of experience and a matching salary.
I only have 10 years of experience, so I'm not trying to say that your lived experience is invalid, but personally I figure if this is the way the industry is heading then I may as well try to learn how to thrive within the new environment.
The current hype cycle might even represent a net global gain like some people argue. But it represents yet more externality driven exploitation. Remains to be seen what the new equilibrium will be given that now the population being exploited is not only close to the core of the world system but also already overburdened.
I do think it represents a mere acceleration of the previous trend that resulted since around 2005 in an explosion of average (not median) pay for software developers due to similar dynamics. If the system settles on a new level of pay that manages to convince enough people of enough skill to go along, it might just hum along and not implode. As for the rest of us, welcome to the growing permanent underclass and brace for the impact of the climate wars. We will be the fodder that will insulate the chosen ones under their air conditioned domes.
If you’re unhappy, make a change.
The real question isn't if things are going to change around our jobs, its are we going to be able to move fast enough to avoid starving in the streets?
But that's because I don't have any real familiarity with the systems involved and I don't expect that gaining such familiarity will benefit me. If I am working on a system or product I'm responsible for at my job, it should be a different situation.
But I think we should decouple mediocrity from laziness. I haven't seen any team invest in the mentorship required to develop juniors in years, for example.
It would make sense to develop juniors if most of their comp was a four year vest but that doesn't happen until later. And in your first year or two you're usually a net negative... This is even more true with AI.
Especially if you get a little burned out and can't bring yourself to contribute to a side project, but still want to do programming-ish things that get your brain moving
Maybe this «spearheading AI person» just sucks at AI related stuff, as clearly that approach is bananas, but they could still be a OK developer.
If working with LLMs effectively means accepting subpar results or be a reverse centaur, then I’d be glad not to be able to work with them.
I’ve never seen a good example where AI is a net positive to any development workflow. No one argues against compilers, build tools, IDEs, task runners, deploy and orchestration tools. Because they are great levers that lets you create more with less effort.
Where it shines is glueing systems together or building one-off automations that would take days, or weeks, to figure out. It’s for things you don’t have time to figure out or didn’t think were possible.
Why would it mean that? That's one way of using them, sure. Personally, my code is better as I have more time to think about the software design than before, and I'm less avoidant of refactoring in my personal projects.
> I’ve never seen a good example where AI is a net positive to any development workflow
Alright, does that mean you also believe it's impossible then that anyone out there is using AI in a "net positive" way for their development workflow? Or just that you've never seen it, but you're open to it existing?
This one. Only a sith deals in absolute.
I don’t mind experiments to try to find methodologies for those tools. And I believe there are instances where they’ve been successfully used. The issue I have is the kind of generic statements that they are good enough to replace currently established methodologies. Like using AI is a panacea.
> Personally, my code is better as I have more time to think about the software design than before, and I'm less avoidant of refactoring in my personal projects
That’s a bit what I’m talking about. Have you investigated how it has helped you? And if there are other, more economical way to get the same result? Your statement seems more ritualistic than logical.
No I haven't, but I'm happy to just freeform walk you through my thinking on it: I typically write (wrote?) software for two purposes: consulting/freelancing for others so building what others want, or for simplifying and making my own life easier and more enjoyable. "Stupid" stuff like Home Assistant for example, isn't really life-or-death, or Jellyfin for that matter, both things my family relies on now, but our daily life just gets easier all throughout the day when everything works in sync with what we're doing.
It used to be I had to make a decision what to spend time on, either I work on my professional stuff so we have enough money to survive (maybe more) and I get new challenges and all that, or I spend time improving and maintaining my home infrastructure, or whatever software I feel like I'd need to be better at doing my professional development.
I no longer am making that choice, I'm spending less time in front of the computer, yet the output and quality of my work remains the same, and the code and design when I look at it, even stuff I shipped 6 months ago, I'm still happy with how the code is, which for me I guess is the way I validate if what I produce is good enough.
Nowadays, my entire home-lab is configured with Nix and almost everything except my workstation and some random stuff, runs NixOS. Everything is hosted on a local Forgejo instance, which also has it's own (custom "written" of course) agent acting on issues and PRs, and I have my harness basically maintain my entire home lab at this point. Now I just open issues, have a conversation until everything is 100% clear, end up with a PR to review and merge if it looks good, and I can do this while juggling other things.
I agree with you that there are tons of people who are selling LLMs as a panacea to lots of things, and there is so much over-hype in the industry and ecosystem, I also feel like every "new thing" kind of comes with this type of almost scamming, which sucks, and makes it hard to discern from real positive opinions vs just regurgitated opinions someone read somewhere. I'm not sure what the answer to that is, except perhaps as what you say, only a sith deals in absolutes.
What are the exact "currently established methodologies" you're talking about that cannot be replaced by LLMs + a harness today, just as some examples? You're probably right that those exists, but I'm curious to hear what you think would be the most difficult to replace today.
I was explaining [0] under another post that programming is mostly translation works. You take a specs and you formalize it using code, like going from sketch to a proper engineering drawing. Software design is more creative, where you take a problem and then comes up with a solution (creating the specs). Software Engineering is ensuring that those two are done well enough while consuming the least resources.
So a program is always a formal system. It's also static. It will be executed by a computer which will actually have a tangible effect in the real world. That effect is what's valuable. The program is the seed which let us control that effect. Aka it's the map that let us plan the journey, but it's not the territory that we will have to travel in.
The issue I keep pointing in most of my comment is thinking that the map is the territory. That the novel are the words and not the story so we need more words. Or that the code is more important than the user' workflows, se we are adding more buggy code, while not ensuring that the workflows are undisturbed.
> Nowadays, my entire home-lab is configured with Nix and almost everything except my workstation and some random stuff, runs NixOS. Everything is hosted on a local Forgejo instance, which also has it's own (custom "written" of course) agent acting on issues and PRs, and I have my harness basically maintain my entire home lab at this point.
It's also highlighted here where you focus more on the process than the output here. The goal is to have a working homelab. NixOS managing it is only the process (accidental complexity). If it's where truly about the goal and not NixOS and using AI, by this point, adding new nodes (software, devices,...) should be as easy as selecting it and adding it to the current system, like a strategy game.
You can see that philosophy in OpenBSD, where the focus is to have a working OS, not to work on developing an OS. A lot of software are done and it's mostly just bug fixing every once in a while. You can also see the same attitude in industrial engineering where you develop a solution and then use it for years. You don't spend all your time tweaking it and thus disturbing the production flow.
So yes, when I see a LLM methodology, it's mostly about the work itself, not the output of the work. There is no definition of done or even the idea of having one. It's work for the purpose of working.
Both of these can be quite invisible. But the benefit is there.
Uhm ... I've heard quite alot arguing against IDEs. And I feel IDEs are too much of a lock in.
Over the past year maybe 1.5x to 2.0x for me. As in: I can work on two projects at the same time with reduced amount of context switch. But that's it for me.
Maybe I don't have the brains for 1000x terminal agent coding, but 2 parallel projects seems like my saturation point.
But most who keep on going about their 10x productivity gain are indistinguishable from that one obnoxious guy at a party who won't shut up about his Ayahuasca retreat last spring. And they think they're Erdős.
AI is like having a junior dev with an adderall addiction and an encyclopedic knowledge of coding syntax at your beck and call.
Many many people have jobs where their contribution is granting access to deliberately undocumented things, like knowing where the config files are and some such. They hate the idea of AI. For my non IT friends its great for diagnosing wifi issues. It's also great for competent network engineers. It's not great for those who gain a salary due to having memorized some actions or settings that they don't even understand much. Note that this group has also already resisted traditional script automation, just like US dock workers who resist automation.
Workplaces are where many of us spend a large percentage of our waking lives. So, it is "normal," unfortunately. This is why HR language and norms have broken containment into the non-work world. (Whether that's a good thing is another question.)
There is not one single discourse norm to rule them all and calling out every little thing as too offensive is just annoying. Yeah, yeah there are no midwits, everyone is a unique little genius flower, yeah.
More productive? Sure, to an extent.
Being merely more productive is a tame claim for what some people unashamedly post here
Karpathy, Carmack, Terence Tao, Simon Willison etc. are all smart people and manage to use AI effectively and productively because it doesn't hurt their ego.
You can see my comment history.