So much more stuff and growing- what it is actually useful for ? Are we getting actually more done than with previous volumes or is it just all wasted energy?
I’m getting a lot more done. Hobby projects that languished for years are coming along great, at quality and depth I could never have found time for before.
Best code is the one that you have not written :) Because the goal is not the code , it is the things that code does, and if it can be done without code, its the best code. Also if you produce lots of code that does not do anything in reality, then its worst code.
And yes, we can rebut that with "time you enjoy wasting is not wasted" except of course some externalities, like boiling earths oceans.
If it's not your job, then just ignore the reports.
If it's actually critical, someone will put money on the table and then it's a business. And then it's about scheduling and resourcing - also should not burn anyone out.
Just because many people have false sense of entitlement as soon as they get a free offering, it does not mean anyone needs to accommodate them.
Just doing what others wish is not conscientous in itself! It _may_ be depdending on situation but it can be just pathological towards the self.
When it's psyhocologically hard to do things you imagine will dissapoint someone that's probably not concientousness. It's more like low self-esteem or codependency.
It's very hard for someone to tell these apart themselves. Hence when this topic pops out it's good idea to remind that being super-accomodating may in fact be a personality flaw - that can be healed if acknowledged.
There is very large spectrum between "trying not to dissapoint anyone" and doing what you know is the right thing.
Sounds like their problem, not something a SaaS product should dance around.
Yet they kind of did. I've limited participation in my libraries with GitHub's setting that nobody who made an account in the last 6 months can do anything in my repos (after some misguided hustler thought they're an easy target and posted an ad).lp
Time's marching forward though. Wonder what will happen after a few more months. We'll have bot spam accounts that are no longer as fresh.
A great majority of business applications do run on open source projects, and in turn, are affected by them if things go awry. It’s a prisoner’s dilemma in this case.
Basically the only library for reading jp2k data (complicated specs, ask your AI to one shot an implementation, mine said "it's 3000 lines of fiddly spec, too complicated"). Issues full of buffer-overflows. Recently unmaintained.
Used in tons of projects, now all possibly vulnerable.
It's starting to become a cliché to have people reply "I'm getting a lot more done", but without seeing any evidence of this incredible productivity gains, I'm starting to wonder if y'all are suffering from collective hallucination. If the accepted claims are of "100x productivity" (increasing by the day), and LLMs have gotten very good for the past ~year, for sake of argument, where are the 100 year improvements in the status quo of software?
If one claims such extraordinary figures of 100x increased productivity, a step forward never seen in the history of humanity in such short timespans, they must present extraordinary proof or be branded as a complete lunatic. I could have accepted people saying "I'm 20% more productive", which is an incredible achievement by itself, but not the 10x, 20x, 100x I keep hearing about. I think I've read 200x this week.
The analogy here would be : a kid who wants a toy but does not have money. So he keeps dreaming how he some day would get that toy and how he would play with it and how it would make him happy, but times goes by and he still does not have money to get that toy. Then suddenly along comes LLM and you have infinite money to buy you all the toys that you wanted, you get them, but you now don't have time to play with them. Because time is money and just like before you didn't had time to "buy" the toys, now that you have them you still have no time to play with them.
I've heard people use the same word, I was dubious but they did produce some stuff, yet I think that it ends up as an itch-project. You're satisfied you saw the thing emerge into existence but that's about it. No more drive after that. Maybe because LLM don't require you to have a real long term intense need for that thing.
This is exactly my experience. A month of excitement building something that I wouldn’t have had time to do myself, then something broke in the setup and my motivation didn’t extend to fixing it.
I’m only back at it four months later and I don’t really know what happened before, or why it’s working now, I’m just happy that I can scratch that itch again.
Hey, traditional hand coder fellow ... the times have past and the future is already a present. I never have been this productive before, and it's been ~20 years that I spent coding. System level programming. Few years back I would have said the bottleneck is not in spelling out the code so we wouldn't see that much AI impact but boy I was wrong. Writing code has never been this cheap, both in terms of time resources and $$$. Now I can iterate over the ideas I didn't have the capacity before, both intellectual and time-wise.
I think using AI often feels faster than it is because you put less thought and effort into the problem yourself.
Another possibility is that the people who experience these 100x productivity increases are honest, correct, and simply had abysmal productivity which has now been increased to near-average junior levels thanks to AI.
> I could have accepted people saying "I'm 20% more productive", which is an incredible achievement by itself, but not the 10x, 20x, 100x I keep hearing about. I think I've read 200x this week.
That’s a measure of lines of code, I suspect the parent is talking about what results those LOC create.
AI built me a 1.5k+ LOC react component which is probably a 15x increase on the file size I would have created, with negative impact on the project for those extra LOC.
The variance is extreme though. Thanks to Claude Code and Codex I've been able to make several non-trivial internal tools and libraries without writing much in terms of code, just some reviews here and there.
I spent a couple of days on those, and its would have taken me months to write manually I am sure, so in that regards it's close to 50x.
I've also had Claude track down some logic issue in a module I was unfamiliar with which had very large and complicated flows. Would have taken me many days, since I did not have a reproducible case, so had to go by logs and customer description alone. I spent 5 minutes writing a prompt and when I checked back, Claude had identified the issue. The fix I had to implement myself, but was fairly easy. So there Claude definitely was a 100x increase in productivity.
Then there are cases where they're much more modest, or where they might even be negative, when they think they're fixing stuff but actually are introducing more bugs.
You can accept what you like, but it's true. Our team and our business is incredibly more productive. The number of new valuable customer facing features, and the number of PRs (which represent REAL work, not taking a PR and splitting it into 200 PRs game) have all increased dramatically. We've shipped something like ~10x more PRs so far this year than all last year. And we've done that without increasing the number of bugs and outages.
A link to a YouTube video without context e.g. summary of findings, primary author/creators, and primary citations, methodology, and so on is a next to useless for making a point. For all we know you’re linking to a crackpot or an industry sock puppet and I don’t care to “watch” any of what can potentially be a dubious video or worse a malicious video. It is your job as the linker to convince me the video is worth even one iota of my time.
On the other hand recent papers highlight the validity of concern/suspicion:
> This systematic review demonstrates that the environmental footprint of artificial intelligence is a structural and increasingly consequential challenge, shaped by interdependent decisions across algorithms, software pipelines, hardware infrastructures, and deployment contexts. The synthesized evidence shows that energy consumption and carbon emissions associated with AI systems are highly variable, context-dependent, and often underestimated — Beyond Efficiency: A Systematic Review of Energy Consumption and Carbon Footprint Across the AI Lifecycle (published in “Sustainability” an international, peer-reviewed, open-access journal)
https://www.mdpi.com/2071-1050/18/3/1359
Nobody is concerned about the costs and environmental impact of data centers.
When someone in a discussion about the benefits of AI goes "did you think about the environment?!", it's always performative.
The real motivation is disliking AI itself or doubt about the government's ability to offset the labor market impact. Discussions that start with feigned concerns being raised are nearly always going to be unproductive.
I don’t dislike AI but really of mine are negatively affected by climate change and AI isn’t helping what is easily observed when Google and MS scrapped their CO2 reduction targets.
So every time I use AI I think about the necessity and usefulness of what I‘m doing with AI and if the use outweighs the costs.
Since the rise of AI the environmental impact doesn’t seem to matter anymore.
I guess because it’s the shiny new toy of the hackernews audience.
Privacy also lost importance given the fact that the same people who refused to give information like their phone number to companies like Google and Meta now upload their whole life to their AIs to asks what should the eat, hyperbolically speaking
You're not helping your case by questioning the usefulness of software produced with AI in the same comment section, or complaining about other people supposedly compromising their own privacy in overusing AI.
The reason it doesn't matter is because the environmental impact is moderate, and the benefit obviously tremendous.
The environmental impact is anything but moderate and the benefits are not obviously tremendous at all. I'm happy using Claude Code as much as the next guy, but saying that the impact has been "tremendous" is vastly overstating the actual results.
I disagree, with the projected doubling by 2030 we're looking at 3% of global electricity consumption or 3.4 EJ, less than 1% of final energy consumption.
That is moderate. Energy-intensive industry is around 130 EJ, and global final energy consumption > 450 EJ.
Existing documented applications of today's AI have the potential to decrease energy consumption by >13 EJ/year by 2035.
Now that was about operational energy consumption. Someone might bring up manufacturing and construction.
From what I could find the climate impact of those are estimated somewhere between 10-35% of the total climate impact of data centers, so relatively small compared to the operational energy consumption.
It is very hard to justify more than moderate environmental impact here, in my opinion.
For the benefits of AI, my personal results have been great, so I am quite optimistic. And objectively, I find it hard to ignore recent results in mathematics and security research.
"Global data centers consumed around 415 terawatt-hours (TWh) of electricity—about 1.5% of the world's total electricity—with AI acting as a primary accelerator for new power demand."
That is today where we already consume too much. If by 2030 AI's consumption doubles it gets worse.
While training large models draws major initial power, everyday AI usage (inference) now drives roughly 80% to 90% of cumulative AI energy
"Existing documented applications of today's AI have the potential to decrease energy consumption by >13 EJ/year by 2035."
Seems like AI helps slowing down the rise of energy consumption.
We are at a point where we want less CO2 not moderataly more.
In the end more is more.
If your doctor tells you to lose weight or you get sick it's not a success to gain weigth slower
Well, at least we could establish that the environmental impact is moderate rather than extreme.
And if the potential of >13 EJ/year is actually realized, it would seem like the net impact of the data centers is not just "moderately more CO2" but possibly "moderately less".
Most of my family are small business owners, so I've done a handful of Excel automations that they needed that generally take me a while to figure out. Landing pages and a few 3D designed prototypes that I used the Fusion 360 MCP server for
I play modded Starfield. There's been a clear increase in mods lately. Some of them are from self-proclaimed non-programmers who are using the LLM's to reverse engineer the game or other abandoned mods, and they've started to create new cool mods or they've fixed various engine limitations. Can confirm that these actually work and I can finally have my 1000+ modlist.
There was a huge exodus of existing programmers/modders ~two years ago, due to paid mods and what not. The gamers took over with their LLM tools.
Well, many of the saas I use continue to have problem meeting their SLA. And I’m on support just as often as always trying to get through to a human to file a bug that will never get fixed. “It’s in our roadmap”.. no it isn’t. Even with LLMs, product will focus on making new features to push their AI mission.
I have. In fact, some of my hand rolled stuff is actually _provably_ faster and more secure then even heavily battletested and widely used "industry standard" solutions. This is mainly due to them passing an exhaustive barrage of millions of lines of code of tests (literally, in fact I just did a pass over all my tests/ dirs and it's sitting at 6.3 million as of today) ranging from adversarial CVE probing attacks to fuzz tests. Ironically, my same testing suite has caught _numerous_ bugs in production stacks (openSSL/libuv) particularly, literal hard SIGSEGVs and the like.
On CVE probing, and I haven't really seen anyone describe/use it (or I may be oblivious), but the way you do it is you curate a list of CVEs for the class of software you're writing, say a web server. Then you take this list in chunks and hand them off to your agents to devise and implement adversarial technically analogous attacks against your codebase. If it's red, report and patch. Ironically (even with Fable 5) it's never complained/refused to do it.
At my company, we are using AI to clean up huge amounts of technical debt that would have just hung around otherwise, so yes. I'm not sure that your average user would notice, but we do without a doubt have a much better product now.
That’s like asking whether fuel consumption was productive or leisure as the number of cars on the road increased. It’s both! I don’t think you can separate one from the other in any reasonable way.
I have some big issues with this technology and the companies behind it, but I know of quite a few people personally who were not previously coders but have now been able to use LLMs to make their own custom software, solving real problems they had.
Are non-coders these days aware that they should use version control (and push their code to GitHub)? Or does their agent helpfully suggest setting up a GitHub repo?
One of the things I've done is create an entire fully functional GitHub alternative that does more of what I want and hosts all of my other projects, so yes I at least am getting considerably more done.
That's how it's sold, but have you heard about any major tech company that sends their worker home when they've achieved what they used to achieve pre-AI?
EDIT: Instead of simply down-voting, you're welcome to name examples that proves me wrong ;)
This is anecdotal, but I know that a lot of my coworkers and coasting and putting up one AI generated PR per day which they've hardly even self reviewed.
> In a good company that will come back to bite them next performance review.
In a good company that should be discussed in the next 1:1s so actual change can happen meanwhile. If it just waits for the end of year review, then it's not a good company.
To some extent we are getting more things done as well. In my company (mid-sized startup), they're making us push features every other day now as opposed to maybe 1-2 features per person per sprint. Back when I joined, things were a lot slower. Today, they expect freshers to push new features on day one.
