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One thing I find really funny is when AI enthusiasts make claims about agents and their own productivity its always entirely anecdotally based on their own subj
by llmslave2 9mo ago
One thing I find really funny is when AI enthusiasts make claims about agents and their own productivity its always entirely anecdotally based on their own subjective experience, but when others make claims to the contrary suddenly there is some overwhelming burden of proof that has to be reached in order to make any sort of claims regarding the capabilities of AI workflows. So which is it?
- travisjungroth 9mo ago> anecdotally based on their own subjective experience So the “subjective” part counts against them. It’s better to make things objective. At least they should be reproducible examples. When it comes to the “anecdotally” part, that doesn’t matter. Anecdotes are sufficient for demonstrating capabilities. If you can get a race car around a track in three minutes and it takes me four minutes, that’s a three minute race car.
- llmslave2 9mo agoAnecdotal: (of an account) not necessarily true or reliable, because based on personal accounts rather than facts or research. If you say you drove a 3 minute lap but you didn't time it, that's an anecdote (and is what I mean). If you measured it, that would be a fact.
- ozim 9mo agoI think from your top post you also miss “representative”. If you measure something and amount is N=1 it might be a fact but still a fact true for a single person. I often don’t need a sample size of 1000 to consider something worth of my time but if it is sample N=1 by a random person on the internet I am going to doubt that. If I see 1000 people claiming it makes them more productive I am going to check. If it is going to be done by 5 people who I follow and expect they know tech quite well I am going to check as well.
- llmslave2 9mo agoChecking is good, you should probably check. Every person I respect as a great programmer thinks agentic workflows are a joke, and almost every programmer I hold in low regard thinks they're the greatest things ever, so while I still check, I'm naturally quite skeptical.
- rjh29 9mo agoDoesn't help that many people use AI to assist with autocompleting boilerplate crap or simple refactors, where it works well, or even the occasional small feature. But this is conflated with people who think you can just tell an AI to build an entire app and it'll go off and do it by itself in a giant feedback loop and it'll be perfect.
- ozim 9mo agoThere are already people I follow who are startup owners and developers themselves saying they are not hiring “respectable developers” who are bashing agentic coding, they much rather hire junior who is starry eyed to work with agents. Because they see the value as they are running companies.
- hackable_sand 9mo agoIn this case it's more like someone simulated a 3-minute lap and tried to pass it off as a real car with real friction.
- tshaddox 9mo agoThe term "anecdotal evidence" is used as a criticism of evidence that is not gathered in a scientific manner. The criticism does not imply that a single sample (a car making a lap in 3 minutes) cannot be used as valid evidence of a claim (the car is capable of making a lap in 3 minutes).
- jimbo808 9mo agoI have never once seen extraordinary claims of AI wins accompanied by code and prompts.
- Ianjit 9mo agoStudies have shown that software engineers are very bad at judging their own productivity. When a software engineer feels more productive the inverse is just as likely to be true. Thats why anecdotal data can't be trusted.
- colechristensen 9mo agoOn one hand "this is my experience, if you're trying to tell me otherwise I need extraordinary proof" is rampant on all sides. On the other hand one group is saying they've personally experienced a thing working, the other group says that thing is impossible... well it seems to the people who have experienced a thing that the problem is with the skeptic and not the thing.
- llmslave2 9mo agoSomeone who swears they have seen ghosts are obviously gonna have a problem with people saying ghosts don't exist. Doesn't mean ghosts exist.
- colechristensen 9mo agoOk, but if you're saying I've had delusions LLMs being helpful either I need serious psychiatric care or we need to revisit the premise because we're talking about a tool being useful not the existence of supernatural beings.
- llmslave2 9mo agoNobody is saying LLM's can never be helpful, it's skepticism towards certain claims made around agentic workflows re. programming, such as claims of massively increased productivity or the idea that agents will replace most if not all programmers.
- b00ty4breakfast 9mo agoI think the point is that a subjective experience, without accompanying data, is useless for making any factual claims wrt both ghosts and reported productivity-boosts from LLM usage. Getting photos of ghosts is one thing, but productivity increases are omething that we should be able to quantify at some level to demonstrate the efficacy of these tools. That's a silly thing to request from random people in the comments of an HN thread though ha
- intended 9mo ago
- bdangubic 9mo agoWhich is it is clear - the enthusiast have spent countless hours learning/configuring/adjusting, figuring out limitations, guarding against issue etc etc etc and now do 50 to 100 PRs per week like Boris Others … need to roll up the sleeves and catch up
- burnte 9mo agoOr the tool makers could just make better tools. I'm in that camp, I say make the tool adapt to me. Computers are here to help humans, not the reverse.
- bdangubic 9mo agoso when you get a new computer you just use it, as-is, just like out of the box that’s your computer experience? you don’t install any programs, connect printer, nothing eh? too funny reading “tool should adapt to me” and there are roughly 8.3 billion “me” around - can’t even put together what that means honestly
- paodealho 9mo agoThere isn't anything clear until someone manages to publish measurable and reproducible results for these tools while working on real world use cases. Until then it's just people pulling the lever on a black box.
- nfw2 9mo ago[flagged]
- deleted 9mo ago[deleted]
- llmslave2 9mo ago[flagged]
- nfw2 9mo agopretending the only way anybody comes to a conclusion about anything is by reading peer-journals is an absurdly myopic view of epistemological practices in the real world
- llmslave2 9mo agoNobody is pretending that's the case...
- nfw2 9mo agoyour argument was that it's laughable on its face that anyone should be more skeptical of one claim vs another a priori
- llmslave2 9mo agoNo, it's that it's hypocritical to make a bunch of unfounded claims and then whine that someone who is conducting actual research and trying to be objective isn't doing it well enough or whatever.
- nfw2 9mo agoTo say that anyone who says they are more productive with ai is making an unfounded claim is evidence that you believe you that the only path to knowledge is formal research, which you claimed to not believe.
- palmotea 9mo ago> One thing I find really funny is when AI enthusiasts make claims about agents and their own productivity its always entirely anecdotally based on their own subjective experience, but when others make claims to the contrary suddenly there is some overwhelming burden of proof that has to be reached in order to make any sort of claims regarding the capabilities of AI workflows. So which is it? Really? It's little more than "I am right and you are wrong."
- AstroBen 9mo agoIt's an impossible thing to disprove. Anything you say can be countered by their "secret workflow" they've figured out. If you're not seeing a huge speedup well you're just using it wrong! The burden of proof is 100% on anyone claiming the productivity gains
- dude250711 9mo agoAh, the "then you are doing it wrong" defence. Also, you have to learn it right now, because otherwise it will be too late and you will be outdated, even though it is improving very fast allegedly.
- llmslave2 9mo agoPeople say it takes at least 6 months to learn how to use LLM's effectively, while at the same time the field is rapidly changing so fast, while at the same time Agents were useless until Opus 4.5. Which is it lol.
- wakawaka28 9mo agoI used it with practically zero preparation. If you've got a clue then it's fairly obvious what you need to do. You could focus on meta stuff like finding out what it is good or bad at, but that can be done along the way.
- jimbo808 9mo agoThat one's my favorite. You can't defend against it, it just shuts down the conversation. Odds are, you aren't doing it wrong. These people are usually suffering from Dunning Kruger at best, or they're paid shills/bots at worst.
- neal_jones 9mo agoBest part of being dumb is thinking you’re smart. Best part of being smart is knowing you’re smart. Just don’t be in the iq range where you know you’re dumb.
- nfw2 9mo agoThe author is not claiming that ai agents don't make him more productive. "I use LLM-generated code extensively in my role as CEO of Carrington Labs, a provider of predictive-analytics risk models for lenders."
- jimbo808 9mo agoThis is not always the case, but I get the impression that many of them are paid shills, astroturf accounts, bots, etc. Including on HN. Big AI is running on an absurd amount of capital and they're definitely using that capital to keep the hype cycle going as long as possible while they figure out how to turn a profit (or find an exit, if you're cynical - which I am).
- thierrydamiba 9mo agoThat’s a bit of a reductive view. For example, even the people with the most negative view on AI don’t let candidates use AI during interviews. You can disagree on the effectiveness of the tools but this fact alone suggests that they are quite useful, no?
- zeroonetwothree 9mo agoThere is a difference between being useful for sandboxed toy problems and being useful in production.
- kop316 9mo agoNot really. I'd rather find out very quickly that someone doesn't know a domain space rather than having to wade through plausible looking but bad answers to figure out the exact same thing.
- viking123 9mo agoAt this point it's foolish to assume otherwise. Applies to also places like reddit and X, there are intelligence services and companies with armies of bot accounts. Modern LLM makes it so easy to create content that looks real enough. Manufacturing consent is very easy now.
- felipeerias 9mo agoClaims based on personal experience working on real world problems are likelier to be true. It’s reasonable to accept that AI tools work well for some people and not for others. There are many ways to integrate these tools and their capabilities vary wildly depending on the kind of task and project.
- viraptor 9mo agoThere are different types of contrary claims though, which may be an issue here. One example: "agents are not doing well with code in languages/frameworks which have many recent large and incompatible changes like SwiftUI" - me: that's a valid issue that can be slightly controlled for with project setup, but still largely unsolved, we could discuss the details. Another example: "coding agents can't think and just hallucinate code" - me: lol, my shipped production code doesn't care, bring some real examples of how you use agents if they don't work for you. There's a lot of the second type on HN.
- alfalfasprout 9mo agoYeah but there's also a lot of "lol, my shipped production code doesn't care" type comments with zero info about the type of code you're talking about, the scale, and longer term effects on quality, maintainability, and lack of expertise that using agentic tools can have. That's also far from helpful or particularly meaningful.
- viraptor 9mo agoThere's a lot of "here's how agents work for me" content out there already. From popular examples from simonw and longer videos from Theo, to thousands of posts and comments from random engineers. There's really not much that's worth adding anymore. (Unless you discover something actually new) It works for use cases which many have already described.
- shimman 9mo agoUsing two randos that are basically social media personalities as SMEs is just a damning statement about the current trends of programming.
- viraptor 9mo agoThe area is still relatively fresh. Those two media personalities do actual work though and provide a summary for today's state. You can wait for an academic research on what happened 6 months ago or a consulting industry keynote/advertisement about what they implemented a year ago... but I'm not sure you'll be better informed.
- order-matters 9mo agothe people having a good experience with it want the people who arent to share how they are using it so they can tell them how they are doing it wrong. honestly though idc about coding with it, i rarely get to leave excel for my work anyway. the fact that I can OCR anything in about a minute is a game changer though
- citizenpaul 9mo agoIts really a high level bikeshed. Obviously we are all still using and experimenting with LLM's. However there is a huge gap of experiences and total usefulness depending on the exact task. The majority of HN's still reach for LLM's pretty regularly even if they fail horribly frequently. Thats really the pit the tech is stuck in. Sometimes it oneshots your answer perfectly, or pair programs with you perfectly for one task, or notices a bug you didn't. Sometimes it wastes hours of your time for various subtle reasons. Sometimes it adamantly insists 2 + 2 = 55
- nfw2 9mo agoLatest reasoning models don't claim 2 + 2 = 55, and it's hard to find them making an sort of obviously false claims, or not admitting to being mistaken if you point out that they are
- taormina 9mo agoI can’t go a full a full conversation without obviously false claims. They will insist you are correct and that your correction is completely correct despite that also being wrong.
- nfw2 9mo agoIronically the start of this thread was bemoaning the use of anecdotal evidence
- citizenpaul 9mo agoAlso that I specifically mentioned bikeshedding yet the reply bikesheds my simple example. While ignoring the big picture that LLM's still regularly generate blatantly and easily noticed false information as answers.
- citizenpaul 9mo agoIt was clearly a simplified example, like I said endless bikeshed. Here is a real one. I was using the much lauded new Gemini 3? last week and wanted it to do something a slightly specific way for reasons. I told it specifically and added it to the instructions. DO NOT USE FUNCTION ABC. It immediately used FUNCTION ABC. I asked it to read back its instructions to me. It confirmed what I put there. So I asked it again to change it to another function. It told me that FUNCTION ABC was not in the code, even though it was clearly right there in the code. I did a bit more prodding and it adamantly insisted that the code it generated did not exist, again and again and again. Yes I tried reversing to USE FUNCTION XYZ. Still wanted to use ABC
- deadbabe 9mo agoThis is why I can’t wait for the costs of LLMs to shoot up. Nothing tells you more about how people really feel about AI asssitants than how much they are willing to pay for them. These AI are useful but I would not pay much more than what they are priced at today.
- keeda 9mo agoActually, quite the opposite. It seems any positive comment about AI coding gets at least one response along the lines of "Oh yeah, show me proof" or "Where is the deluge of vibe-coded apps?" For my part, I point out there are a significant number of studies showing clear productivity boosts in coding, but those threads typically devolve to "How can they prove anything when we don't even know how to measure developer productivity?" (The better studies address this question and tackle it well-designed statistical methods such as randomly controlled trials.) Also, there are some pretty large Github repos out there that are mostly vibe-coded. Like, Steve Yegge got to something like 350 thousand LoC in 6 weeks on Beads. I've not looked at it closely, but the commit history is there for anyone to see: https://github.com/steveyegge/beads/commits/main/ https://github.com/steveyegge/beads/commits/main/
- reppap 9mo agoThat seems like a lot more code than a tool like that should require.
- keeda 9mo agoIt does, but I have no mental model of what would be required to efficiently coordinate a bunch of independently operating agents, so it's hard to make a judgement. Also about half of it seems to be tests. It even has performance benchmarks, which are always an distant afterthought for anything other than infrastructure code in the hottest of loops! https://github.com/steveyegge/beads/blob/main/BENCHMARKS.md https://github.com/steveyegge/beads/blob/main/BENCHMARKS.md This is one of the defining characteristics of vibe-coded projects: Extensive tests. That's what keeps the LLMs honest. I had commented previously (https://news.ycombinator.com/item?id=45729826 https://news.ycombinator.com/item?id=45729826) that the logical conclusion of AI coding will look very weird to us and I guess this is one glimpse of it.
- llmslave2 9mo agomore code = better software
- 9mo ago
- alfalfasprout 9mo agoTBH a lot of this is subjective. Including productivity. My other gripe too is productivity is only one aspect of software engineering. You also need to look at tech debt introduced and other aspects of quality. Productivity also takes many forms so it's not super easy to quantify. Finally... software engineers are far from being created equal. VERY big difference in what someone doing CRUD apps for a small web dev shop does vs. eg; an infra engineer in big tech.
- CuriouslyC 9mo agoPeople working in languages/libraries/codebases where LLMs aren't good is a thing. That doesn't mean they aren't good tools, or that those things won't be conquered by AI in short order. I try to assume people who are trashing AI are just working in systems like that, rather than being bad at using AI, or worse, shit-talking the tech without really trying to get value out of it because they're ethically opposed to it. A lot of strongly anti-AI people are really angry human beings (I suppose that holds for vehemently anti-<anything> people), which doesn't really help the case, it just comes off as old man shaking fist at clouds, except too young. The whole "microslop" thing came off as classless and bitter.
- twelvedogs 9mo agothe microslop thing is largely just a backlash at ms jamming ai into every possible crevice of every program and service they offer with no real plan or goals other than "do more ai"
- giancarlostoro 9mo agoLast time I ran into this it was a difference of how the person used the AI, they weren't even using the agents, they were complaining that the AI didn't do everything in one shot in the browser. You have to figure out how people are using the models, because everyone was using AI in browser in the beginning, and a lot of people are still using it that way. Those of us praising the agents are using things like Claude Code. There is a night and day difference in how you use it.
- safety1st 9mo agoI think it's a complex discussion because there's a whole bundle of new capabilities, the largest one arguably being that you can build a conversational interface to any piece of software. There's tons of pressure to express this in terms of productivity, financial and business benefits, but like with a coding agent, the main win for me is reduction of cognitive load, not an obvious "now the work gets done 50% faster so corporate can cut half the dev team." I can talk through a possible code change with it which is just a natural, easy and human way to work, our brains evolved to talk and figure things out in a conversation. The jury is out on how much this actually speeds things up or translates into a cost savings. But it reduces cognitive load. We're still stuck in a mindset where we pretend knowledge workers are factory workers and they can sit there for 8 hours producing consistently with their brain turned off. "A couple hours a day of serious focus at best" is closer to the reality, so a LLM can turn the other half of the day into something more useful maybe? There is also the problem that any LLM provider can and absolutely will enshittify the LLM overnight if they think it's in their best interest (feels like OpenAI has already done this). My extremely casual observations on whatever research I've seen talked about has suggested that maybe with high quality AI tools you can get work done 10-20% faster? But you don't have to think quite as hard, which is where I feel the real benefit is.
- heavyset_go 9mo agoNow that the "our new/next model is so good that it's sentient and dangerous" AGI hype has died down, the new hype goalpost is "our new/next model is so good it will replace your employees and do their jobs for you". Within that motte and bailey is, "well my AI workflow makes me a 100x developer, but my workflow goes to a different school in a different town and you don't know her". There's value there, I use local and hosted LLMs myself, but I think there's an element of mania at play when it comes to self-evaluation of productivity and efficacy.
- BatteryMountain 9mo agoSome fuel for the fire: the last two months mine has become way better, one-shotting tasks frequently. I do spend a lot of time in planning mode to flesh out proper plans. I don't know what others are doing that they are so sceptical, but from my perspective, once I figured it out, it really is a massive productivity boost with minimal quality issues. I work on a brownfield project with about 1M LoC, fairly messy, mostly C# (so strong typing & strict compiler is a massive boon). My work flow: Planning mode (iterations), execute plan, audit changes & prove to me the code is correct, debug runs + log ingestion to further prove it, human test, human review, commit, deploy. Iterate a couple of times if needed. I typically do around three of these in parallel to not overload my brain. I have done 6 in the past but then it hits me really hard (context switch whiplash) and I start making mistakes and missing things the tool does wrong. To the ones saying it is not working well for them, why don't you show and tell? I cannot believe our experiences are so fundamentally different, I don't have some secret sauce but it did take a couple of months to figure out how to best manipulate the tool to get what I want out of it. Maybe these people just need to open their minds and let go of the arrogance & resistance to new tools.
- 9rx 9mo ago> why don't you show and tell? How do you suggest? A a high level, the biggest problem is the high latency and context switches. It is easy enough to get the AI to do one thing well. But because it takes so long, the only way to derive any real benefit is to have many agents doing many things at the same time. I have not yet figured out how to effectively switch my attention between them. But I wouldn't have any idea how to turn that into a show and tell.
- hdjrudni 9mo agoI don't know how ya'all are letting the AIs run off with these long tasks at all. The couple times I even tried that, the AI produced something that looked OK at first and kinda sorta ran but it quickly became a spaghetti I didn't understand. You have to keep such a short leash on it and carefully review every single line of code and understand thoroughly everything that it did. Why would I want to let that run for hours and then spend hours more debugging it or cleaning it up? I use AI for small tasks or to finish my half-written code, or to translate code from one language to another, or to brainstorm different ways of approaching a problem when I have some idea but feel there's something better way to do it. Or I let it take a crack when I have some concrete failing test or build, feeding that into an LLM loop is one of my favorite things because it can just keep trying until it passes and even if it comes up with something suboptimal you at least have something that compiles that you can just tidy up a bit. Sometimes I'll have two sessions going but they're like 5-10 minute tasks. Long enough that I don't want to twiddle my thumbs for that long but small enough that I can rein it in.
- Kiro 9mo agoThey are not the same thing. If something works for me, I can rule out "it doesn't work at all". However, if something doesn't work for me I can't really draw any conclusions about it in general.
- geraneum 9mo ago> if something doesn't work for me I can't really draw any conclusions about it in general. You can. The conclusion would be that it doesn’t always work.
- frez1 9mo agowhat i enjoy the most is every "AI will replace engineers" article is written by an employee working at an AI company with testimonials from other people also working at AI companies
- jaccola 9mo ago- This has been going on for well over a year now. - They always write relatively long, zealous explainers of how productive they are (including some replies to your comment). These two points together make me think: why do they care so much to convince me; why don't they just link me to the amazing thing they made, that would be pretty convincing?! Are they being paid or otherwise incentivised to make these hyperbolic claims? To be fair they don't often look like vanilla LLM output but they do all have the same structure/patter to them.
- jennyholzer4 9mo ago[dead]
- drogus 9mo agoI think it's a mix of people being actually hyped and wishing this is the future. For me, productivity gains are mostly in areas where I don't have expertise (but the downside, of course, is I don't learn much if I let AI do the work) or when I know it's a throwaway thing and I absolutely don't care about the quality. For example, I'm bedtime reading a series of books for my daughter, and one of them doesn't have a Polish translation, and the Polish publisher stopped working with the author. I vibe coded an app that will extract an epub, translate each of the chapters, and package it back to an epub, with a few features like: saving the translations in sqlite, so the translation can be stopped and resumed, ability to edit translations, add custom instructions etc. It's only ~1000 lines of Rust code, but Claude generated it when I was doing dinner (I just checked progress and prompted next steps every few minutes). I can guarantee that it would take me at least an evening of coding, probably debugging problems along the way, to make it work. So while I know it's limited in a way it still lacks in certain scenarios (novel code in niche technology, very big projects etc), it is kinda game changer in other scenarios. It lets me do small tools that I just wouldn't have time to do otherwise. So I guess what I'm saying is, even with all the limitations, I kinda understand the hype. That said, I think some people may indeed exaggerate LLMs capabilities, unless they actually know some secret recipe to make them do all those awesome hyped things (but then I would love to see that).
- evilduck 9mo ago> why do they care so much to convince me; Someone might share something for a specific audience which doesn't include you. Not everything shared is required to be persuasive. Take it or leave it. > why don't they just link me to the amazing thing they made, that would be pretty convincing?! 99.99% of the things I've created professionally don't belong to me and I have no desire or incentives to create or deal with owning open source projects on my own time. Honestly, most things I've done with AI aren't amazing either, it's usually boring routine tasking, they're just done more cost efficiently. If you flip the script, it's just as damning. "Hey, here's some general approaches that are working well for me, check it out" is always being countered by the AI skeptics for years now as "you're lying and I won't even try it and you're also a bot or a paid shill". Look at basically every AI related post and there's almost always someone ready to call BS within the first few minutes of it being posted.
- ulfw 9mo agoIt's because the thing is overhyped and too many people are vested in keeping the hype going. Facing reality at this point, while necessary, is tough. The amount of ads for scam degrees from reputable unis about 'Chief AI Officer' bullshit positions is staggering. There's just tooo much AI bubbling
- SkyBelow 9mo agoIf someone seems to have productivity gains when using an AI, it is hard to come up with an alternate explanation for why they did. If someone sees no productivity gains when using an AI (or a productivity decrease), it is easy to come up with ways it might have happened that weren't related to the AI. This is an inherent imbalance in the claims, even if we both people have brought 100% proof of there specific claims. A single instance of something doing X is proof of the claim that something can do X, but no amount of instances of something not doing X is proof of the claim that something cannot do X. (Note, this is different from people claiming that something always does X, as one counter example is enough to disprove that.) Same issue in math with the difference between proving a conjecture is sometimes true and proving it is never true. Only one of these can be proven by examples (and only a single example is needed). The other can't be proven even by millions of examples.
- misja111 9mo agoA while ago someone posted a claim like that on LinkedIn again. And of course there was the usual herd of LinkedIn sheep who were full of compliments and wows about the claim he was making: a 10x speedup of his daily work. The difference with the zillion others who did the same, is that he attached a link to a live stream where he was going to show his 10x speedup on a real life problem. Credits to him for doing that! So I decided to go have a look. What I then saw was him struggling for one hour with some simple extension to his project. He didn't manage to finish in the hour what he was planning to. And when I had some thought about how much time it would have cost me by hand, I found it would have taken me just as long. So I answered him in his LinkedIn thread and asked where the 10x speed up was. What followed was complete denial. It had just been a hick up. Or he could have done other things in parallel while waiting 30 seconds for the AI to answer. Etc etc. I admit I was sceptic at the start but I honestly had been hoping that my scepticism would be proven wrong. But not.
- alex1138 9mo agoYou're supposed to believe in his burgeoning synergy so that one day you may collaborate to push industry leading solutions
- ruszki 9mo agoThere were such people also here. Copy-pasting the code would have been faster than their work, and there were several problems with their results. But they were so convinced that their work is quick and flawless, that they post a video recording of it.
- jennyholzer4 9mo agoHackernews is dominated by these people LLM marketers have succeeded at inducing collective delusion
- judahmeek 9mo ago> LLM marketers have succeeded at inducing collective delusion That's the real trick & one I desperately wish I knew how to copy. I know there's a connection to Dunning Kruger & I know that there's a dopamine effect of having a responsive artificial minion & there seems to be some of that "secret knowledge" sauce that makes cults & conspiracies so popular (there's also the promise of less effort for the same or greater productivity). Add the list grows, I see the popularity, but I doubt I could easily apply all these qualities to anything else.
- athrowaway3z 9mo agoPublic discourse on this is a dumpster fire. But you're not making a meaningful contribution. It is the equivalence of saying: Stenotype enthusiasts claim they're productive, but when we give them to a large group of typers we get data disproving that. Which should immediately highlights the issue. As long as these discussions aren't prefaced with the metric and methodology, any discussion on this is just meaningless online flame wars / vibe checks.
- immibis 9mo agoEverything you need to know about AI productivity is shown in this first chart here: https://metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/ https://metr.org/blog/2025-07-10-early-2025-ai-experienced-o...
- bearforcenine 9mo agoNot confident it's quite that straightforward. Here's a presentation from Meta showing a 6-12% increase in diff throughput for above-median users of agentic coding: https://www.youtube.com/watch?v=1OzxYK2-qsI https://www.youtube.com/watch?v=1OzxYK2-qsI
- LinXitoW 9mo agoProductivity gains in programming have always been incredibly hard to prove, esp. on an individual level. We've had these discussions a million times long before AI. Every time a manager tries to reward some kind of metric for "good" code, it turns out that it doesn't work that way. Every time Rust is mentioned, every C fan finds a million reasons why the improvement doesn't actually have anything to do with using Rust. AI/LLM discussions are the exact same. How would a person ever measure their own performance? The moment you implement the same feature twice, you're already reusing learnings from the first run. So, the only thing left is anecdotal evidence. It makes sense that on both sides people might be a little peeved or incredulous about the others claims. It doesn't help that both sides (though mostly AI fans) have very rabid supporters that will just make up shit (like AGI, or the water usage). Imho, the biggest part missing from these anecdotes is exactly what you're using, what you're doing, and what baseline you're comparing it to. For example, using Claude Code in a typical, modern, decently well architected Spring app to add a bunch of straight forward CRUD operations for a new entity works absolutely flawlessly, compared to a junior or even medior(medium?) dev. Copy pasting code into an online chat for a novel problem, in an untyped, rare language, with only basic instructions and no way for the chat to run it, will basically never work.
- lazarus01 9mo ago>> when others make claims to the contrary suddenly there is some overwhelming burden of proof that has to be reached That is just plain narcissism. People seeking attention in the slipstream of megatrends, make claims that have very little substance. When they are confronted with rational argument, they can’t respond intellectually, they try to dominate the discussion by asking for overwhelming burden of proof, while their position remains underwhelming. LinkedIn and Medium are densely concentrated with this sort of content. It’s all for the likes.
- deleted 9mo ago[deleted]
- Hobadee 9mo agoI will prefix this all by saying I'm not in a professional programming position, but I would consider myself an advanced amateur, and I do code for work some. (General IT stuff) I think the core problem is a lot of people view AI incorrectly and thus can't use it efficiently. Everyone wants AI to be a Jr or Sr programmer, but I have serious doubts as to the ability of AI to ever have original thought, which is a core requirement of being a programmer. I don't think AI will ever be a programmer, but rather a tool to help programmers take the tedium away. I have seen massive speedups in my own workflow removing the tedium. I have found prompting AI to be of minimal use, but tab-completion definitely speeds stuff up for me. If I'm about to create some for loop, AI will usually have a pretty good scaffold for me to use. If I need to handle an error, I start typing and AI will autocomplete the error handling. When I write my function documentation I am usually able to just tab-complete it all. Yes, I usually have to go back and fix some things, and I will often skip various completion hints, but the scaffold is there, and as I start fixing faulty code it generated AI will usually pick up on the fixes and help me tab-complete the fixes themselves. If AI isn't giving me any useful tab-completions, I'll just start coding what I need, and AI picks up after a few lines and I can tab-complete again. Occasionally I will give a small prompt such as "Please write me a loop that does X", or "Please write a setter function that validates the input", but I'll still treat that as a scaffold and go back and fix things, but I always give it pretty simple tasks and treat it simply as a scaffold generator. I still run into the same problem solving issues I had before AI, (how do I tackle X problem?) and there isn't nearly as much speedup there, (Although now instead of talking to a rubber duck, I can chat with AI to help figure things out) but once I settle on the solution and start implementing it, I get that AI tab completion boost again. With all that being said, I do also see massive boosts with fairly basic tasks that can be templated off something that already exists, such as creating unit tests or scaffolding a class, although I do need to go back and tweak things. In summary, yes, I probably do see a 10x speedup, but it's really a 10x speedup in my typing speed more than a 10x speedup in solving the core issues that make programming challenging and fun.
- egeozcan 9mo ago> I have serious doubts as to the ability of AI to ever have original thought, which is a core requirement of being a programmer If you find a job as an enterprise software developer, you'd see that your core requirement doesn't hold :)
- bryanrasmussen 9mo agosubjective experience is heavily influenced by expectations and desires, so they should try to verify.
- DauntingPear7 9mo agoAs a CS student who kinda knows how to build things. I do in fact get a speedup when querying AI or letting AI do some coding for me. However, I have a poor understanding of the system it builds, and it does a quite frankly terrible job with project architecture. I use Claude sonnet 4.5 with Claude code, and I can get things implemented rather quickly while using it, but if anything goes wrong I just don’t have that great of an idea where anything is, what code is in charge of what, etc. I can also deeply feel the brainrot of using AI. I get lazy and I can feel myself getting worse at solving what should be easy problems. My mental image of the problem to solve gets fuzzy and I don’t train that muscle like I would if I didn’t use AI to help me solve it.