91–100 of 113 posts
I had a team of developers and essentially told them all 'either learn to code with Claude' or you're out. What I found is the more junior developers started 'vibe coding' resulting in a net decrease in performance, where the more senior ones used it to accelerate their speed cautiously and selectively. My conclusion was senior engineers were better because they were used to managing developers and taking on more man…
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How do you find the quality of the Haskell code produced by LLM? Also, how do you use the LLM when coding Haskell? Generating single functions or more?
I'm stuck in my ways with vim/tmux/ghci etc, so I'm not using some AI IDE. I write stuff into ChatGPT and use the output, copying manually, or writing it myself with inspiration from what I get. I feed it a fair bit of context (like, say, a production module with a load of database queries, and the associated spec module) so that it copies the structure and patterns that I've established. The quality of the Haskell c…
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People who get overly excited from every new shining thing also thought that NFTs and Crypto and web3 (whatever the heck it means) are the next coming of Jesus. If LLM boosters were not so preachy about it, I'd left them off the hook easier. But at the current moment: - Only study up to date shows experienced developers have 19% less productivity when using LLMs https://metr.org/blog/2025-07-10-early-2025-ai-experien…
If we put people in a jet with poor training and they crash, that's the pilot's fault, yet if people crash LLMs, that's the LLMs fault. If a study showed 95% of people crashed jets without training, I wouldn't take that as a sign jets are a flawed idea. As it is, I have no problem with your naysaying, I'm getting results, your disbelief doesn't change that, in fact I find it more amusing than anything.
Mystical practitioners discount the studies done in the open as not fair or not being done right, or the people participating not believing in it hard enough.
My man, 95% of AI pilots failed.
https://fortune.com/2025/08/18/mit-report-95-percent-generat...
> As it is, I have no problem with your naysaying, I'm getting results, your disbelief doesn't change that
Studies and evidence mean nothing to cults and religious believers, so yeah, I am happy that you feel and believe like you have your personal connection to the higher being that is the LLM. Keep the faith!
LLMs are very useful tools for software development, but focusing on employment does not appear to really dig into if it will automate or augment labor (to use their words). Behaviors are changing not just because of outcomes but because of hype and expectations and b2b sales. You'd expect the initial corporate behaviors to look much the same whether or not LLMs turn into fully-fire-and-forget employee-replacement to…
> LLMs are very useful tools for software development That's an opinion many disagree with. As a matter of fact, the only limited study up to date showed that LLMs usage decrease productivity for experienced developers by roughly 19%. Let's reserve opinions and link studies. https://metr.org/blog/2025-07-10-early-2025-ai-experienced-o... My anecdotal experience, for example, is that LLMs are such a negative drain on…
That’s a massive overstatement of what the study found. One big caveat is this: “our developers typically only use Cursor for a few dozen hours before and during the study.” In other words, the 19% slowdown could simply be a learning curve effect.
> one has to be really early in their career to benefit from their usage.
I have decades of experience, and find them very beneficial. But as with any tool, it helps to understand what they are and aren’t good at, and hope to use them effectively. That knowledge comes with experience.
Be careful of dismissing a new tool just because you haven’t figured out how to use it effectively.
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That's a skill issue. That lone study was observing untrained participants. It's no surprise to me that devs who are accustomed to working on one thing at a time due to fast feedback loops have not learned to adapt to paralellizing their work (something that has been demonized at agile style organizations) and sit and wait on agents and start watching YouTube instead, as the study found (productivity hits were due to…
Interesting take. I suggest an alternative take: it's a skill issue if LLMs help a developer. If the study showed that experienced developers suffered a negative performance impact while using an LLM, maybe where LLMs shine are with junior developers? Until a new study that shows otherwise comes out, it seems the scientific conclusion is that junior developers, the ones with the skill issues, benefit from using LLMs,…
There is this paper that surveys results of 37 studies and reaches a different conclusion: https://arxiv.org/abs/2507.03156
> Our analysis reveals that LLM-assistants offer both considerable benefits and critical risks. Commonly reported gains include minimized code search, accelerated development, and the automation of trivial and repetitive tasks. However, studies also highlight concerns around cognitive offloading, reduced team collaboration, and inconsistent effects on code quality.
Why are you ignoring the existence of these 37 other studies and pretending the one study you keep sharing is the only in existence and thus authoritatively conclusive?
Furthermore from the study you keep sharing, they state:
> We do not provide evidence that: AI systems do not currently speed up many or most software developers. Clarification: We do not claim that our developers or repositories represent a majority or plurality of software development work
Why do YOU claim that this study provides evidence, conclusively and as settled science, that AI systems do not speed up many or most developers? You are unscientifically misrepresenting the study you are so eager to share. You are a complete “hype man” for this study beyond what it evidences because of your eagerness for a way to shut down discourse and dismiss any progress since the study’s focus on Sonnet 3.5. The study you share even says that there has been a lot of progress in the last five years and future progress as well as different techniques in using the tools may produce productive results and that the study doesn’t evidence otherwise! You are unserious.
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My argument is limited to “we don’t know and one study with significant limitations with regards to participant adaptation doesn’t settle anything definitively for the long-term”. Your argument seems to project significantly more certainty and spittle.
The LLM crowd always sees themselves as messianic and victims, eerly reminding me of the NFT crowd back 1 year ago. I would not be surprised if a lot of those are the same folks. The burden of proof is on the ones saying a new concept/tool (LLMs/NFT) is revolutionary or useful. I provided studies showing not only the new concept is not revolutionary, but that it is a step back in terms of productivity. Where are the…
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My argument is limited to “we don’t know and one study with significant limitations with regards to participant adaptation doesn’t settle anything definitively for the long-term”. Your argument seems to project significantly more certainty and spittle.
The LLM crowd always sees themselves as messianic and victims, eerly reminding me of the NFT crowd back 1 year ago. I would not be surprised if a lot of those are the same folks. The burden of proof is on the ones saying a new concept/tool (LLMs/NFT) is revolutionary or useful. I provided studies showing not only the new concept is not revolutionary, but that it is a step back in terms of productivity. Where are the…
You submitted one study and claimed it’s the only in existence (it’s not)
“I got the receipts”
You have one receipt that you misrepresent by saying it scientifically settles things the paper itself points out that it explicitly does not claim
Hysteresis is a bitch.
This study showed that early career workers of which they only focused on the 22-25 range had a ~20% drop in employment between 2022 and now. If you include the 26-30 range which includes most early-career that's roughly ~30% less jobs, from the Payment Processors perspective.
The study doesn't seek to cover other impactors such higher costs on the labor pool, and interference in employment matching, which are also of great concern.
30% after shock normalization is well beyond statistical significance. This is happening, people said it would happen, and no one acted to stop it because they listened to evil people seeking short-term profit; blind to all else.
Sad and dark times are ahead. There are things that can be reasonably predicted ahead-of-time, but the moment you give preferential treatment to liars is the moment you lock in losses. Sure the data proving the prediction will come, but not in time to take corrective action; such is the structured cascading failures involving hysteresis.
I had a team of developers and essentially told them all 'either learn to code with Claude' or you're out. What I found is the more junior developers started 'vibe coding' resulting in a net decrease in performance, where the more senior ones used it to accelerate their speed cautiously and selectively. My conclusion was senior engineers were better because they were used to managing developers and taking on more man…
When you set impossible constraints that neglect requirements for sustainability, and tell people to do the impossible, you pigeonhole and sieve only the people you are actually looking for (the ones that can meet that sieve).
The lying, and deceit that you do, naturally occur after-the-fact (which blind people don't notice, often making them evil). The danger of most deceit and lying occur where you say something truthful omitting something important that they know, but then later contradict yourself in the outcome. These are called lies of omission. Deceivers and Vipers take full effect of these actions pretending its not them, its the circumstance, but a circumstance they control.
Of course the middle team would be the only ones left, after all you tortured your senior team having them baby a LLM driving them to burnout, and the junior team lacked the knowledge that makes the difference between Junior and Mid, to be productive. You set a filter that only your midlevel team could meet, and any conclusions you make will equally conform to your initial decisions in the criteria you set which is you don't want to hire young people, or old people. You want them just right, and there are laws against age discrimination. People have tried to get around these laws for years, and have never had more luck in evading these than now; with the advent of blackbox AI which can obscure these type of decisions through hiding them in the weights. Short term, there will of course be more profit, long-term the lawsuits will get you, and your good character which you thought you had will not be good.
Additionally, you have your perfect team left that is wholly dependent on LLM, who won't be able to solve the rare but inevitable problems the senior level people would (before they occur).