201–209 of 209 posts
I keep thinking of a friend in finance in pre-crash 2008 who could see the emperor had no clothes but was derided by his enthusiastic coworkers every time he opened his mouth.
On one hand, AI helps me and my team ideate and prototype quickly. On the other, it’s replacing the fun part of coding with the annoying part: troubleshooting its thought process and fixing its generated code.
I’d say it’s still too early to have a concrete opinion.
Earlier quoted context omitted.
> Those "experienced" actually are just senior code monkeys if u ask me, it's trivial right Well, it seems you are not open for discussion. There is no reason to disparage the senior devs that participated in the study just because you don't like the results of the study. But the study happened, and it is clear: experienced developers are the ones that suffered from using LLMs. > but it's just illogical for a junior…
That study was not conducted well at all. The participants haven’t learned how to use these tools. For example one was interviewed later and said a lot of the time they would wait for an agent and get distracted playing with something irrelevant and then forget to go back until much later. That has solutions they are not aware of to implement.
Counterpoint: the agents are the reason for the distraction.
> That has solutions they are not aware of to implement.
Counterpoint: there are no other current studies that suggest otherwise. Given the impact of LLMs on open source (net negative, maintainers are drowning in slop: e.g curl: https://daniel.haxx.se/blog/2025/07/14/death-by-a-thousand-s...) maybe it makes sense to be a bit more critical on LLM's supposed gains.
Let's see what we have so far:
- The only study to date suggests a net negative from using LLMs on experienced developers
- OSS maintainers are rejecting AI generated PRs due to low quality
- No other studies have come out so far to suggest otherwise
Based on my anecdotal experience and based on the currently available evidence, for me the conclusion is clear: LLMs and agents are mostly hype.
Earlier quoted context omitted.
That study was not conducted well at all. The participants haven’t learned how to use these tools. For example one was interviewed later and said a lot of the time they would wait for an agent and get distracted playing with something irrelevant and then forget to go back until much later. That has solutions they are not aware of to implement.
> For example one was interviewed later and said a lot of the time they would wait for an agent and get distracted playing with something irrelevant and then forget to go back until much later Counterpoint: the agents are the reason for the distraction. > That has solutions they are not aware of to implement. Counterpoint: there are no other current studies that suggest otherwise. Given the impact of LLMs on open sou…
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. The study reflects usage of emergent tools without training, and with regressive training on previous generation sequential processes, so I would expect these results. If there is any merit in coordinating multiple agents on slower feedback work, this study would not find it.
Earlier quoted context omitted.
You don't use any AI - drafting documentation, write boilerplate code, transcribing meetings, simplifying team communications, searching product documentation, alternative to Google or StackOverflow, creating presentations, as a brainstorming partner? I would consider all of these "work". If you say AI does 0% of your work, I'd say you're either a genius, behind the curve or being disingenuous.
LLM does 0% of my work, don't know what to tell you. LLMs are like 3 years old, I learned to do everything I know without LLMs, how is that hard to believe? How do you think all the software you use everyday, including this site itself, was written? 99.99% of it without any LLMs at all. Do I use LLMs as an alternative to Googling? Absolutely. That doesn't mean AI is doing my job. Google and Stack Overflow also do 0%…
In my opinion, the only thing that AI is helpful for is doing all the menial boilerplate nonsense that is only necessary because the unexperienced people in charge of so many projects. For example, setting up 30 totally unnecessary GitHub actions, etc. Anything that is worth doing, I'd rather do myself and not lose my skills.
Neural Networks have the long tail risk problem. In that they are good at returning the top 20% of answers to you. But they are pretty poor at returning the less common 80% answers.
I have seen the different tools return the wrong code, code with security issues or code that was open source that is not legal to use in your project without open sourcing it.
The big tech companies are selling it as AGI and this massive replacement tool to get more money. But really it is just gaining a few percentage points of productivity.
Most modern development tools can do the same. Like if you are able to build a app with some low code method. I have not seen a AI build app that i could not build in a low code system in the same amount of time.