Unsurprisingly it works OK when it's about finding syntax errors you made or about low stakes mechanical work you need to repeat. The leash has to be very short.
Such contributions still don't exist. Or their quality is so abyssal that they waste everyone's time. Don't fall for the marketing speak.
Looks like the productivity gain promises are still mostly hypothetical. Except on specific limited tasks of course but that doesn't cover for a whole job. Also, when there is a gain it's apparently not the workers who benefit from them.
The metaphors are... funny. But still I think there's good lesson in there. If you use generative AI tools for development purposes, don't loose sight of the struggle needed to learn and improve. Otherwise you won't be able to properly drive those tools after a while.
This is a question which I have been pondering for a while... what will be left when the generative AI bursts. And indeed it won't be the models as they won't age well. The conclusion of this article got a chill running down my spine. It's indeed likely that the conclusion will be infrastructure for a bigger surveillance apparatus.
Sourcehut pulled the trigger on their crawler deterrent. Good move, good explanations of the reasons too.
This matches what I see. For some tasks these can be helpful tools, but it definitely need a strong hand to steer them in the right direction and to know when to not use them. If you're a junior you'd better invest in the craft rather than such tools. If you got experience, use with care and keep the ethical conundrum in mind.
Even if you use LLMs, make sure you don't depend on them in your workflows. Friction can indeed have value. Also if you're a junior you should probably seldom use them, build your skill and knowledge first... otherwise you'll forever be a beginner and that will bite you hard.
I somehow recognise myself in this piece. Not completely though, I disagree with some of the points... but we share some baggage so I recognize another fellow.
Again that confirms that all the hype and grand announcements are not deserved. It also gives a good idea of the skills which are required to use those tools, clearly the setup process is involved if you want to don't want to be overwhelmed and drowning in bad code.
And yet another reverse proxy to use as a scraper deterrent... It looks like several are popping every week lately.
Don't underestimate how much of a skill making a stupid crawler can be...
Despite the marketing speak... it's definitely not there yet. So far all the attempts at using LLM for coding larger pieces end up in this kind of messy results. It helps kickstarting a project indeed but quickly degenerates after that.
More details about the impacts of the LLM companies acting like vandals... This is clearly widespread and generating work for everyone for nothing.
Those bots are really becoming the scourge of the Internet... Is it really necessary to DDoS every forge out there to build LLMs? And that's not even counting all the other externalities, the end of the article make it clear: "If blasting CO2 into the air and ruining all of our freshwater and traumatizing cheap laborers and making every sysadmin you know miserable and ripping off code and books and art at scale and ruining our fucking democracy isn’t enough for you to leave this shit alone, what is?"
People really need to be careful about the short term productivity boost... If it kills maintainability in the process you're trading that short term productivity for a crashing long term productivity.
This is definitely a problem. It's doomed to influence how tech are chosen on software projects.
The security implications of using LLMs are real. With the high complexity and low explainability of such models it opens the door to hiding attacks in plain sight.
This is an interesting way to frame the problem. We can't rely too much on LLMs for computer science problems without loosing important skills and hindering learning. This is to be kept in mind.
Again it's definitely not useful for everyone... it might even be dangerous for learning.