Lazy work used to mean too little output.
Now, with AI, it often means too much and more work for everyone else.
@tobi call it "slop grenades."
A "Slop Grenade" is when you let AI produce the work and pass it on without adding any value (including checking it).
Someone else has to wade through it, catch the mistakes, and clean up the mess.
You save time and look productive but someone else pays for it.
C# is pure dominance. Clean syntax that respects your time, features like LINQ and async that feel illegal, and .NET power that scales from Unity blockbusters to enterprise beasts. Other languages talk. C# ships.
Absolutely beautiful rant about AI in Linux Kernel from Linus yesterday:
I realize that some people really dislike AI, but this is an area
where I'm willing to absolutely put my foot down as the top-level
maintainer.
Linux is not one of those anti-AI projects, and if somebody has issues
with that, they can do the open-source thing and fork it.
Or just walk away.
AI is a tool, just like other tools we use. And it's clearly a useful one.
It may not have been that "clearly" even just a year ago, but it's no
longer in question today.
There are other questions around AI (like what the economy of it will
actually look like in the end), but "is it useful" is no longer one of
those questions. Anybody who doubts that clearly hasn't actually used
it.
Yes, it can also be a somewhat painful tool, both for maintainer
workloads and just from a "it keeps finding embarrassing bugs"
standpoint.
But the solution is not to put your head in the sand and sing "La La
La, I can't hear you" at the top of your voice like some people seem
to do.
The solution is to make sure those LLM tools _help_ maintainers
instead of just causing them pain. There's no question on that side.
We're not forcing anybody to use it, but I will very loudly ignore
people who try to argue against other people from using it.
And no, AI isn't perfect. But Christ, anybody who points to the
problems at AI had better be looking in the mirror and pointing at
themselves at the same time.
Because it's not like natural intelligence is always all that great either.
The kernel project has been and will continue to be about the technology.
Sure, the social angle of working on open source is important and
often a very motivating part of the project, but in the end that's a
side benefit, not the _point_ of the project.
This is *NOT* some kind of "social warrior" project, never has been,
and never will be.
In the kernel community we do open source because it results in better
technology, not because of religious reasons.
And so we make decisions primarily based on technical merit. Not fear
of new tools.
Linus
It's been 3 months since the 100x vibers started 100x vibin'! So, post your 25-years-of-work-equivalent project here, so we can signal boost and everyone can celebrate the Life's Work that you did in 3 months. Looking forward to it, Let's Go!!!
@warpdotdev 's revenue is up 19x this year. Our first $1M ARR took 300+ days (it took a lot of time to build an ADE from scratch!).
Now we add $1M every ~10 days and the pace is accelerating.
Sharing this because (a) I'm proud of our progress and (b) I want the world to know that our vision of agentic development where every dev task starts with a prompt is catching on.
We are hiring awesome engineers and GTM - come join us.
Workaccount2 on Hacker News just coined the term "context rot" to describe the thing where the quality of an LLM conversation drops as the context fills up with accumulated distractions and dead ends https://t.co/2oWaMhlZDi
"container is a tool that you can use to create and run Linux containers as lightweight virtual machines on your Mac. It's written in Swift, and optimized for Apple silicon." https://t.co/RE7Gb1QrQX
Congratulations @crosbymichael@ehazlett@MadhuVenugopal!
This might be the best visualization of limitations of LLMs.
LLms learn from a distribution. The further away from this distribution we ask the LLM, the less reliable the answer.
Larger LLMs = better performance, but inherently it's the same pattern.LLM's