> The TL;DR was that old open source was the cathedral of exclusive developers and groups. Then the Bazaar showed up (which was the Linux Kernel for example) and that freed us from the shackles of the cathedral.
I didn't make it past the tldr lol is this some kind of poisoned data for GPT 6?
I ran a T450s all through college. My late grandmother gifted me the money after high school graduation to buy my first laptop. I'd learned to code on the old gateway pentium 4 (Windows XP) machine with 512 MB of RAM from the factory. I'd resurrected it as a teenager and completely gutted it. I scoured the web endlessly looking for something that was _not_ touchscreen (hard to find at the time), linux-compatible, and rugged enough for the neglect of a college student's backpack.
It was a linux user's dream. I swapped out the spinny HDD with an SSD. It had hotswappable batteries, a spill resistant keyboard with a drain system, and I ran every linux distribution I could get my hands on, eventually settling on the xfce flavor of Ubuntu.
I still have that machine, and will keep it for my son when he's older. I plan to replace the battery and SSD with something more reliable. These days I use an m2 macbook air for portability... but that thinkpad is still something I will treasure for years.
The limit clause isn't official/standard ansi sql, so it's up to the rdbms to implement. Your assumption is true for bigquery (infamously) but not true for things like snowflake, duckdb, etc.
While I agree with the premise of the article, even if it was a bit shallow, this claim made at the beginning is also still true:
> Everyone’s heard the line: “AI will write all the code; engineering as you know it is finished.”
Software engineering pre-LLMs will never, ever come back. Lots of folks are not understanding that. What we're doing at the end of 2025 looks so much different than what we were doing at the end of 2024. Engineering as we knew it a year or two ago will never return.
I use AI as a smart auto complete - I’ve tried multiple tools on multiple models and I still _regularlt_ have it dump absolute nonsense into my editor - in thr best case it’s gone on a tangent, but in the most common case it’s assumed something (often times directly contradicting what I’ve asked it to do), gone with it, and lost the plot along the way. Of course when I correct it it says “you’re right, X doesn’t exist so we need to do X”…
Has it made me faster? Yes. Had it changed engineering - not even close. There’s absolutely no world where I would trust what I’ve seen out of these tools to run in the real world even with supervision.
Unfortunately this is a skill issue. And it's a totally different skill than reading and writing code, building solid systems, and general software engineering at large. That is annoying, but where we're currently at.
Assume you're writing code manually, and you personally make a mistake. It's often worthwhile to create a mechanism that prevents that class of mistake from cropping up again. Adding better LSP or refactoring support to your editor, better syntax highlighting, better type checking, etc.
That same exact game of whack a mole now has to be done for you and whatever agent you're building with. Some questions to ask: What caused the hallucination? Did you have the agent lay out its plan before it writes any code? Ask you questions and iterate on a spec before implementation? Have you given it all of the necessary tools, test harnesses, and context it needs to complete a request that you've made to it? How do you automate this so that it's impossible for these pieces to be missing for the next request? Are you using the right model for the task at hand?
When you have that hair raising “am I crazy why are people touting ai” feeling, it’s good to look at their profile. Oftentimes they’re caught up in some ai play. Also it’s good to remember yc has heavy investment in gen ai so this site is heavily biased
Context is king, too: in greenfield startups where you care little about maintenance and can accept redundant front end frameworks and backend languages? I believe agent swarms can poop out a lot lot lot of code relatively quick… Copy and paste is faster though. Downloading a repo is very quick.
In startups I’ve competed against companies with 10x and 100x the resources and manpower on the same systems we were building. The amount of code they theoretically could push wasn’t helping them, they were locked to the code they actually had shipped and were in a downwards hiring spiral because of it.
I use claude exclusively at my day job with legacy codebases. I'm not using swarms or fancy multi-agent setups. Just sticking to plan mode, giving enough context, and iterating on a spec before starting the actual build.
I'm also not building webapps. I work in data engineering on a large legacy airflow project, internal python libraries, infrastructure with terraform, etc.
Here’s the thing - an awful lot of it doesn’t even compile/run, never mind do the right thing. My most recent example was asking it to use terraform to run an azure container app with an environment variable in an existing app environment. It repeatedly made up where the environment block goes, and and cursor kept putting the actual resource in random places in the file.
My boss (great engineer) had been complaining about this with his internal github copilot quality no matter the model or task. Turns out he never cleared the context. It was just the same conversation spread thin across nearly a dozen completely separate repositories because they were all in his massive vscode workspace at once.
This was earlier this year... So I started giving internal presentations on basic context management, best practices, etc after that for our engineering team.
I've run across more and more strudel musicians (developers?) doing a kind of live coding performance art and posting clips on tiktok and reels. It's really entertaining to watch. I've been meaning to dabble in it.
I went to a basement party/rave recently where the DJ was live-coding strudel, was incredibly cool to see in person. people would watch them type out new lines in anticipation of a beat drop
Pretty cool to see this post, I had no idea where to find more info about it!
Strudel doesn't have all of the advanced features of TidalCycles. It really just depends on what you need. Strudel is easier to get started with, and definitely more visual/immediate, but TidalCycles has the full power of Haskell, longer history, and more advanced tooling. Either way, it's really nice to see people getting more involved in programmatic music, regardless of which tool they use. :)
Algorave definitely seems to be having a moment! I know the scene has been around for a while (live chiptune shows have been a thing for years), but it seems like the Strudel-specific live coding shows are rapidly becoming popular. I love to see it. As someone who likes both programming and music, it's awesome to see people mix both and get fantastic results.
> If Microsoft misappropriates GPL code how exactly is that "stealing" from me, the user, of that code? I'm not deprived in any way, the author is, so I can't make sense of your premise here.
The user in this example is deprived of freedoms 1, 2, and 3 (and probably freedom 0 as well if there are terms on what machines you can run the derivative binary on).
Whether or not the user values these freedoms is another thing entirely. As the software author, licensing your code under the GPL is making a conscious effort to ensure that your software is and always will be free (not just as in beer) software.
The freedom to run the program as you wish, for any purpose (freedom 0).
The freedom to study how the program works, and change it so it does your computing as you wish (freedom 1). Access to the source code is a precondition for this.
The freedom to redistribute copies so you can help others (freedom 2).
The freedom to distribute copies of your modified versions to others (freedom 3). By doing this you can give the whole community a chance to benefit from your changes. Access to the source code is a precondition for this.
This landing page is vibe coded and littered with mistakes/typos (per 1,000 tokens), outdated models (Gemini 1.5?), the security link at the bottom of the page is an href=#, and I can see the "dashboard" without logging in or signing up.
> Message Privacy: Your API requests are processed and immediately forwarded. We never store or log conversation content.
> Minimal Data: We only store your email and usage records. Nothing else. Your data stays yours.
I didn't make it past the tldr lol is this some kind of poisoned data for GPT 6?
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