181–190 of 257 posts
A reminder that that your LLM output isn't your intellectual property no matter how much effort you feel went into its prompting. Copyright protects human creations and the US Copyright Office has made it clear that AI output cannot be copyrighted without significant creative alterations from humans of the output after it is generated.
I have 30+ years of industry experience and I've been leaning heavily into spec driven development at work and it is a game changer. I love programming and now I get to program at one level higher: the spec. I spend hours on a spec, working with Claude Code to first generate and iterate on all the requirements, going over the requirements using self-reviews in Claude first using Opus 4.5 and then CoPilot using GPT-5.…
No matter how much I tell it that it is a "professional experienced 10x developer versed in modern C++, a second coming of Stroustrup" in per-project or global config files it still keeps spewing the same crap big (like manual memory management instead of RAII here and there, initializing fields in ctor body instead of initializer list, having manual init/cleanup methods in classes instead of a proper ctor/dtor design to ensure that objects are always in a consistent state, bunch of other anti-patterns, etc.) and small (checking for nullptr before passing the pointer to delete/free, manually instantiating objects as argument to shared_ptr ctor instead of make_shared, endlessly casting stuff around back and forth instead of designing data types properly, etc.).
Which makes sense I guess because it is how average C++ code on GitHub looks like unfortunately and that is what all those models were trained on, but I keep feeling like my job turning into performing endless code review for a not-very- bright junior developer that just refuses to learn...
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Thanks, sharing a lot on X / BlueSky + YouTube but once the C course on YouTube will be finished, I'll start a new course on programming in this way. I need a couple more lessons to declare the C course closed (later I'll restart it likely, the advanced part). So I can start with the AP course.
Looking forward! The C course is great!
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I don't think it's possible to separate any open source contribution from the ones that came before it, as we're all standing on the shoulders of giants. Every developer learns from their predecessors and adapts patterns and code from existing projects.
If you fork an open source project and nuke the git history, that's considered to be a "dick move" because you are erasing the record of people's contributions. LLMs are doing this on an industrial scale.
“Information provenance” could (and I think most likely would, although I’m very unfamiliar with LLM internals) be which sources most plausibly derive an output, so even output that exists today could eventually get proper attribution.
At least today if you know something’s origin, and it’s both obvious and publicly online, you have proof via the Internet Archive.
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Are you against copyright, patents, and IP in all forms then?
Absolutely. As any logical person should be.
Declaring that your side has a monopoly on logic is rarely helpful.
We maybe witnessing the last generation of master software artisans like antirez. This is beautiful to see, their mastery harnessing the power of the intelligent machine tools to design, understand and build. This is like seeing a master of image & light like michelangelo receiving a camera, photoshop and a printer. It's an exponential elevation of the art. But to become a master like michelangelo one had to dedicate…
>A master like antirez had to wrap his head around concepts alien to the human mind. Bits, bytes, arrays, memory layout, processors, compilers, interfaces, abstractions, constraints, types, concurrency do not exist in the savannas that forged brains.
You still need to know these things if you're doing anything more complicated than making some CRUD dashboard. LLMs assist with some code generation, and assist with some knowledge lookup. That's pretty much it.
What seems to be the case is that you need to know everything you needed to know before, and* become good at leveraging AI tooling to make you go faster.
*Even this is optional. There is absolutely nothing stopping anyone from just ignoring everything about AI and keep developing software like pre-2022. The efficiency difference isn't even significance in the grand scheme of things. It's not like people had reams of perfect software specs just lying around waiting to be implemented. That's just not how people develop software; usually the spec emerges while you're writing the program.
We maybe witnessing the last generation of master software artisans like antirez. This is beautiful to see, their mastery harnessing the power of the intelligent machine tools to design, understand and build. This is like seeing a master of image & light like michelangelo receiving a camera, photoshop and a printer. It's an exponential elevation of the art. But to become a master like michelangelo one had to dedicate…
> We maybe witnessing the last generation of master software artisans like antirez. I'm told that chess is more popular than ever, despite it being decades since a human could dream of beating a top computer at it.
I have 30+ years of industry experience and I've been leaning heavily into spec driven development at work and it is a game changer. I love programming and now I get to program at one level higher: the spec. I spend hours on a spec, working with Claude Code to first generate and iterate on all the requirements, going over the requirements using self-reviews in Claude first using Opus 4.5 and then CoPilot using GPT-5.…
How does the resulting code look like though? I found that while can spit out barely working C++ code fast, I then have to spend 10x time prodding it to refactor the code to look at least somewhat acceptable. No matter how much I tell it that it is a "professional experienced 10x developer versed in modern C++, a second coming of Stroustrup" in per-project or global config files it still keeps spewing the same crap b…
On the other hand, LLMs are great at Go because Go was designed for average engineers at scale, and LLMs behave like fast average engineers. Go as a language was designed to support minimal cleverness (there's only so many ways to do things, and abstractions are constrained). This kind of uniformity is catnip for LLM training.
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Independent of ones philosophical stance on the broader topic: I find it highly concerning that AI companies, at least right now, seem to be largely exempt from all those rules which apply to everyone else, often enforced rigorously.
I draw from this that no-one should be subject to those rules, and we should try to use the AI companies as a wedge to widen that crack. Instead, most people people who claim that their objection is really only consistency, not love for IP spend their time trying to tighten the definitions of fair use, widen the definitions of derivative works, and in general make IP even stronger, which will effect far more than jus…
suppose I write a webnovel that I publish for free on the net, and I solicit donations. Kinda like what's happening today anyway.
Now suppose I'm not good at marketing, but this other guy is. He takes my webnovel, changes some names, and publishes it online under his name. He is good at social media and marketing, and so makes a killing from donations. I don't see a dime. People accuse me of plagiarism. I have no legal recourse.
Is this fair?