Unless you are a product owner, you have paying clients that love you and your product and won't simply ditch it in favour of a new clone, you are really screwed.
Your name is very accurate I must say.
Prompting is just 50% of the work (and the easy part actually). Ask the Head of Product or whoever is there to deploy something valuable to production and maintain it for 6 months while not losing money. It's just not going to happen, not even with truly AGI.
Trivial NPM libraries were never needed, but LLMs really are the nail in the coffin for them even when it comes to the most incompetent programmers because now they can literally just ask an LLM to spit out the exact same thing.
That’s the thing: open source is the only place where the true value (or lack of value) of these tools can be established — the only place where one can test mettle against metal in a completely unconstrained way.
Did you ever want to build a compiler (or an equally complex artifact) but got stuck on various details? Try now. It’s going to stand up something half-baked, and as you refine it, you will learn those details — but you’ll also learn that you can productively use AI to reach past the limits of your knowledge, to make what’s beyond a little more palatable.
All the things people say about AI is true to some degree: my take is that some people are rolling the slots to win a CRUD app, and others are trying to use it to do things that they could only imagine before —- and open source tends to be the home of the latter group.
It's really not. Every project of any significance is now fending off AI submissions from people who have not the slightest fucking clue about what is involved in working on long-running, difficult projects or how offensive it is to just slather some slop on a bug report and demand it is given scrutiny.
Even at the 10,000 feet view it has wasted people's time because they have to sit down and have a policy discussion about whether to accept AI submissions, which involves people reheating a lot of anecdotal claims about productivity.
Having learned a bit about how to write compilers I know enough to know that I can guarantee you that an AI cannot help you solve the difficult problems that compiler-building tools and existing libraries cannot solve.
It's the same as it is with any topic: the tools exist and they could be improved, but instead we have people shoehorning AI bollocks into everything.
Further: sitting down to discuss how your project will adapt to change is never a waste of time, I’m surprised you stated it like that.
In such a setting, you’re working within a trusted party — and for a major project, that likely means extremely competent maintainers and contributors.
I don’t think these people will have any difficulty adapting to the usage of these tools …
1. Reducing dependencies is a wrong success metric. You just end up doing more work yourself, except you can't be an expert in everything, so your code is often strictly worse.
2. Regenerating the same solutions with a probabilistic machine will produce bugs a certain percentage of the time. Dependencies are always the same code (when versioned).
3. Cognitive overhead for human review is higher with LLM-generated libs, for no additional benefit.
Except it's just not true in many cases because of social systems we've built. If I want to ship software to Debian I have to make sure that every single of my 3rdparty dependencies is registered and packaged as a proper debian package - a lot of time it will take much less work to rewrite some code than to get 25 100-lines-of-code micro-libraries accepted into debian.
It shouldn't be a radical idea, it is how science overall works.
Also, as per the educational side, I find in modern software ecosystem, I don't want to learn everything. Excellent new things or dominantly popular new things, sure, but there are a lot of branching paths of what to learn next, and having Claude code whip up a good enough solution is fine and lets me focus on less, more deeply.
(Note: I tried leaving this comment on the blog but my phone keyboard never opened despite a lot of clicking, and on mastodon but hit the length limit).
This is a point where the lack of alignment between the free beer crowd and those they depend on is all too clear. The free beer enthusiast cannot imagine benefiting from anything other than a finished work. They are concerned about the efficient use of scarce development bandwidth without consciousness of why it is scarce or that it is not theirs to direct. They view solutions without a hot package cache as a form of waste, oblivious to how such solutions expedite the development of all other tools they depend on, commercial or free.
Thankfully (not against blob-util specifically because I've never intentionally used it), I wouldn't completely blame llms either since languages like Go never had this dependency hell.
npm is a security nightmare not just because of npm the package manager, because the culture of the language rewards behavior such as "left-pad".
Instead of writing endless utilities for other project to re-use, write actual working things instead - that's where the value/fun is.
“A little copying is better than a little dependency.”
So if fewer people are including silly dependencies like isEven or leftPad, then I see that as a positive outcome.
Use of an AI to write your code is also a form of dependency. When the LLM spits out code and you just dump it in your project with limited vetting, that's not really that different from vendoring a dependency. It has a different set of risks, but it still has risks.
Why would you put uncopyrightable code into your codebase?
RyanHamilton•1h ago
zwnow•1h ago
phoronixrly•1h ago
Correction -- sadly, we're already well within this era
NitpickLawyer•1h ago
Slight pushback on this. The web has been spammed with subpar tutorials for ages now. The kind of medium "articles" that are nothing more than "getting started" steps + slop that got popular circa 2017-2019 is imo worse than the listy-boldy-emojy-filled articles that the LLMs come up with. So nothing gained, nothing lost imo. You still have to learn how to skim and get signals quickly.
I'd actually argue that now it's easier to winnow the slop. I can point my cc running in a devcontainer to a "tutorial" or lib / git repo and say something like "implement this as an example covering x and y, success condition is this and that, I want it to work like this, etc.", and come back and see if it works. It's like a litmus test of a tutorial/approach/repo. Can my cc understand it? Then it'll be worth my time looking into it. If it can't, well, find a different one.
I think we're seeing the "low hanging fruit" of slop right now, and there's an overcorrection of attitude against "AI". But I also see that I get more and more workflows working for me, more or less tailored, more or less adapted for me and my uses. That's cool. And it's powered by the same underlying tech.
NegativeK•1h ago
The problem is that AI makes all of that far, far easier.
Even using tooling to filter articles doesn't scale as slop grows to be a larger and larger percentage of content, and it means I'm going to have to consider prompt injections and running arbitrary code. All of this is a race to the bottom of suck.
AstroBen•42m ago
skydhash•20m ago