I want to argue that AI models will write good code because of economic incentives. Good code is cheaper to generate and maintain. Competition is high between the AI models right now, and the ones that win will help developers ship reliable features fastest, which requires simple, maintainable code. Good code will prevail, not only because we want it to (though we do!), but because economic forces demand it. Markets will not reward slop in coding, in the long-term.

— Soohoon Choi, Slop Is Not Necessarily The Future

Tags: slop, ai-assisted-programming, generative-ai, agentic-engineering, ai, llms

Idea

One of the most common worries I hear from parents and see on online forums is:

“My kid didn’t fully understand this concept. Should we slow down? Should I be worried?”

The truth:

• Understanding in math almost never happens the first time or second time.

In fact, many mathematicians would say it takes three to five exposures to really understand something.

• The first time: you get the shape of the idea

• The second time: you notice what you missed

• The third time: it starts to click

• The fourth and fifth time: you can actually use it

So if your kid does not fully understand a concept the first time they see it, that’s not a problem.

It’s natural and expected.

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This is not a flaw in your child, nor is it a flaw in the material.

It’s just how learning math works.

Even if they are a “math-y” kid.

Story

There’s a wonderful (and very human) story about two famous mathematicians: Hermann Weyl and David Hilbert.

Hermann Weyl and David Hilbert are discussing this very topic.

For some context, a quick snapshot of their background.

Hermann Weyl was a German mathematician whose research was in theoretical physics and number theory, and he had been described as one of the “last great universal mathematicians of the nineteenth century.”

David Hilbert was a German mathematician described as “one of the most influential mathematicians of his time,” and in 1900 presented a collection of 23 problems known as “Hilbert’s problems” that have helped drive mathematical research ever since (note: many of them are still unsolved!).

Weyl asked Hilbert:

“How many times do you have to explain something to your students before they understand it?”

Hilbert replied:

“Five times, Hermann, five times. But for very talented students like you, three times is enough.”

Even among the greatest mathematicians, understanding wasn’t expected to happen instantly.

It took repetition.

Personal Example

A few months ago, one of my kids was learning a new concept in geometry.

They followed the lesson and could do some of the homework.

But there were some problems they couldn’t solve because they couldn’t quite grasp how the lesson topic related to the problem.

Instead of stopping everything, we kept going.

As a rule of thumb, if they’re getting about 60–80% of the material, we move forward, trusting we’ll see it again.

A week later, the same idea showed up again, only this time inside a new type of problem.

And suddenly:

“Ohhh… that’s why we did that.”

The problems that once felt impossible became solvable (and were!).

This has happened to us so many times that we now expect it to happen

Which is why we don’t aim for 100% mastery the first time.

Getting to 100% is nearly impossible the first (or even second) time, so we keep going, knowing eventually they’ll get it.

Each time they revisit the concept, their understanding deepens, not because they stayed longer, but because they saw it from a new angle.

What at first looked like confusion was actually the beginning of understanding.

Why it matters

If we expect children to “get it” the first time, two things happen:

1. Kids feel like they’re failing when they’re not

2. Parents feel like they need to intervene too early

Real understanding of math is layered and takes time.

This is why many math curricula (even traditional ones) are designed to spiral:

• Concepts come back again and again

• Each time with slightly more depth

• Each time making more sense

• With space in between, so the idea feels “new” again

There’s also another important piece:

Sometimes a child doesn’t understand something because they don’t yet see why they need it.

For example, many students struggle with high school algebra, not because algebra is too hard, but because they haven’t yet seen why it matters.

Then they encounter calculus or physics, and suddenly those same algebra rules become essential.

When I’ve spoken with (high school and college) calculus teachers, they often say:

It’s not the calculus that students struggle with; it’s the algebra.

In many cases, a student’s real understanding of algebra arrives during calculus.

There’s even a saying:

“You don’t understand a class until you’ve taken the class that depends on it.”

That is, understanding often arises when the context for why and how it’s used emerges.

Practical tip

Instead of asking:

“Do they fully understand this?”

Try asking:

“Have they seen this enough times to be familiar with it?”

And if they haven’t seen it enough times, you don’t need to:

• re-teach everything

• slow everything down

• or find the “perfect” explanation

You can simply:

• Keep moving forward

• Mark the concept mentally (“we’ll see this again”)

• Revisit it later from a different source

One of the advantages of learning today is that “another source” is easy to find:

• a different book

• a YouTube video

• a new type of problem

• or even explaining it to someone else

Different explanations unlock different insights.

Takeaway

Your child does not need to understand a concept the first time they see it.

They need to see it multiple times, in multiple ways, over time.

The key to getting good at math is to keep doing math.

So if frustration creeps in (for them or for you(!)), take a breath and keep going.

That’s how deep understanding is built.

How to practice

Try this small shift the next time your kid says:

“I don’t get this.”

Say:

“That’s okay. You might not have seen it enough times yet.”

Then:

• Let them try a few problems

• Move on if needed

• Revisit the idea later in the week

You can even make it explicit:

“You’re going to have to see this idea a few more times before it clicks.”

Over time, your child will internalize the incredibly powerful lesson:

• Understanding is a process that happens over time

Really, truly believing this lesson will help them not only in math, but in anything else they choose to learn.

That’s all for today :) For more Kids Who Love Math treats, check out our archives.

Stay Mathy!

Talk soon,
Sebastian

There’s a reason it’s a popular aphorism

The post The Students Who Believe Practice Makes Perfect Get Pretty Perfect Grades appeared first on Nautilus.

I keep a folder in Apple Notes called “cursed websites,” where I save various artefacts that make me feel like the social contract has dissolved. Call it an act of self-loathing. Call it collecting evidence of the fall. Dansugc.com went straight into the folder this morning.

It’s a site where marketers // entrepreneurs (and I find the line between those two groups has become blurred to the point of being illegible) can buy pre-recorded “Reaction” videos for $3 apiece. You browse a library of 2k clips, sorted by emotion (shocked! Happy! Crying! Excitement!), pick a face you find particularly appealing, download a 5-10 second clip of a stranger performing surprise // delight at nothing in particular, and splice it int your own content. The idea is to make it look like an actual someone had an actual emotional response to your app on TikTok. Custom orders run to $8 and let you specify outfits, emotional arcs etc.

The tagline reads: “100% Real Humans. Zero AI.”

And I think that tells you almost everything you need to know about where we are. And where we are is a place where “at least the fake fuckery was produced by a biological organism” counts as a premium feature. The pitch for selling manufactured authenticity at scale is that at leas the people in the factory are still real people. That’s the floor. That’s what passes for premium. We are drowning in content that is functionally the same as so many designer handbags stitched up alongside so many dupes.

The internet is the most powerful communication technology in human history, and we’re using it to sell each other $3 clips of faked surprise.

I don’t blame Dan, if that’s even his real name. He’s running a business filling a niche. He’s recognised that the entire internet advertising “ecosystem” now runs on simulated, casual, spontaneous “cool girl” energy. He’s simply the shovel-seller in an authenticity gold rush; except the gold is par asocial trust, and the shovels are clips of various women pretending to have their minds blown by your calorie-counting app.

100, ready to post UGC videos per month costs $800. A fully managed campaign for 500 videos goes for $10k. Dan claims over 5 billion total views generated, and I don’t doubt his numbers at all. But if this stuff doesn’t set off your alarms, even a little, you’ve probably been marinating in it so long you’ve lost the ability to smell it.

What Dan’s business lays bare - if you actually sit with it - is that the internet, as a social and cultural space is almost entirely performance. The whole apparatus has been hollowed into a content mill that grinds human attention into micro-conversions. I’m aware that I’m not the first person to make the complaint that the internet sucks - but every point of suck has now compounded into the final boss of shitty experiences. The algorithmic timelines, the social media homogeneity, the death of truth, the proliferation of monetisation strategies and side hustles etc have all contributed to this moment: a growth hacked, engagement optimised, brand-building logic that has destroyed our ability to distinguish between a person sharing something they give a shit about, and a person executing a “content” strategy.

Open TikTok right now and ~try to find a video that isn’t, at some level, trying to sell you something. A political identity, a digital product, a lifestyle, a personal brand. It's next to impossible. Every piece of content carries this faint whiff of ~strategy behind it. The girl doing a “Get Ready With Me” video has an affiliate link in her bio, and the asshole ranting about immigration has a Substack he can’t wait to funnel you to. The therapist explaining attachment styles is, naturally, building a course she’ll launch next month, and the couple doing a “day in our van-life” vlog is negotiating a brand deal in their DMs. There is always a funnel, always a CTA, and the output, no matter how “down to earth” it’s designed to feel, is always doubling as a mechanism to convert your attention into revenue.

Jean Baudrillard (read Simulacra and Simulation) identified how modern society replaces reality with the symbols and signs of reality. He mapped the process in four stages: first the image reflects reality, then it masks reality, then it masks the absence of reality, and finally it has no relation to reality whatsoever. A UGC reaction video purchased for $3 and spliced into a TikTok ad is operating at that fourth stage, because the reaction doesn't reference a real reaction, there was never a real reaction, and the whole thing is a sign pointing at nothing, wearing the costume of spontaneity.

You might say who cares, advertising has always been manipulative, and sure, that's true. When Grigory Potemkin allegedly erected fake village facades along the Dnieper River in 1787 to impress Empress Catherine II during her tour of Crimea, he was doing UGC marketing for the Russian Empire (the historical consensus is that the villages were probably real settlements that had been tidied up rather than total fabrications, but the legend stuck because the concept is so useful as shorthand). The instinct to manufacture the appearance of prosperity for the benefit of powerful onlookers is old as dirt. What's different now is the scale and the fact that regular people are doing it to each other all day long, voluntarily, for free or for pennies.

There's a phrase you hear in marketing: "everyone is a creator now." It sounds democratizing, hopeful even, like the whole internet has become a Renaissance workshop where artisans and thinkers reach audiences directly. In practice, everyone is a marketer now. The "creator economy" turned out to be an economy where the thing being created, more and more, is demand for more of yourself. Your aesthetic, your opinions, your morning routine, your trauma, your fitness journey, your face: all raw material for the content machine, all measured against growth metrics that would make a mid-career product manager feel right at home.

The result is an internet that feels, to use a technical term, like shit. Scroll any platform and you're wading through a river of optimized slop, and what makes it depressing is how same-y it all is despite the theoretically infinite diversity of human expression available online.

Political content looks like beauty content and beauty content looks like finance content and finance content looks like fitness content, because they’re all using the same hooks and they’re all built on the same emotional beats. The provocative claim in the first 2 seconds, the false tension, the extreme language, comment if you agree, like and subscribe and so on and on. Don’t forget to share this with someone who ~needs to hear this. Make sure you follow for part 2. The playbook is identical, whether someone’s raving about the best skin serum, or about their least favourite ethnic groups...

AI makes all of this both worse and darkly funny at the same time. AI slop and human slop have now converged to the point that Dan can credibly market “zero AI” as a premium feature, while his customers’ output offers no real elevation from the realm of deepfakes. And as much as Real Humans is a selling point for the internet today, the AI is getting better, too. It can produce damn-near the same hooks, the same engagement-bait captains, the same dead-eyed reaction that a human can churn out today. AI content creators aren’t even poisoning the well; not really. They’re simply drawing from a well we already puked in years ago.

AI slop is human slop with the labor costs removed, and that's why nobody can tell the difference, and that's why Dan has to specify that his product is made by real humans, like a carton of eggs stamped "cage-free."

There's a moment in Don DeLillo's White Noise where a character visits "The Most Photographed Barn in America" and realizes that nobody can actually see the barn anymore because the barn has been completely replaced by the aura of the photographs of the barn. Once you've seen the signs about the barn, he says, it becomes impossible to see the barn. The internet has done this to basically everything. You scroll past enough UGC reaction videos and you can't encounter a real reaction without wondering if it's bought, you read enough performative vulnerability posts and you can't encounter real vulnerability without suspecting it's a hook. The constant presence of the fake thing corrodes your ability to trust the real thing, and the really vicious part is that a lot of the "real things" were fake too, which means the thing you're mourning the loss of may never have existed in the form you remember it.

This is, I suspect, why nostalgia for "the old internet" has become its own genre of content (which is, of course, itself being optimized for engagement, because there's no exit door). People remember a time when someone's blog was their blog and nothing more, when a forum post was written because a person had a thing to say and they said it and moved on. Whether that era was actually as good as we remember is debatable, and I think there's a strong case that we're romanticizing it. Sturgeon's Law applied then too: 90% of everything was crap. But the crap was sincere crap. The crap was some guy with a Blogspot writing 3,000 words about his favorite Star Trek episodes because he liked Star Trek and had opinions about the Borg, with zero intention of building an audience or selling a course called "How I Built a 6-Figure Blog About Star Trek."

With ever increasing sizes of various programs (video games being notorious for this), the question of size optimization comes up more and more often. [Nathan Otterness] shows us how it’s done by minifying a Linux “Hello, World!” program to the extreme.

A naive attempt at a minimal hello world in C might land you somewhere about 12-15Kb, but [Nathan] can do much better. He starts by writing everything in assembly, using Linux system calls. This initial version without optimization is 383 bytes. The first major thing to go is the section headers; they are not needed to actually run the program. Now he’s down to 173 bytes. And this is without any shenanigans!

The first shenanigans are extreme code size optimizations: by selecting instructions carefully (and in a way a C compiler never would), he shaves another 16 bytes off. But the real shenanigans begin when he starts looking for spaces in the ELF header that he can clobber while the program is still accepted by Linux: now he can move his already tiny x86_64 code into these “vacant” spaces in the ELF and program headers for a final tiny ELF file weighing in at just 120 bytes.

P.S.: We know it is possible to make this smaller, but leave this as an exercise to the viewer.

The past, present, and future of academic deception

The post A Very Unscientific History of Scientific Hoaxes appeared first on Nautilus.