You know, Herman, I was trying to buy some new hiking boots online last night, and the experience was just... infuriating. I typed in waterproof leather boots, and the search results gave me everything from flip-flops to umbrellas. It was like the website had no idea what its own products were. I spent forty-five minutes clicking through filters that didn't work, only to find the boots I wanted listed under the category of casual footwear, but they didn't show up in the outdoor section. It is a classic example of a digital experience that looks beautiful on the surface but is completely hollow underneath.
Herman Poppleberry here. And Corn, what you just described is basically the modern digital version of a library with all the books thrown in a pile on the floor. It is a failure of taxonomy. And it is funny you mention that, because our housemate Daniel sent us a prompt this morning that dives right into the heart of that exact frustration. It is a topic that sounds dry when you say it at a dinner party, but it is actually the secret engine of the entire information age.
Oh, good timing, Daniel. I was definitely feeling the lack of order last night. It is one of those things you never think about until it breaks, right? We just assume the world is organized, but there is this massive, invisible architecture keeping everything in its place. When you can't find your boots, or a doctor can't find a patient record, or a researcher can't find a specific paper, you are bumping into the walls of a broken taxonomy.
Taxonomy is the unsung hero of the information age. People think it is just for librarians or biologists looking at beetles, but it is actually the logic gate for almost everything we do. If you can not name it and categorize it, you can not find it. And if you can not find it, it might as well not exist. We are talking about the difference between a pile of data and a body of knowledge.
That is a heavy thought to start with. If it is not in the system, it is gone. So today we are digging into the history of how humans have tried to organize everything. We are looking at the systems, the people who build them, and why this matters more than ever in the age of artificial intelligence. We are in March of twenty twenty-six, and even with the incredible power of the latest large language models, we are finding that the old rules of organization are more important than ever.
And I think we should start by clearing up some of the terminology, because people throw words around like taxonomy, ontology, and folksonomy as if they are interchangeable. They are not. They represent different philosophies of how we view the world.
Right, let’s set the stage. Most people know taxonomy as a tree, like the biological classification we learned in school. Kingdom, phylum, class, order, family, genus, species. It is very rigid. But how does that differ from an ontology?
Think of it this way. A taxonomy is a hierarchy. It is a tree. Everything has its one place. It is about parent-child relationships. A lion is a type of feline, which is a type of mammal. An ontology is more like a web or a graph. It defines the relationships between things across different categories. So, in a taxonomy, a lion is just a feline. In an ontology, you can define that a lion lives in the savanna, it eats zebras, it is a symbol of royalty, and it has a specific conservation status. It maps the complexity of the real world rather than just putting things in boxes. It allows for multiple inheritance and complex associations.
And then there is the folksonomy, which sounds like something you would find at a music festival.
In a way, it is! A folksonomy is just user-generated tagging. Think of hashtags on social media or the way people tag photos on Flickr back in the day. There is no central authority saying you must use this specific word. If you want to tag a photo of a sunset as "vibe" or "orange" or "Tuesday," you can. It is messy, it is bottom-up, and it is chaotic. It is the opposite of a controlled vocabulary. It is great for discovery and trends, but it is terrible for precision.
Which brings up a great question. We live in twenty twenty-six. We have massive large language models that can seemingly understand any prompt we throw at them. They can find patterns in unstructured text that would take a human a lifetime to see. Is taxonomy a dead art? Do we still need to build these rigid maps if the artificial intelligence can just find the patterns on its own?
That is the big misconception right now. People think the artificial intelligence is magic. But here is the thing: if you want an artificial intelligence to be reliable, especially in a professional, legal, or medical setting, you need what we call R-A-G, or retrieval-augmented generation. And for R-A-G to work, your data needs to be structured. You need a map. Without a taxonomy, the artificial intelligence is just guessing based on probability. It is hallucinating connections that might not be there because it doesn't have a ground truth to anchor to.
So the artificial intelligence is the engine, but the taxonomy is the tracks it runs on. If the tracks are broken, the train goes off the rails, even if it has a thousand horsepower.
Beautifully put. And we have been building these tracks for a long time. If we want to understand where we are going, we have to look at where this all started. And you really can not talk about human order without talking about Melvil Dewey.
Ah, the Dewey Decimal System. I remember those little cards in the library when we were kids. It felt like a secret code. But I didn't realize how revolutionary it was at the time.
It was a total paradigm shift! Before eighteen seventy-six, libraries were a mess. Books were often shelved by "fixed location." That meant they were shelved by the order they were purchased, or even by the color of their spine or their size to make the shelves look nice. If a library got a new book on astronomy, they just put it at the end of the shelf, next to a cookbook or a biography. There was no "relative location."
Wait, so if you wanted to find all the books on astronomy, you had to look through the whole building? Or just hope the librarian had a good memory?
Pretty much. You had to rely on the memory of the librarian or a very cumbersome ledger. Melvil Dewey changed everything when he published his system in eighteen seventy-six. Interestingly, the original pamphlet was only forty-four pages long. But he introduced this idea of a universal decimal system where every subject had a number. He divided all knowledge into ten main groups, from zero hundred to nine hundred.
It was essentially the first A-P-I for human knowledge. A standardized way for any library to talk to any other library.
Precisely. It allowed for "relative location." You could add new books to a category and the system would just expand. If you had a book on the moon at five twenty-three point three, and you got a new one, it went right next to it. It was brilliant, though it definitely reflected the biases of the nineteenth century. For example, in the original Dewey system, almost all the space for religion—the two hundreds—was dedicated to Christianity, while every other religion in the world was crammed into a single sub-category, the two nineties.
That is a great point about the "worldview" of a taxonomy. When you build a system of classification, you are not just organizing the world; you are deciding what is important and what is secondary. We talked about this a bit in episode eight hundred sixteen, when we looked at how we moved from scrolls to modern databases. The way you categorize things reveals your priorities. It is an act of editorial judgment disguised as science.
It really does. And that is why standardization became such a huge deal in the twentieth century. We realized that if everyone has their own private taxonomy, we can not share data. If my "astronomy" is your "stargazing," our computers can't talk. That is where organizations like the I-S-O, the International Organization for Standardization, come in.
I wanted to ask you about that. Most people hear I-S-O and think of camera settings or shipping containers. But they have a massive role in how we organize information, right?
Oh, they are the giants in this space. Specifically, I-S-O twenty-five nine sixty-four. That is the international standard for thesauri and interoperability between information systems. It was finalized in two parts between twenty-eleven and twenty-thirteen. It sounds dry, but it is the reason a medical database in Jerusalem can talk to a research database in Washington, D.C. It provides the rules for how to build a "thesaurus" in the technical sense—not just a book of synonyms, but a structured vocabulary of preferred terms.
So it is about creating a "controlled vocabulary." Tell me more about why that matters. Why can’t we just use whatever words we want? We have search engines that can handle synonyms.
Because language is slippery. Think about the word "lead." L-E-A-D. Are we talking about the metal? Or are we talking about a sales lead in a marketing database? Or are we talking about the lead singer of a band? Or the verb "to lead"? Without a controlled vocabulary and a proper taxonomy, a search engine is going to give you all four. A controlled vocabulary ensures that everyone agrees on what a term means in a specific context. It uses "scope notes" to define the boundaries of a word.
It prevents what you call "semantic drift," where the meaning of a category starts to change over time as different people use it.
And maintaining that is a full-time job. This is not a "set it and forget it" situation. The world changes. New diseases are discovered, new technologies are invented, and social norms shift. If your taxonomy doesn't evolve, it becomes a prison for your data. You end up with "legacy debt" where you are trying to describe a twenty twenty-six smartphone using categories designed for a nineteen ninety-five landline.
That leads us perfectly into the professional landscape. Who are the people actually doing this work? I think most people assume it is just a side task for a software engineer or a librarian, but there is a whole career path here. You don't just stumble into being a taxonomist.
There is. You have professional taxonomists and information architects. And while they work closely together, they are not the same thing. In the last five years, with the rise of data science, these roles have become incredibly high-paying and high-stakes.
What is the distinction? How would you explain the difference to someone who is looking to hire for a product team?
I like to use the analogy of a building. The taxonomist is the one who designs the structural integrity and the storage system. They are looking at the "what." What is this piece of data? Where does it belong in the master list? What are its attributes? They build the "spine" of the organization. They are worried about the logic and the hierarchy.
And the information architect?
They are more focused on the "how." How does a human being move through this information? They design the navigation, the search filters, the labels on the buttons, and the user flow. They take the taxonomy and turn it into a usable interface. The taxonomist builds the warehouse and the shelving units; the information architect builds the shopping experience and the signs that tell you where the milk is.
That makes total sense. I’ve seen so many websites where the navigation is great—the buttons are pretty, the flow is smooth—but the actual categories are a mess. You can click through the menus perfectly, but you still end up with the wrong products because the underlying tags are wrong. That is a case where the information architecture is good, but the underlying taxonomy is broken.
Or vice versa! You can have a perfect, scientifically accurate taxonomy that is absolutely impossible for a normal human to navigate because it is too complex. If you have to know the Latin name of a plant just to find a bag of potting soil, the taxonomy is great but the information architecture has failed. You need both. And interestingly, these professionals are everywhere now. It is not just libraries.
Where are they hiding? Give me some examples of industries where a taxonomist is a "must-hire."
Big retail is a massive employer. Think about a company like Amazon or Walmart. They have millions of products. If their taxonomy is off by even a little bit, they lose millions of dollars in sales because people can not find what they are looking for. If a "power drill" isn't tagged as both a "tool" and "home improvement," you lose half your customers. But you also find them in pharmaceuticals, where they have to manage thousands of chemical compounds, clinical trial results, and regulatory filings.
And the stakes there are much higher than just missing out on a pair of hiking boots.
We covered this in episode eight hundred, talking about medical data. If a doctor uses a different term for a symptom than the research database uses, a life-saving connection might never be made. In medicine, taxonomy is literally a matter of life and death. The I-C-D-eleven, the International Classification of Diseases, is one of the most complex taxonomies in existence. It has over seventeen thousand unique codes. If a coder gets it wrong, the insurance doesn't pay, the treatment is tracked incorrectly, and the global health statistics are skewed.
It is the invisible layer. We don't see the taxonomist working in the background to reconcile synonyms and manage edge cases, but we feel it when they aren't there. It is like the plumbing in a house. You only notice it when the pipes burst.
And the workload is staggering. Think about the "maintenance debt" of a system like the Library of Congress Subject Headings. It is a living, breathing taxonomy that has been around for over a century. Every time a new concept enters the cultural lexicon—like "cryptocurrency" or "generative artificial intelligence"—they have to decide where it fits. Does it go under "Economics"? "Computer Science"? "Art"? And they are notoriously slow because they have to be sure. They can't just jump on every trend.
I imagine there is a lot of tension there between being "accurate" and being "current." If you change your categories too fast, you break all your old records and your search history. If you change them too slow, you become irrelevant and people can't find modern topics.
That is the "Taxonomy Maintenance" problem. In the corporate world, this is a nightmare. Imagine you are a major retailer and you decide to split the "Electronics" category into "Mobile" and "Home Audio." You have to re-tag hundreds of thousands of legacy items without breaking the search filters for your customers who are still using the old site. It is like trying to change the tires on a car while it is going sixty miles an hour down the highway.
It sounds like a lot of manual labor. Is there any way to automate this in twenty twenty-six, or are we always going to need humans in the loop?
We are seeing more automated tagging tools, especially using vector embeddings, but they still need a human to define the "ground truth." An artificial intelligence can identify that two things are similar, but it can't always tell you "why" they should be grouped together for a specific business purpose. You still need that human judgment to say, "In our context, these two things belong together because of a legal requirement, even if they look different."
This brings us back to the societal impact. Taxonomy isn't just about business efficiency; it is about how we perceive reality. Think about something like the census or medical coding. The categories we choose for those systems literally define who gets funding, who gets treatment, and how we see ourselves as a society.
You are hitting on a very important point, Corn. Classification is an act of power. When the government decides on census categories, they are drawing lines around groups of people. If your identity doesn't fit into one of those boxes, you are effectively invisible to the state. You don't get the resources or the representation. This is why there is often so much political debate around how we categorize people. It is not just about data; it is about existence.
And from our perspective, as people who value clear definitions and objective truth, this is where it gets tricky. You want a system that is accurate and reflects reality, but you also have to acknowledge that reality is complex and doesn't always want to stay in its box. The world is often more of an ontology than a taxonomy.
And as conservatives, we often appreciate the value of established, traditional structures. There is a reason the Dewey Decimal System has lasted so long. It provides a stable foundation that allows knowledge to be passed down. But we also have to be honest when those structures no longer serve the purpose of clarity. The goal should always be the most accurate representation of the truth, even if that means updating the categories to reflect new discoveries.
Right, it is about maintaining the integrity of the information. If the categories become so outdated that they start obscuring the truth rather than revealing it, then the system has failed. It is like the "ancient backups" we discussed in episode ten thirty-two. If you can't read the data because the filing system is obsolete, the data is lost.
So, let’s talk practically. If someone is listening to this and they are running a business or a project, and they realize their "tags" have become a meaningless mess... what do they do? How do you start fixing the "invisible layer"?
The first step is usually a "metadata audit." You have to look at what you actually have. Most companies find that they have fifteen different tags for the same thing because they let everyone create their own. One person tagged it "cell phone," another tagged it "mobile," and another tagged it "smartphone." You have to consolidate those into a single "preferred term."
That is the folksonomy problem we mentioned earlier. It is fine for social media, but it is a disaster for a database. You need a "synonym ring" where all those terms point to one master ID.
So the takeaway is: move toward a controlled vocabulary. Pick one term, define it, and stick to it. And if you are building something complex, don't wait until you have ten thousand items to think about taxonomy. Do it when you have ten. It is much easier to grow a tree than to untangle a forest.
And don't be afraid to hire a professional. If you are building a serious data product or an artificial intelligence application, a taxonomist is just as important as a lead developer. They are the ones who ensure your data has a future. Especially now, with the move toward these graph-based knowledge systems we discussed in episode four ninety-two. The architecture of your information is your most valuable asset.
I think that is a great point to lean into as we look toward the future. We are moving away from that "filing cabinet" model of folders inside folders and moving toward these rich, interconnected webs of data. But even in a web, you need to know what the nodes are.
We are. And that is where the real "aha moment" happens. When you have a solid taxonomy, you can start to see connections you never would have noticed otherwise. You can see how a specific manufacturing process in one factory is related to a quality control issue in a completely different product line three years later. The taxonomy provides the "connective tissue" that allows for deep analysis.
It is the difference between having a pile of bricks and having a building. The bricks are the data, but the taxonomy is the blueprint that tells you how they all fit together to create something functional. Without the blueprint, you just have a very heavy pile of clay.
I love that. And we have to remember that order is not a natural state. Entropy is the natural state. Things want to fall apart. Information wants to become disorganized. Language wants to drift. Taxonomy is a constant, deliberate human act of resistance against that chaos. It is a way of saying, "This matters, and this is what it is called."
It is a very human endeavor, isn't it? This desire to name things, to categorize them, to find our place in the universe. It goes all the way back to the beginning of history, from Aristotle classifying animals to the modern developer building a schema.
It really does. Whether it is Aristotle or a developer in Tel Aviv building a new schema for a medical artificial intelligence, we are all doing the same thing. We are trying to make the world understandable. We are trying to build a shared reality.
Well, I think I have a much better appreciation for why my boot search failed now. It wasn't just a glitch; it was a fundamental breakdown of the invisible architecture. Someone, somewhere, didn't do the work of maintaining the taxonomy.
Next time you are on a site like that, just think about the poor taxonomist who is probably screaming into their coffee because the marketing department decided to ignore the controlled vocabulary for a "flashy" new campaign.
"But it's a lifestyle product, not a boot!"
And that is how the metadata dies. One "lifestyle product" at a time.
Before we wrap up, I want to remind everyone that if you are interested in how we used to do this in the past, go back and listen to episode eight hundred sixteen. It gives a lot of great context on the evolution from physical scrolls to S-Q-L databases. It really sets the stage for what we talked about today.
And if you are into the more technical side of how this works in healthcare, episode eight hundred is a must-listen. It really shows the high stakes of what we are talking about today. It is not just about shopping; it is about survival.
This has been a fascinating deep dive. I think we often take for granted how much work goes into making the world "searchable." We just expect the box to give us the answer, but there are thousands of people making sure that answer is actually correct.
It is the work of thousands of people whose names we will never know, keeping the lights on in the giant library of human knowledge. They are the guardians of the "Invisible Layer."
Well, thanks to Daniel for sending this in. It definitely gave me a lot to think about next time I am browsing the web. And hey, if you have been enjoying the show, we’d really appreciate it if you could leave us a review on your favorite podcast app. It genuinely helps other people find the show and join the conversation.
Yeah, it makes a big difference. We love seeing the community grow. You can find all of our past episodes—all one thousand and twenty-one of them now—at our website, myweirdprompts dot com. There is a search bar there, and I promise, the taxonomy is actually pretty good. We spent a lot of time on it.
We try our best! You can also find us on Spotify and subscribe to the R-S-S feed if you want to make sure you never miss an episode.
Alright, I think that covers it for today. From our home in Jerusalem to wherever you are listening, thanks for joining us.
This has been My Weird Prompts. We will see you next time.
Until then, keep your metadata clean and your hierarchies logical.
I was going to say "stay curious," but I like yours better.
Why not both? Stay curious and keep your metadata clean.
Fair enough. Goodbye, everyone.
Bye for now.
You know, Herman, thinking about the Dewey system, I wonder what number this podcast would fall under.
Oh, that is a good one. Probably zero zero six point seven for multimedia systems, or maybe zero zero one point nine for controversial knowledge.
Controversial? I like to think of us as "thoughtfully provocative."
That is the "Corn and Herman" sub-category. We are an edge case in the taxonomy of podcasts.
We need our own decimal point. Zero zero one point nine point Poppleberry.
I will get the I-S-O to start working on that immediately. I'll send them a forty-four page pamphlet.
Good luck with that. I hear they are quite fast.
Only about twenty years per update. We will be in our eighties by the time they approve the "Poppleberry" tag.
Something to look forward to. Alright, let’s go get some lunch. I am starving.
Me too. I wonder if the kitchen is organized by a proper taxonomy.
It is mostly just "Corn's snacks" and "everything else." It is a very simple hierarchy.
That is a very biased system, brother. It lacks interoperability.
But it works for me.
We will have to audit that later.
Looking forward to it. Thanks for listening, everyone.
See ya.
So, Herman, before we truly sign off, I was thinking about the "Invisible Layer" one more time. You mentioned "maintenance debt" in corporate taxonomies. Is that why so many legacy systems in government or banking feel so clunky? Is it just that the taxonomy is fifty years old and nobody wants to touch it?
That is exactly it. It is the "too big to fail" problem of information. If you change the way a bank categorizes transactions, you might accidentally break the logic that calculates interest rates for millions of people. So they just keep layering new categories on top of the old ones, like archaeological strata. You end up with this digital "City of David" where the modern stuff is built on top of things from the nineteen seventies. You have modern web interfaces talking to S-Q-L databases that are still using codes from the C-O-B-O-L era.
That is a vivid image. You are digging through the database and you suddenly hit a layer of C-O-B-O-L and seventy-year-old classification logic. It is like digital archaeology.
It happens more than you think. There is a reason why "digital transformation" is such a massive industry. It is mostly just people trying to excavate and modernize these old taxonomies without the whole building collapsing. It is about mapping the old world to the new one.
It makes you realize that the work we do today—the way we tag our files, the way we name our variables, the way we structure our data—it is a gift or a curse to the people who will be sitting in our chairs forty years from now. We are building the foundations they will have to live with.
We are the ancestors of the future’s data. Let’s try to be good ones. Let's leave them a clean map.
On that note, I think we have truly exhausted the topic.
For now! There is always more to categorize. The universe is a big place.
Don't I know it. Alright, let's actually go eat.
Lead the way.
Or should I say... "lead" the way? The metal or the action?
Oh, stop it. You are causing semantic drift in the hallway.
Guilty as charged. Bye everyone.
Goodbye.
