It’s National Junk Food Day!

As though the US needs an excuse to eat poorly.

Strange, I don’t think there is a Binge-Drinking Day—though many days in Wisconsin might qualify as honorary entries. Nor is there a Do-Controlled-Substances Day—though, admittedly, that one would be broad. I’m on prescription meds every day of the week. Sometimes when I write these blog posts, I wonder if they are really doing what they promise. And perhaps many of you, when reading my posts, also become paranoid. Apologies if so. Today’s post is a doozy…

As for junk food, my substances of choice are Kinnikinnick Vanilla-Frosted Gluten-Free Donuts. They come in a box of six, typically freezer-burned between the gluten-free lasagna that no one has bought in 11 years and the frozen tapioca bread that… well, no one has ever bought.

But these donuts—from Edmonton, Canada, nonetheless—sell fast, because they are as addictive as nicotine. My entire family concurs: these donuts are laced with something. Even completely frozen, I can gnaw through half a box in about two minutes and still be clawing at the back three like a rabid squirrel attacking acorns.

The downside? These things are kind of pricey. With inflation what it is, these small donuts come to about a buck-fifty each. And having grown up in the 1980s, when you could get a six-pack of Little Debbie Swiss Cake Rolls or Nutty Bars for 69 cents at the local convenience store, this seems outrageous to me. I sure as heck didn’t give up smoking in my early 20s to splurge $8 on donuts that last two minutes instead. By comparison, nicotine was an affordable habit… though I haven’t looked at the price of tobacco since 2005—in Hungary. Perhaps cigarettes cost more than $1.50 a pack now, too?

Alas… I guess what I’m getting at here is that I have had and continue to have vices. (I presume most people do.) I don’t drink. I don’t smoke. But I am an All-American junk-food eater. It is my weakness. My cultural shame. And I’m sure it will soon be my undoing, as my heart can’t take much more cheese, donuts, and ice cream. Nonetheless, if it’s true that people trade one addiction for another, I’m happy I landed on junk food. Because in America, eating processed food that’s bad for you is not only culturally acceptable, it’s celebrated with its own day! Hip-hip-hooray!!!

Wait… what is Halloween then, you ask? I can see a non-American’s confusion about this. However, that is definitely not an official junk-food day. That’s an annoy-every-person-on-your-block-and-consume-mass-quantities-of-candy day. Very different. That’s why we have both, I imagine.

Which raises the question: are there Fruit or Vegetable Days? I don’t know. I guess Ken and I will find out. Stay tuned.

It’s hard not to assume Junk Food Day was developed by some cabal of fast-food executives, soda companies, and chocolatiers—and I know, I know… I’m going to cut some of you off here. I’ve heard about those studies. “Dark chocolate is good for you,” some say, so I shouldn’t lump dark chocolatiers into this mix.

Whenever my kids tell me this bit about dark chocolate, I remind them about that infamous “Danish study” my Danish friend Klaus talked about nonstop during our senior year at Duluth East High School. He cited it like gospel. “Ian, a Danish study says…” And you can guess what a Danish study about beer consumption might have said in 1997: drinking three beers a day is really healthy!

Here is the funny thing, though. “Scientific research” says whatever the hell you want it to say if you stop following the research the moment you find a statistically significant result you want to hear. I didn’t know that then, so I couldn’t tell Klaus while huddled around a fire and drinking my third beer to my health. I get it now. Blasted… I later read an article disputing the Danish study completely. I should have stopped learning.

Which, of course, brings us to AI.

On LinkedIn, I keep seeing people post education studies showing that students who used AI in college last year are “dumber” than students who came before them. I’m paraphrasing, but not by much. The accompanying posts usually imply that humanity is losing its ability to think, civilization is nearing its intellectual terminus, and whither humanity if no one can read a passage of *Moby-Dick* and explain what drives Captain Ahab – or a fictitious whale.

The studies come fast and furiously out of education research centers right now because there is ample funding—and ample angst—around AI in education. AI is definitely going to flip traditional education on its head, or perhaps more likely, knock it on its ass. Some of the anxiety is warranted. Some students will absolutely use AI to avoid thinking. I avoided thinking with Cliff’s Notes, cooperative learning assignments, and by sitting near my smart friend Darren in grade school. In Hungary, my half the dorm spent three days creating cheat sheets and placing them in every conceivable place on their clothing, pens, etc. It was madness. They told me it was part of the academic process. Every generation develops its own technologies for intellectual evasion. Ours were simply less efficient and more analog.

But I keep seeing several different questions collapsed into one:

• Does AI help someone produce a better answer?
• Does using AI help that person learn?
• Can the person reproduce the result without AI?
• And is reproducing the result without AI still the ability that matters?

Those are not the same question. Not even close.

A student can produce better work with AI and learn very little. That is possible. In fact, a large high-school mathematics experiment found that students using unrestricted GPT assistance performed better during practice but could perform worse once the assistance disappeared. (Shocker!) Yet, a more carefully designed AI tutor reduced that problem. In other words, “AI harms learning” and “AI supports learning” can both be true, depending on what the tool does and how the student uses it. How terribly inconvenient for LinkedIn.

There is also evidence that generative AI can improve higher-order problem solving, and workplace studies have found substantial productivity gains—especially among less-experienced workers. That fascinates me. AI may not magically pour wisdom into everyone’s skull, but it can make some forms of hard-won expertise available to people who do not yet possess it. That is not the same thing as becoming educated. It is not the same thing as becoming intelligent, either. But it is not nothing. It may turn out to be economically enormous.

Education studies evaluate educational achievement. Intelligence research studies cognitive abilities. Workplace research evaluates performance and productivity. These things overlap, obviously. Education can strengthen cognitive abilities, and intelligence strongly influences educational achievement.

But educational achievement is not synonymous with intelligence. A decline in math or reading scores does not, by itself, prove that an entire generation has become less capable of reasoning, adapting, inventing, navigating social life, or solving problems with the technologies available to it. It proves that performance declined on the abilities being tested. That matters, but it is a narrower claim than the cultural obituary people like to write from it.

The more interesting question is whether we are measuring the abilities people will need next, or perhaps more aptly, the abilities institutions needed people to possess yesterday.

Shocker: replacing schools with hastily assembled Zoom links, parental panic, social isolation, and two years of Fortnite did not produce a pedagogical renaissance. Math and reading scores went down. But I remain curious: if we had also measured eye-hand coordination, rapid visual processing, group strategy in distributed environments, and the ability to pilot a drone with an Xbox controller, might some scores have gone up? I’m guessing yes. Why do we assume the skills schools already measure constitute the natural borders of human intelligence? With the rise of AI, they are far less likely to measure the skills today’s employers will be looking for.

As a daily mapmaker of products like the National Retainer Day Map, I know better than to mistaken the borders on a map for the borders of the world – particularly gnomonic-projected ones.

This is where the philosophy gets interesting – or perhaps unbearable – depending on your tolerance for philosophy in a post that began with frozen donuts.

Humans have always placed parts of our intelligence outside our bodies. Writing stores memory. Mathematics stores relationships. Libraries store collective knowledge. Maps store spatial reasoning. A map allows someone who has never stood on a mountain to understand the valleys around it, at least partially. No one looks at a map and says, “Well, this is disturbing. Humans will lose their innate ability to survey a continent personally.” The map is understood as an extension of cognition. It’s not proof that human spatial cognition has ended.

Socrates reportedly worried that writing would weaken memory and give people the appearance of wisdom without its substance. The annoying part is that he was right. Writing did weaken the need to memorize. (That’s why we aren’t reciting The Odyssey to one another but going to watch it in cinema.) But writing made philosophy, science, literature, law, and this unnecessarily long blog post possible. Technologies very rarely make us simply smarter or dumber. They redistribute our cognition. We stop doing some things, begin doing others, and then pretend the new current arrangement has been natural all along.

Every major technology of thought has allowed humans to forget something; it’s wonderful! We use the freed cognition to think about something else.

There is an old philosophical idea wrapped in the Greek word “pharmakon”: something can be both a remedy and a poison. The dose, context, and relationship matter. Junk food is not poison in the same way arsenic is poison. A donut does not destroy nutrition. A diet consisting entirely of frozen donuts, however delicious and economically ruinous, is another matter.

AI is probably a “pharmakon” too. It can be cognitive junk food: frictionless answers, consumed rapidly, providing the sensation of understanding without much intellectual nutrition. It can also be a kitchen, a tutor, a laboratory, a sparring partner, a drafting table, a coding collaborator, or access to expertise that a person previously could not afford. The fact that it can be abused tells us almost nothing about whether it should exist. Most useful technologies can be abused. Have you seen automobiles? Social media? Your fellow humans?

The question is not whether AI makes humanity smarter or dumber. The question is which forms of intelligence it amplifies, which abilities it allows us to neglect, and which neglected abilities will turn out to have mattered.

That last part is important. I am not arguing that knowledge is obsolete. You need enough understanding to recognize when a machine is feeding you nonsense. You need judgment. You need context. You need skepticism, curiosity, and some idea of what a good answer looks like to you. If anything, AI makes those abilities more important because it can produce incredibly incorrect answers that sound… well, educated.

Personally, I think formal education will lose its monopoly over expertise – at least partially. For generations, education served at least three roles: it helped people learn, certified that they had learned, and rationed access to professional opportunity (i.e., career). AI disrupts all three, but especially the rationing. When expertise can be called upon in seconds, knowing everything personally may become less valuable than knowing what to ask, what to distrust, what to combine, and what to do next.

That does not mean math no longer matters. It means the economic value of manually performing certain mathematical procedures declines. Calculators did not end mathematics; they changed which operations deserved human attention. Spreadsheets did not end accounting. GIS did not eliminate geography—though it did tick off a bunch of human geographers for quite a while. AI will likely do something similar at a much broader scale.

Will my daughters need calculus if they become engineers or work on global map projections like my friend Bojan? Probably. Will they need to execute every derivative by hand for months to prove they understand the concept? No. The durable ability may shift from successfully executing procedures to framing problems, selecting methods, inspecting results, and noticing when the answer violates reality. Iteration… collaborating with intelligent systems. That will be important.

Writing will change in much the same way. I find it hard to believe that most consequential final drafts will not involve AI within five years. I may have written my last book using the archaic method of organizing, drafting, and writing every word one after another myself. Am I sad about that? A little, perhaps – kind of like I miss making proportional symbols by hand in Macromedia FreeHand. I look back on it fondly. I enjoyed the craft. But I try not to confuse my affection for past techniques as proof that everyone must preserve the workflow forever.

Imagine if I had spoken this free-write into ChatGPT and asked it to organize my thoughts, check the claims, streamline the digressions, and make sure I didn’t offend anyone. You would probably be appreciative right now, and what I’m rambling about might make more sense. We would both win: I wouldn’t get cancelled, and you would be able to understand me. What’s not to love?!

Well… something might be lost. The rhythms might become too smooth, right? The jerkiness of driving a Chevy Sonic stick shift giving way to a VW Tiguan automatic. The weird connections might disappear. The machine could politely remove the frozen donut and Socrates references I added here, because they do not appear relevant to my – or its or our? – thesis. The resultant write-up may be clearer for you but worse in affect. In writing, efficiency is not the only value, and polish is not the same thing as meaning.

That is why human direction still matters.

What about coding? Many software engineers believe coding is indispensable, which is understandable because it pays their mortgages. But the history of higher-level programming occupies a mere blip in human history. It exists largely to let humans communicate instructions to computers without arranging ones and zeros personally, which would be a terrible way to spend a Thursday.

Now we can increasingly communicate with computers in natural language. Why will everyone continue choosing a syntax-strict artificial language when ordinary language can express the desired outcome? Perhaps coding, as most people currently practice it, was a transitional stage in our relationship with computers—the first date, as it were. We have now entered the deep-talking phase.

That does not mean software engineering disappears next Tuesday. Natural language is ambiguous. Machines misunderstand us. Systems still require architecture, testing, security, verification, maintenance, and people who understand the machinery beneath the charming conversational surface. But the balance is shifting from manually constructing every instruction toward directing, evaluating, and integrating machine-generated work. I see no persuasive reason to pretend otherwise because the old arrangement made expertise scarce and salaries high.

Some people would say the future I’m describing is dystopian and ridiculous. Maybe. Four years ago, I would have said what I’m saying now was pure bananas. But I no longer believe refusing the technology will preserve human intelligence. Humans are technological animals. Our intelligence does not exist separately from language, tools, symbols, institutions, and one another.

The serious risks are not that AI is unnatural. The serious risks are that a handful of companies may control our cognitive infrastructure; that systems reproduce bias and error at enormous scale; that people surrender judgment for convenience; that surveillance becomes ambient; and that productivity gains flow upward while displaced workers are told to learn prompt engineering. Those are political, economic, and ethical problems. “Ban the chatbot and make everyone write five-paragraph essays again” is not an adequate response to them.

Perhaps the reason many of us – including my entire family, except me – fear this future is that we grew up when humans had to accumulate education to become the experts who built technology. Expertise lived in people and institutions, and access was scarce. Now more of it can be summoned on command. That does not mean the machine contains all human intelligence or possesses wisdom. It means the practical boundary between “what I know” and “what I can competently accomplish with assistance” is becoming harder to locate.

And perhaps that boundary was never as firm as we imagined. How much of my intelligence resides in my brain, and how much resides in books, colleagues, software, databases, maps, search engines, and the accumulated work of people I will never meet? If you remove all external assistance, are you measuring my pure intelligence – or merely placing me in an artificial and rather pointless survival game?

That is why I encourage my daughters to use AI regularly. Not to avoid learning, but to learn how to work with it while they still have teachers and parents around to tell them when it is bullshitting. They are already smart, and they are doing well in school. Education will continue to matter, although perhaps less as a gatekeeping credential and more as a foundation for judgment. They may enter an economy that rewards them not only for what they know, but for the quality of the questions they ask, the problems they can frame, the tools they can direct, and the compassion they show toward people affected by their decisions.

I hope so, anyway. Their parents have made a living largely from education and expertise, and we may be quite worthless in the market by then if I’m right and the human-expertise job market starts downsizing. Every utopian forecast becomes more interesting when the author’s own paycheck is fed into it.

What a trip… from Junk Food Day to Danish beer studies, Socrates, the externalization of human cognition, and my optimistic – though some would be forgiven for thinking dystopian – thoughts about life with AI.

This whole essay is speculation written to intentionally disturb coming to any comfortable conclusions, including my own. I go where the evidence leads; I hope others do too. And I”m often wrong; I chose Microsoft Zune over iPod, for example.

Should writing everything manually in a word-processing app and high demand for coding boot camps come roaring back, I’ll concede that I was way off. I would even bet against it right now, but gambling is not one of my vices. I have to draw the line somewhere.

Did I digress…?

A daily map. Which one is it again? Oh yes! Junk food, naturally.

For today’s map, I created a bivariate map of the two places where I most often access my junk food: convenience stores and fast-food restaurants.

I also made it using a Macromedia Flash MX map-design schema. And, strangely enough, the map demonstrates the entire argument I have just dragged you through. (It’s weird that if you write long enough, and it hits 1:30 in the morning as it has here, your argument may just naturally come full-circle.)

Notice – which will be particularly hard to miss if you are red–green colorblind, I imagine – that the map uses red and green quite inappropriately. Not good. Horrible. And I realize this fact.

But I left it because the schema was accurately reproducing what many Flash maps did in the early 2000s. ColorBrewer had not yet appeared, or had just appeared, when I made my first Flash maps. Red and green were still frequently placed together. Red meant stop and green meant go, after all. It seemed intuitive to many designers at the turn of the millennium.

The AI followed the design schema I fed it. It reproduced the period accurately. And the result contains a poor accessibility decision.

That is the point!

Successful execution is not the same thing as a wise outcome. A system can follow its instructions perfectly and still produce something we should question. Prompt cartography supplies capability. The human mapmaker supplies – or ought to supply – judgment, context, responsibility, and the willingness to say, “Yes, that is historically accurate, but perhaps we should not do it.” (And of course, when someone tell me perhaps we shouldn’t do it, even myself, I tend to say: well, let’s see what happens if we do do it. I guess I can’t get enough null-hypothesis testing in my life.)

We have come a long way in twenty-some years – and over the 20 minutes you’ve been reading, perhaps). We will presumably look back at today’s AI products with the same combination of nostalgia, embarrassment, and disbelief. I hope we do. It will mean we kept learning.

Please use AI thoughtfully and eat junk food responsibly. There are children about!

Tomorrow is Rat Catcher Day.

God help us all. You can’t make these days up!

A Studies Fueling My Ramble

• Ritchie, Stuart J., and Elliot M. Tucker-Drob. “How Much Does Education Improve Intelligence? A Meta-Analysis.” Psychological Science, 2018.
• Bastani, Hamsa, et al. “Generative AI Without Guardrails Can Harm Learning.” Proceedings of the National Academy of Sciences, 2025.
• Brynjolfsson, Erik, Danielle Li, and Lindsey R. Raymond. “Generative AI at Work.” NBER Working Paper, 2023.
• Zhao, Yuting, et al. “Does Generative Artificial Intelligence Improve Students’ Higher-Order Thinking?” 2025.

View Map Here

Web Mapper Prompt (Link)

Attached files: Flash_2000_v2.json, census_dataset.csv (created with Spatial Data Doctor)

HI. Tuesday is National Junk Food Day in the USA! Woohoo!

I would love to create an interactive web map to celebrate this triumphant day.

I’m attaching a dataset showing how many fast food restaurants there are per 1000 residents by US county, as well as how many convenience stores per square mile or similar, I forget.

Can you create a multivariate map that shows both variables at the same time, please? When users hover over a county, or click, please have an info window show certain relevant statistics you find in the dataset about the county and state that it is in overall. Give the map a title that makes it sound serious: Junk Food Access by County, etc.

Exclude superfluous decision and methodology text from anywhere in the map except for a “?” Help and Attribution modal.

Oh, finally, I just created a super detailed new map design schema that I’d like to try out. Can you follow this schema to design the map overall. Please note that this should work on both desktop and smartphone devices, but how it is designed for both may vary significantly.

Thank you!

I’ve only had caviar a few times. I’m pretty sure the stuff that cost ~$3 in Hungary in 1994 wasn’t legit, but I’m counting it. It was delicious – though bright orange. It was some sort of egg. Maybe just eggs from the nyekladhaza tok where I frequently swam.

I had it at some party too. I forget where. But then someone mentioned whatever it was that they were serving was caviar, and like the time I couldn’t pass up eating free lobster at Larry’s 50th birthday party in Madison, I ran over there just to try it. And then consumed probably more than my share… It was good. It’s basically salt with a gelatinous texture and a hint of fish flavor, but… as you can already tell, there is a reason I’ll never be a food critic. (Speaking of which, perhaps, and just perhaps, food critic and taste-testing is one of the most stable professions to be in right now? It will take a while for a Tesla bot to outdo a human on that, I imagine. Then again, people like me think fish eggs are delicious – maybe we humans are the crazy ones?!)

I spent my teen years living on Lake Superior – literally, as in it was 20 meters across the street. My city decided to subsidize and build a giant freshwater aquarium celebrating Lake Superior and local fish – The Great Lakes Aquarium.

I don’t bring this up to imply that city planners and politicians trying to get reelected should never be allowed to make long-term public business decisions on behalf of the community – though I do mean that. Rather, even though everyone an aquarium showing trout and walleye that are in almost all 15,000+ lakes in Minnesota would not draw a crowd just because they added a large sturgeon to the tank, the mascot they created for the aquarium became one of my all-time favorites! If they had t-shirts with this mascot, I would buy five. (I tend to hoard clothing items I really like and worry I’ll never get replicas of. It’s weird!)

Alas, like a scene from a Robert Zemeckis movie, if he created Back to the Future, as I can’t be bothered to check my memory on this, the Surgeon General has been erased… from history! (In other words, I can’t be bothered to go look up the director of a movie, but I can spend an hour searching Google and Wikimedia for images from before the digital camera era of a person in a giant sturgeon costume dressed as a general. He has now become merely a mythical and legendary mascot even though I recall shaking the General’s hand one day at a community event. (Perhaps this is how UAP/UFO observers feel when no one believes them?)

Without further ado, a map for National Caviar Day – which I will note, seems somewhat strange, because I don’t think the market for caviar is huge in the US, and you might as well go all out with an international day, but whatever, maybe the former-Duluth mayor that thought it was a good idea to build a freshwater aquarium is now in charge of the US Caviar Lobby Group?

Happy National Caviar Day everyone! Long live the Sturgeon General!

P.S. I found a drawing of the Sturgeon General in an archived Lake Superior Magazine article, where the journalist actually sat down and interviewed the Sturgeon General himself. A fascinating read and look at 1990s, pre-internet marketing in many ways.

Article is linked here, but this is not the Sturgeon General I remember! This is a mere caricature of his greatness!

View map here

Web Mapper Prompt

Create an interactive web map titled **“Black Pearls: A Global Atlas of Caviar and Sturgeon.”**

The map should celebrate National Caviar Day while presenting caviar through four connected themes: geography, sturgeon biology, aquaculture, and conservation. The experience should feel luxurious and refined, but it must remain educational, scientifically responsible, and transparent about data quality.

### Core concept

Begin with a dark global perspective of the northern hemisphere showing major sturgeon rivers, inland seas, coastal habitats, aquaculture regions, and documented caviar-producing locations. Avoid making political boundaries the dominant visual element. Instead, emphasize river systems, watersheds, species ranges, and production geographies.

Continue reading →

I don’t like snakes. I have a (seemingly) primordial bias against them.

My dislike for them only increased when, as a child I stepped on a Gardner snake barefoot while playing tag in my yard. Not poisonous, but unexpected and creepy. (I imagine the snake enjoyed the run-in even less.) I still shriek whenever I see a Garner snake on my property, which is quite frequently, as I moved into a pine forest full of them.

I’ve always been fascinated by poisonous snakes, though, ever since seeing the movie, Raiders of the Lost Ark, and because where I grew up, we didn’t have anything “venomous” to speak of. Not even spiders.

I think that’s why snakes feel “more dangerous” than they probably really are. Bears, moose, and sometimes a random wolf or two were frequently in my yard growing up… (albeit a spruce forest then). Our crab apple tree tended to attract momma bears with young cubs every year. Made waiting for the school bus intriguing. But they were no problem. They were mammals. Our species’ cousins, if you will.

But poisonous snakes?! I felt so lucky I never had to deal with those.

Today, I decided to create a map of poisonous snake species around the world to celebrate a day that (inwardly) freaks me out – World Snake Day. Perhaps it will help me overcome my fear. (And yes, I know snakes are crucial for ecosystems. I still don’t like them.)

Animal range datasets are frequently murky. Also, the datasets aren’t generally easily or readily available or accurate for 60 different species around the world at once.

So today’s map was a two-part challenge for me.

The first: use Spatial Data Doctor GPT to find, collect, and trace different toxic snake species ranges anywhere it could find them. Naturally, I asked it to also return reliability scores based on how each feature was retrieved, its source, and the level of generalization the source had to begin with.

Simple. This was a much bigger ask than many other data retrievals I’ve done, because in some cases I believe it had to analyze print maps from open-access journal articles, etc., and then logically determine and trace those ranges.

Well done, Spatial Data Doctor GPT. Well done. This is my favorite GPT in the whole WebMapGPT suite. I don’t think many GIS companies have realized this yet, but there is absolutely little reason for a human cartographer in 2026 to ever visit a slow-loading, archaic GIS data portal again. That’s what LLM agents are for! Try it if you haven’t yet. It may just change your dataset creation life. Don’t forget to ask for a source and reliability score for each feature returned too and/or a provenance file. Particularly because the anti-LLM trolls are out there, and they are looking for prompt cartographers to strike. Beware of the trolls. They’re like… like… what we’re mapping today!

So where was I… yes, poisonous snakes!

I now had an epic dataset. So it was time to create a map. Alas… you may have heard, but over the past two weeks I’ve been creating a lot of stuff for other prompt cartographers. What drives me recently is helping more people develop prompt cartography workflows and become more proficient at the process. That’s my entire modus operandi right now. That’s why I started creating map design styles and schemas a couple of weeks ago.

On that front, I’ve also created a Map Design Lab at www.promptcartography.com that allows you to mix and mash up to four of these design schemas to create your own Franken-Design schema (or style genome) using what I am currently calling a Map DNA composite score. (I labeled the tool “beta” on purpose to reserve the right to change the subpar naming conventions I tend to come up with at one in the morning on a Monday).

So now we all have over 40 researched styles we can use, as well as a site where you can mix and match different styles together, add new colors, remove some palette colors, edit and tweak which fonts are used, etc. So the second goal of today’s map…

I wanted to use some new schemas and a Map Design Lab mash-up to make this map. I will show you three mash-up schemas below. All of them are based off of board game systems I own and love, because I haven’t had time to play many games recently.

In the end, I kept the the World War II Undaunted Normandy-inspired card game theme mixed with the classic Cassini French Cartography style. I just preferred the legend styling and map organization with on this one compared to the other outputs. It’s a map style mash-up! Cool!

You’ll noticed that the board game schemas aren’t posted anywhere online yet. There’s a reason for that. They were made with a new WebMapGPT agent I’ve built called Map Styler. These were the first design schemas I created with the actual GPT. They are prototype and QA outputs. The original design schemas were designed in a different place, not using a specialized GPT. I took what I learned from making those to create a GPT tool I can share with the world.

I will release Map Styler shortly – maybe tomorrow depending on how fried I am after work. It will allow you to write a simple prompt and create detailed design schemas (essentially what are used in the Map Design Lab) of your own.

For example, in the examples shown below, I asked the GPT to create schemes based off board games I was looking at on a cart in my garage. You can make design schema from almost anything – the backs of DVD covers work, Ravesnburger puzzle box layouts, Ikea furniture catalog designs… Yup, I’ve been playing around a lot. You can make some seriously cool designs by mixing them together!

And rest assured, the tool never copies any trademarked or copyrighted icons, logos, etc. It creates a map style scheme inspired by what you ask it to do research on – not copying directly. It’s amazing. It’s fun. And it just sped up the cartographic process significantly! Anyone who has played Bohnanza knows that the overly saturated yellow map with eye-burning red font is spot on. Design inspiration and mixing is merely a prompt away now. No coding required. No GUIs required. Just a half-decent prompt.

Map Styler will be announced on the WebMapGPT Blog soon. So if you’re interested, stay tuned.

But anyway… snakes! Blasted snakes! Yikes!

Today’s map shows where 60 of the world’s most toxic snakes live (roughly).

It’s interactive and designed for kids, parents, and people who randomly might Google or LLM “show me a map of the world’s most poisonous snakes please.” I’m sure this will land on the 47th page  of Google search, but it will be out there, in the wild.

Another prompt cartography artifact. Ta-da!

I hope you enjoy today’s map. It was fun to make. And I can’t wait to get to the next day, because snakes… yuck!

Bohnanza / Family Card-Inspired Game Mash Up Styled Map

Forest Shuffle Game / Cassini Map Mash Up
(Also inspired by Guillaume Touya and the very nice cheese-shop guy in Nantes 🙂

The Final Design Version
World War II / Undaunted-Card-Game-System-Inspired Mash Up Map

Pop-up style was designed in one-off prompt without me mentioning it at all, because the schema associated the card styles and layouts to map components.

View Map Here

Web Mapper Prompt (www.webmapgpt.com) Single Prompt for each style.

Please create a fun, educational map about snake ranges for World Snake Day. The audience should be targeted at school children who are fascinated by deadly snakes and may ask Google to find a map. (Add some SEO stuff to the metadata at top, please, about poisonous snake maps, ranges, interactive maps, reliable, etc..) I’m attaching a ton of information and data created by another GPT. Use the data that makes the most sense for the easiest, cleanest presentation on an apache website. There is a readme file that describes what the datasets are and what you can visualize. If there is data on number of deaths, etc., perhaps add proportional circles, etc. Otherwise, just ranges are fine. Perhaps take a look at the data and attached style schema before you begin and provide your best style and dsign suggestion. Thank you!