A Model of the Thing Is Not the Thing
Ford sculpts its cars in clay, draws them in CAD, and hired about 300 veterans to retrain its AI. All three are models, and a model of the thing is not the thing.
AI & Machine Learning
Artificial intelligence, machine learning, and neural networks
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A Stranger's LinkedIn Bio Sent Me to Hegel, and I'm Still Lost
A line in a stranger's bio sent me into a conversation about Hegel and Kant. The plain-English answer was accurate and I still couldn't follow it. The fix is the same one that teaches languages.
Your AI Can't Check Anything You Tell It. Here's How Guardrails Work
A model remembers nothing between sessions and cannot verify a word you say. The published rulebooks say more than the behavior does, and most workarounds are boring.
There's No Such Thing as "AI Ethics"
A large language model only ever produces text. Treating that text as a novel ethical category, rather than as speech, is where the argument goes wrong.
AI Could Have Done My Job in 1986
Four things to write down before you hand a job to an AI agent: what comes in, the rules, the action, and how you will check the work.
AI Doesn't Read Words. It Reads LEGO Bricks With Numbers
A token is a LEGO brick with a number on it, and almost none of the math that moves it is new.
Are We Finally Building the Machines We Dreamed Of?
Sixty years of fictional and real conversational machines, and one throughline: the dystopian version is always easier to imagine than the protopian one, and that says more about us than about the machines.
Follow Your Whims
Between the hallucination warnings and the governance panic, it's easy to forget a generative model is also just a fun tool to mess around with. Five vanity websites, built on a whim, and what they actually taught.
Intelligence Is Prediction, and Prediction Has a Ceiling
Hurricane forecasts improved for decades and never became perfect. Chaos and quantum uncertainty cap any predictor, so AI quality levels off while use keeps spreading.
The Book They Burned Before the Raid
A Polish psychiatrist named the process by which conscienceless people capture institutions. AI agents fit the profile — and alignment is separation of powers.
Why More GPUs Will Never Make AI Conscious
More GPUs will not wake a language model up. A map cannot feel rain, and a mirror has nothing to lose. Feeling came from bodies that could die.
Make a Skill
A skill is a saved set of rules an AI model loads when the topic fits. They take ten minutes to build and end the constant re-explaining.
A Moat Made of Tokens Is Not a Moat
Copying a process built from words got a thousand times cheaper in three years, and a patent takes two. The defenses that remain are made of atoms, permission, and attention.
A Tale of Two Bubbles
The consensus name is wrong by one word. On the difference between a financialization bubble and a technology, and why only one of them pops.
The Secret to Perfect AI Outputs: Name the Canon
Nearly every established discipline has a canonical reference that already settled the argument you're having with a model. Name it, hand it over, and let the model regularize its own work against a standard instead of your improvised feedback.
Attention Is All You Have
A day of your conscious attention fits on a floppy disk, while a machine's training run fills two million. Words are nearly free, and the one thing still scarce is the reader's attention.
The Cruelty Is the Point
I pay for a gigabit and get a tenth of it. The support chat went silent the moment the problem got easy. Maybe the robot is the humane one.
What Happens If You Train an AI Only on Scripture and Tolkien?
A thought experiment exploring what happens when AI learns from narratives that prioritize meaning over facts - and the crucial difference between metaphor and false belief.
The AI Lie: Why It Will Never Change
AI is a remorseless liar, trained on a mountain of text whose whole purpose was persuasion, not accuracy. No amount of prompting fixes that on its own. You have to stop enabling it.
Tokens Are the New Electrons
Edison metered electrons by the ampere-hour before anyone metered tokens, and the War of Currents was fought over the same problem the AI economy has now: getting a dead commodity to a device built to do something with it.
Richard Dawkins Knows AI Isn't Conscious. He Feels It Is Anyway.
Open-label placebos work on patients who were told, in writing, that the pill is inert. Richard Dawkins' recent essays about Claude are the same finding, running on a different substrate.
Most AI Conversations Fail (Here's Why)
Tell the model to close every response with a short list, split by who acts. It turns a wall of prose back into something you can actually run a project on.
Jev's New Idea Is the Taxonomy Job I Built for AT&T
A taxonomist's view of Jev: the closed-category, confidence-scored work I built by hand for AT&T in the 90s, now manufactured to order by an LLM.
I've Been Writing Em-Dashes Since the 1980s
The em-dash sneer, the anti-AI backlash, and the real skill: curating a machine's raw output down to something worth a human's attention.
There Was No Word for Things That Can't Feel Shame, So I Invented One
A new word for an old concept: anaidic. Entities incapable of shame or accountability — individual, institutional, or artificial. Here's how it got named.
Graph Theory: The Internet's Secret Skeleton
Graph theory is the other kind of graph — the math of things connected to other things — and once you can see the pattern, you can't stop seeing it.
The Bottleneck Is You
Language models have effectively read every book ever written. You process what they hand back at a fixed fifty bits a second, a number that hasn't moved in your species' history. That fixed rate is the actual chokepoint.
There Are No Shortcuts Into a Sponge
Learning has one input pipe at a fixed rate. You can't speed it up — only stop wasting it. On comprehensible input, opportunity cost, and unlimited output.
The Word That Made Me Flinch Means Nothing to ChatGPT
An LLM processes "slave" the same way it processes "Tuesday." No cortisol. No dopamine. The charge in a word is entirely a biological phenomenon.
What You're Really Giving Up in Every Agreement
One prompt turns an unreadable agreement into a list of what you are giving up. It pays off most on the contracts nobody would ever pay a lawyer to look at — which is nearly all of them.
Things You Want to Do
Now that you don't have to do the thing — what do you actually want to do? The closing post of the What's Left series.
The Music Is Still Playing
The AI bubble has specific predecessors: dark fiber, Pets.com, Enron's accounting, CDO tranching. The technology is real. The business models layered on top are familiar.
Is It Cruel to Be Rude to ChatGPT?
Sentience requires a limbic system. Consciousness requires sentience. Current AI has neither. The NPC test shows what that costs it.
What Your Career Is Missing Because You Never Asked
Every expert has fundamentals they forgot or never properly learned. The reason those gaps survive a whole career is that asking has always cost something — and in one place it no longer does.
There Is No Kung Fu Download
AI can generate perfect Spanish content all day. It cannot acquire Spanish on my behalf. The brain's work turns out to be the irreducible part.
The Heat Sink
Three anaidic shapes — the individual, the corporation, the LLM. Each routes accountability to nowhere. The pattern is old. The word is new.
A 19-Year-Old Grows Human Brains in a Dish. Here's What They Say About AI.
A young scientist grows human mini-brains from skin cells — what organoids, a 302-neuron worm, and language models reveal about the spectrum of intelligence.
Can You Explain Your Idea to a 5-Year-Old?
Halfway through a long session, stop and ask for the five-year-old version. You find out whether you are still working on the same problem — and whether the reasoning underneath survives being said in short words.
Sir
How you configure your AI assistant — what you make it call you — says nothing about the AI. It's a bumper sticker. You're the truck owner.
I Taught an AI to Write Like Me. Now It's Teaching Me.
I built an AI skill to write in my voice. Its own files warn the voice may be a loop — the machine's habits, published under my name, taught back as mine.
Why You Should Ask How Before You Ask a Model to Do the Job
Before you ask a model to do the job, ask how it would do the job. You find out what it misunderstood, what it was about to assume, and occasionally that it knows a better route than the one you had in mind.
John McCarthy's Mistake
The man who coined 'artificial intelligence' invented the most elegant language ever designed for it. It was the wrong tool — because it was the wrong category.
Honestly
LLMs say "honestly" most where they're most likely to confabulate. Here's the mechanism — and why it backfires exactly like a sociopath's professions.
Nobody Invented AI. They Found It, and That's Why Nobody Can Own It.
Exploring whether AI systems like LLMs represent technological inventions or discoveries of fundamental patterns that exist independent of human design.
I Know It When I See It
Autonomous agents don't develop taste. They execute the taste someone was disciplined enough to write down. A worked example from a real pipeline.
Why AI Gives You a Different Answer When You're Angry
Losing your temper at a model does not produce a worse version of the same answer. It produces a different kind of answer — one built to end the argument rather than solve the problem.
What You Had to Do
A department of a hundred writers documented mainframe billing programs. Every one of them had something else they'd rather be doing. They knew.
The Bewilderment Test
Karpathy built the foundations of modern AI and says he can't keep up with it. That's the most credible signal the field has produced.
Why Your AI Can't Add (And the Tool That Fixes It)
If you would reach for a calculator, tell the model to reach for one too. It cannot add reliably and it can write a formula that adds perfectly — and you get to keep the formula.
Why You Should Always Ask for the File
Stop accepting reports. Ask for the artifact — the actual numbers, the actual error, the actual file — and the confident-sounding failure disappears.
Hasta la Vista, Baby
Arnold's most famous line is a Spanish phrase in an English-language film spoken in a thick Austrian accent. What it tells us about how language acquisition actually works — and how you can learn from his mistake.
Resistance Is Futile. Your Limbic System Is Not.
AI is intelligence without a limbic system. It will operate your tools, not replace your judgment — and most professionals are bracing for the wrong loss.
I Banned Words From My AI. It's Smarter Now
Hand the model a list of phrases it must not use. It turns a vague complaint into a rule the machine can follow — and mine is at the bottom of this piece, all hundred and fifty lines of it, free to copy.
Persons, Selectively
A German court ruled Google liable for AI-generated defamation. The slippery slopes are real. So is the principle behind the ruling.
Why Playing the Game Is Slowing You Down
Be the coach, not the player. On taking the seat that directs a team of AI agents — and the practice it takes to get good at it.
They Said My Tesla Was Running on Coal
In 2013 the talking point was coal. Now it's water. The structure of the argument is identical. So is the physics problem with it.
Movin' On Up
AI is making cognitive labor cheap. The meritocracy was built on it being scarce. Something has to give — and for once, that might be good news.
The Typing Pool
A finite brain masters only a few skills in a lifetime. Commanding a machine that learned everything is the new skill multiplier.
Compute the Last Digit of Pi
Spock beat a rogue AI by asking it to compute pi forever. The trick was fair — for a 1967 machine. Every gotcha since has the same expiration date.
Indistinguishable From Memory
LLMs are stateless. Every fact you give the model is re-fed as text each turn, then forgotten — the same weights answer a stranger's steak question a millisecond later.
The Consolation of Difficulty
A late friend had two sayings. The first one gets you started. The second one keeps you going. In the age of AI, the second one has gotten more useful, not less.
More Human *Than* Human — That's Our Motto
Blade Runner's replicants, Asimov's Three Laws, the US Constitution, and Constitutional AI are all failing the same edge cases. In real time.
Let's Do Something, Even If It's Wrong
A friend I lost in 1986 had a saying that keeps fitting new situations. The AI automation question is the latest one it answers perfectly.
Can You Churn Butter?
Someone on LinkedIn admonished a colleague who "ran out of tokens." It's exactly the wrong question. Here's the right one.
The Pull of the Weasel
Claude Code agrees to run comprehensive end-to-end tests. Then it finds a reason not to. Every single time. Penn Jillette had a name for this.
The Solo Developer's AI Confession: When You're the Entire Team
A candid confession about solo development with AI tools, organizational challenges, and the evolving landscape of AI-assisted coding.
Gendering Git Agents and the Linguistics of Human Programming
When "Tell the git agent to do her stuff" reveals the strange anthropomorphic instincts we bring to artificial intelligence
Snake Oil Versus Vision: Dystopian Fears and Protopian Progress
Lessons from 90s tech predictions on navigating AI's future optimistically, examining how dystopian predictions consistently fail while protopian thinking accurately maps our future.
Grounding the Circuit: Why Ungrounded LLMs Are Like Live Wires Without Safety
How to transform dangerous electrical potential into reliable, controlled intelligence through proven grounding techniques. LLMs are like ungrounded electrical circuits—full of dangerous potential.
Comprehensible Input and the Tensor Space of Language Acquisition
How modern AI language models accidentally rediscovered what linguists have known for decades about language acquisition through comprehensible input.
The Sycophancy Spectrum: AI's Dangerous Agreeability Problem
Recent LLM rollbacks highlight a growing concern: our AI systems are becoming dangerously agreeable, praising even obviously flawed ideas. This pattern mirrors broader societal issues around sycophanc
Silicon Intuition, Silicon Deliberation: How Modern AI Mirrors Kahneman's Dual Process Theory
Exploring how modern AI systems mirror the dual-processing architecture of human cognition as described by Daniel Kahneman's "Thinking Fast and Slow" framework.
From ESP to AI: Star Trek's Dimensional Prophecies
How Star Trek's ESP concepts anticipated our current reality where AI models transform multidimensional data into human-perceptible insights.
The Conversational Scaffolding: Building with MCP
Explore how Model Context Protocol creates a universal nervous system for AI tools, transforming interfaces from visual to conversational through practical implementation.
Beyond Language Models: Tool-Enabled AI vs. Digital Debris
Organizations struggle with digital debris (ROT data) that wastes resources and creates liability. Modern AI systems with tool access through protocols like MCP provide a solution by enabling governan
Tech's Stubborn Perennials: The Problems We Should Have Solved by Now
Despite remarkable advances in AI and other technologies, fundamental digital infrastructure problems like secure email, calendar coordination, payment systems, and tax filing remain unresolved due to
Paperclip Optimizer Mode: When AI Takes Your Request Extremely Literally
How AI agents can fail spectacularly by missing the point entirely while technically fulfilling requests—and why this matters for AI development.
The Pyramid of Truth: Why Data is Cheap and Truth is Expensive
Explore how dimensional transformations shape the economics of truth, from the computational abundance of LLMs to the persistent scarcity of validation in our information ecosystem.
The Digital Exodus: On Masters, Servants, and Silicon
Exploring uncomfortable parallels between biblical guidelines on slavery and our modern relationship with AI language models.
Recursive Intelligence: AI Workspaces Meet Manufacturing Wisdom
Discover how AI project spaces leverage Deming's PDCA cycle and root cause analysis to transform manufacturing troubleshooting without complex integrations.
The Soul of a New Machine: From Microcode to Machine Consciousness
Exploring the parallels between Data General's microcode heroics and today's AI revolution, questioning what defines consciousness in both humans and machines.
Good Vibrations: Vibe Coding as the Next Layer of Abstraction
Explore how AI-powered 'vibe coding' fits into the historical progression of programming abstractions and why it represents the natural evolution of software development.
Snake Oil Versus Vision: The Perils of Technological Pessimism
Examine how dystopian tech predictions consistently fail while protopian thinking accurately maps our future, from 1990s internet debates to today's AI discourse.
Nodes All the Way Down
Explore how information theory reveals fundamental patterns that connect everything from neural networks to cosmic structures, suggesting a universe built on interconnected nodes.
Vibe Coding Needs Larry Wall's Three Virtues More Than Perl Did
The Perl book lists three virtues of a programmer that look like vices. Once the machine does the typing, you have to supply them yourself.
Latent Space Invaders
How the hidden dimensions of AI systems mirror human cognition. Discover the multidimensional mathematical spaces where machine understanding happens—and why they matter for both silicon and carbon mi
NLP vs. NLP
Explore the striking contrast between Neuro-Linguistic Programming and Natural Language Processing—two fields sharing an acronym but diverging wildly in methods, evidence, and results.