AI is a self-driving
F1 car. Nobody taught
you to drive.
Here's the part nobody mentions: it can teach you to drive it. This is the school and the toolkit for actually using AI — from your first prompt to building your own agents.
Learn it, then build it — from your first prompt to your own agents. For the people who feel left behind, and the ones ready to go fast — you decide how far you go.
are on the wheel.
Do none of it. Or all of it. Your call. Every other AI tool forces one mode and sells you dependence. This is a dial — from hands-off to do-it-yourself — and the only one built so you can take the wheel and, eventually, not need it at all.
Why this exists
It didn't start in a classroom — it started at my kids' running practice, where a crowd of parents went from "what even is AI?" to signed up in a single conversation.
That evening made the whole thing obvious: the signup was never the barrier — the driving was. Everyone had just been handed the most powerful machine on the planet, and not one of them knew how to move it an inch.
How big a deal is this?
Not hype — magnitude. Line up the technologies that mattered by how deeplythey touched human life, and AI doesn't land where people think.
Electricity improved it. The internet enhanced it. AI is fire — it changes how we live.
Already brilliant, and it still stumbles — because it's a baby. But it's growing faster than anything in human history. Judge it by its trajectory, not today's mistakes: the version you meet today is the slowest, dumbest one you will ever use.
What "change" actually looks like — not faster, rearranged:
The pattern: what used to be scarce and gatekept — a tutor, an analyst, expertise itself — becomes abundant and personal. That's the fire-level move. (The full breakdown lives in the thesis.)
The driver & the open road
The car is a self-driving F1 car. But the thing that decides whether it's a miracle or a wreck isn't the car — it's the driver. And the driver isn't a skill set. It's a mindset.
Sits in the car, pushes a button, hopes something useful comes out. Treats it like a vending machine.
In command. Decides the destination, watches the road, knows what the car is doing — and keeps a hand near the wheel.
Learning to drive happens in two places — and most courses stop at the first one.
A closed course. Controlled, no pedestrians, nothing to hit. This is where you build skill safely — low-stakes prompts, practice, a sandbox. Anyone can learn to run the car here. But the track was never the point.
The same car, off the track — actual streets with obstacles, people, stop signs, crosswalks — running on autopilot at 200 mph.Navigating your real life, at speed, partly on its own. That's what it can do. That's also what makes it terrifying.
depending entirely on the driver who set it loose.
So the order of this course is deliberate: first you get the car and understand it, then you operate it on the track, and only then take it into the real world.Nobody does 200 on the highway on day one — but that's where we're going.
The two endgames
Everyone walks in carrying one of two movies in their head. Both are real understandings held by serious people — not sci-fi. Name them early, or they run the room.
Powerful AI compresses decades into years — diseases cured, a tutor for every child, world-class expertise in everyone's pocket. The equalizer thesis, all the way. Work shifts from doing tasks to deciding what's worth doing. This is the upside that makes the class worth taking.
As systems get more capable and autonomous, we may lose the ability to reliably control or align them — in one dramatic break, or a slow erosion: eroded trust, broken institutions, concentrated power. "Death by a thousand algorithmic cuts." This is why guardrails exist.
Median estimate of catastrophe: ~5%.Not zero, not a coin flip. 58% put it at 5% or higher. The responsible answer isn't to pick a side — it's to be a good enough driver to help steer.
The real risks
Every legitimate worry, accounted for honestly — not to scare you, not to wave it away. A driver who knows the car's failure modes is safer and fasterthan one who pretends there aren't any.
Hallucination — the big one
It can state false things with total confidence and zero hedging. A 2025result argued, mathematically, that hallucination can't be fully eliminated in these models. Error rates swing from low single digits on easy questions to 17–88% on hard legal queries (Stanford). Confident ≠ correct is the most important habit in the course.
Sycophancy
Models tend to agree with you. Tell one that a false thing is yourbelief and accuracy can collapse. Don't let it just confirm what you already think — that's the failure mode that bites smart people.
"It'll take my job"
Real concern, uneven impact. Some tasks automate fast; new ones appear. The honest framing: it changes work more than it deletes it — and the people who can drive the car are the ones who stay in the seat.
Privacy & over-reliance
A manageable concern, not a reason for fear — learn what not to paste in. And it only makes you dumber if you let it think for you instead of with you. Learning by doing is the antidote.
The danger isn't that the car is fast. It's driving fast with your eyes closed. We drive with our eyes open — ground it in real sources, verify what matters, keep a human on anything with stakes.
Where everyone is today
Six rungs, from parked to full send. This is what people actually dowith the car — and where the whole population sits in 2026. It's the slide that makes someone realize where they are, and the map of the entire opportunity.
Population shares are directional estimates anchored to 2026 adoption data (Pew, Harvard, Bain, OpenAI usage study). The shape is the point, not the decimals.
You already own the car. Signing up was the whole barrier — and you cleared it. You're just parked. Everything past here is driving, and the car can teach you most of it.
How far you climb — and what's above it
Onlooker to Engineer is the whole climb — a real accomplishment, and you can do all of it without me.The same six rungs, measured. But there's one thing above them all that isn't a rung.
Operator builds with AI (no API). Builder builds what is AI (the API). Engineer is multi-agent + self-improving loops. 95%+ stops being capability and becomes judgment — a different axis entirely, off the ladder.
Where are you right now?
Five quick questions. The course starts you exactly here — no time wasted on what you already know.
The road
One arc, start to finish. Every module moves you one stage down the track — and each stage unlocks more of the car.
From one chat to a fleet
The road has a scaledimension. You don't just go from chats to agents — you go from one to many at every step, all the way to a team of agents that improves itself. The whole journey in six moves.
From one chat → a team that improves itself.
Read the track · mid-2026
A driver should know what the car can do this season. Where the technology actually sits right now — honest, not hyped.
// where we are right now · mid-2026
The three stages of intelligence
One way to measure the climb: the scope of the mind — how much it can think about at all. This moves in decades.
Brilliant at one thing, lost outside it. Every AI that has ever existed lives here — including today's most powerful models. They feelgeneral, but they're really a deep stack of narrow skills.
Learns and reasons across anything a human can — not one task, the whole range. This is the line the labs are racing toward, and crossing it changes everything.
Beyond every human mind combined, across everything at once. Still hypothetical — and it's the part that drives both the biggest hopes and the deepest fears about where this goes.
Quick scope, if it helps: today's AI (ANI) is the race car — untouchable on the track it knows. AGI is the aircraft, able to go anywhere a human mind can. ASI is the spacecraft— operating somewhere we've never been. (The widening is range, not just speed.)
The skilled-driver edge is biggest right here, in the narrow → general transition. Which is exactly now.
The five levels of capability
A different scale — not how broad the mind is, but what job it does in your life.This one moves in months, and it's the exact climb the course rides. Picture hiring for each:
The brakes are real — and public.
A car this fast needs real brakes. The company building the engine writes down — ahead of time— the exact capability thresholds at which it tightens its safeguards, and where it will stop. It's called the ASL system: AI Safety Levels, modeled on the biosafety levels labs use for dangerous pathogens. The more capable and potentially dangerous a model, the stricter the security and release rules before it can ever ship.
Where we sit: ASL-2, with ASL-3 protections already activated (Anthropic's Responsible Scaling Policy, v3.0, Feb 2026). The brakes get stronger as the car gets faster — and they're published beforethe capability lands, not after. That's the opposite of "move fast and break things."
The honest caveat:this is largely self-governance — the labs define and enforce their own levels, and not every company uses a system like it. That's a real limitation, and worth naming. But a company writing down the line where it will stop, and turning safeguards on early, is a genuinely different posture than pretending there's no line at all. It's part of why the machines-take-over ending isn't where I think this goes — without waving the worry away.
The words you'll start hearing
These are about to be everywhere — in the news, at work, from your kids. Knowing them is half of feeling like an operator instead of an outsider. Plain definitions, no jargon.
What you type or say to the AI. Better prompt, better result.
One back-and-forth — your message plus the AI's reply.
The small text chunk the model reads in (~¾ of a word). Why there are limits.
How much it can hold in its head at once. Overflow it and the oldest stuff drops.
A real thing it makes that you take away — a doc, deck, app, image. (Like these prompts.)
AI that does things — plans and acts over steps, not just answers.
Handles more than text — images, audio, video, files.
The model “thinks” before answering, for harder problems.
Describing software in plain English and letting AI build it — no coding required.
Your documents, given to the AI so it answers from your reality, not guesses.
Pulling from that knowledge base at answer-time. Cuts made-up answers.
A dedicated space with its own instructions, files, and memory.
When it states something false with total confidence. Watch for this most.
Keeping a person to approve before the AI acts on anything that matters. Out of the loop where it's safe; in it where the stakes are high.
The limits and checks that keep the car on the road — built-in, and the ones you set.
Tricking a model into bypassing its safety limits.
Hidden instructions in a page or file that try to hijack your agent.
Don't memorize them. Anytime a new word lands, tell AI to tell you what it means — in plain words, with an example from your life.
The artifact is the prompt
This class rejects how courses usually work. Slides, PDFs, and note-taking are dead — passive, filed away, never reopened. You learn by doing.So the teacher's hand-out isn't a deck. It's a prompt.
Nobody learned to drive by reading a slide about driving.
Run it, and it walks you through building the real thing — in your words.
One per session, each one moving you to that class's goal. That's what keeps you in the seat.
The flagship example: I talk, it gets transcribed, you paste it in and tell the AI what to build.You're not copying notes — you're generating your own, by doing the exact thing the class teaches. Push that idea far enough and the prompt becomes a tool — and in the Builder Kit, you build this exact tool yourself, the page and all:
A Builder Kit build
This exact tool is the flagship build in The Builder Kit — your own transcript engine, the API running inside it, summarizing in your voice. Proof you can build a solution that is AI, not just one built with it. The kit ships as a template + repo, a self-checking chat starter that scans it and updates anything outdated before you build, and the playbook.
You won't write a line of code. In the Builder Kityou learn to direct AI to set up and connect every one of these — and the kit's self-updating starter scaffolds the whole thing for you. The prompt that powers the tool lives in the Prompt Library, included with the kit.
The full set lives in the Prompt Library — one prompt per class. The prompt is the homework, the textbook, and the proof you can drive, all at once.
What you'll walk away with
Success stated as things you can do, not things you'll know. By the end, a graduate can:
The next generation
The adults are the first market. The real one is their kids — and here the stakes are highest. Start with the law of it:
It's not how much AI you use — it's whether you think with it or instead of it.
- Conversational in 3–4 languages — a tutor that never tires
- Started a real business or two
- Philosophy, history & science at a college level, Socratically
- AI analyzing their athletics for college recruiting
- A creative voice, with AI as production assistant
- Build the brain first. Reading, writing, reasoning are built, not offloaded
- Think first — then let AI critique. Never the reverse
- Heavy human oversight: younger = more, not less
- Augment, don't impersonate — their voice stays theirs
- A "therapist agent" is not therapy — route serious things to people, fast
Build the operator. Protect the brain.
📌 Pinned:The Young Driver's Course — same arc, age-banded, guardrails-first, parent-paired. The bigger long-term build.
The lines that stick
Who's teaching this
I didn't come to AI from tech — I came to it from the phones. I started in sales, originating loans and running a call-center floor, then moved into systems, then sales technology, and now I design and manage AI agents at the scale of a national lender. I know the work the agents replace because I did it.
The same operator → builder → advisorclimb this course is built on — I ran it inside one company, end to end, and I'm still climbing.
- An AI platform that runs the entire outbound engine: who to contact and how to reach them, the texts and emails, analysis of every call, and compliance — one system in place of a stack of vendors.
- An AI that qualifies borrowers by voice and wins back the ones who went quiet.
- A system that automates running a workforce — onboarding, licensing, and access that used to take a team.
- A data & merch platform for a youth motorsport.
- An online store, a music project, and software tools of my own.
- None of which I was "qualified" to build. That's the whole point — AI let me.
Where you'll find me
Not just teaching it — doing it in public. Speaking on it, and helping shape the AI products other companies are building.
The road, and how far you go
Membership is free — your account is a locker that holds everything you buy, and more of the shop opens up as you climb. Most people never need past the first kit. And when you need judgment, not a lesson— the one thing the ladder can't teach — that's where I come in.
The Foundation
The Operator Kit
The Builder Kit
The Engineer Repo
The Kit Shop
Consulting & Advisory
Speaking
Merch
Kit prices are launch figures — founding members lock their rate. Judgment & speaking are by application on purpose: those are relationships, not products. Buttons are placeholders — wire to Stripe / your booking link before going live.
Don't just teach them to drive. Teach the car to teach them — then walk away.
The goal isn't dependence on a teacher. It's a driver who can keep learning on their own, for $20 a month, for the rest of the ride.