No more excuses

// chapter 00

You just won the lottery

What changes when expert knowledge costs 20 dollars a month?

Freddy Vega, founder of the online school Platzi, opens his talk What if everything goes right with AI? with an uncomfortable story: a lot of lottery winners end up worse off afterwards.

The easy explanation is moralistic: "easy money, hard life", karma, blah blah blah. Freddy's is more interesting: money is the end of excuses.

Think about your usual excuses:

• I don't go to the gym because I have no time, and a personal trainer costs an arm and a leg.
• I'd eat better, but eating well is expensive and complicated. You eat what there is.
• I'd read that difficult book… if I had the time.

Then you hit the jackpot. You have a trainer, a cook and all the time in the world. And if you're still not fit, still not eating well, still not reading… there's no one left to blame. Only you.

AI does something very similar. Freddy puts it like this:

"AI is the compression of expert knowledge, practically free, in everyone's hands."

For about 20 dollars a month you carry in your pocket almost the same models the most advanced researchers on the planet were using a couple of months ago. There's no secret supermodel, a thousand times better, hidden in a basement in San Francisco. What you have is, more or less, what there is.

So the question of this course isn't "what can AI do?". It's this one:

What happens when experts' time becomes infinite?

And, above all, what happens next? Before we move on, one thing.

// chapter 01

A confusion of ideas

If AI makes me more efficient, will I work less?

Christy Yao is a software engineer at a big tech company. She says she has this conversation over and over:

• So, with AI… are you even coding anymore?
• No. AI codes for me.
• Then you must have so much more free time!
• Well… no.

And it's not bad luck. It's a paradox more than 150 years old.

Watt, coal and a party-pooper economist

James Watt's steam engine did the same work with far less coal than the engines before it. The logical expectation: England would burn less coal. What actually happened: it burned far more.

With cheaper power, it paid to put engines everywhere: factories, mines, trains, ships. Each engine used less; the country used much more.

In 1865 the economist William Stanley Jevons explained it in The Coal Question and called the idea that "more efficiency = less consumption" a confusion of ideas. Today we call it the Jevons paradox.

The washing machine didn't give you your afternoons back

Christy brings it home with a book: More Work for Mother, by historian Ruth Schwartz Cowan (1983). Each household appliance made a chore easier… and the standard went up. Clean clothes used to be a once-a-week thing; now clean clothes every day and a spotless house are simply expected.

Three consequences follow, and they affect you directly:

The other side of the coin

Freddy uses the same paradox to reach an optimistic conclusion: if whatever gets cheaper gets used more, AI doesn't have to bring mass unemployment, but more demand for work… of a different kind.

His example: have you ever been happy to call a call center? "Yay, my paycheck is three days late, let me call!" Never. With AI and people working together, that service could finally be good, and handle far more cases.

Is he right? It's his thesis, and history gives him plenty of arguments, though transitions hurt whoever gets caught in the middle (more on that in chapter 2). What's beyond debate is the part that's up to you:

"It takes a conscious effort to do less work and have more free time. Don't count on AI doing that for you. That's your decision."

// chapter 02

Predict the traffic jam

What consequences is almost nobody looking at?

There's a science-fiction line, popularized by Frederik Pohl, that Freddy uses as a compass:

"Good science fiction predicts the car. Great science fiction predicts the traffic jam."

Predicting the car is easy: it's what the technology does. That's the first order. The hard part is seeing what changes when everyone has a car: traffic jams, highways, suburbs, malls, gas stations. That's the second order.

Freddy points out something medicine and software have in common: in both, the bottleneck is us, the experts. If expert time becomes almost infinite, that bottleneck opens up. Let's see what happens.

And yes, there's a flip side: the same technology makes mass surveillance and drones cheap, and crime learns AI faster than the law does.

// chapter 03

The two doors

If everyone can create, who wins?

Freddy sums it up in one sentence:

"The hard part won't be building software, but getting people to use it."

Put the pieces from the previous chapters together. Creating gets cheaper, so far more gets created (Jevons). Everyone has the tool, so building is the baseline, not the edge. Supply explodes… but people's attention doesn't. The result: a huge line at the "build one more thing" door and almost nobody at the "getting clients" door.

Why is almost everyone lining up at the wrong door? Because building is comfortable: it gives instant feedback, it depends only on you, and AI makes it even easier. Talking to customers is scary: they might say no.

The skills behind the short door are the ones becoming scarce:

• Understanding a real problem, for someone who would pay to solve it.
• Knowing what NOT to build: finding the minimum version.
• Selling, and daring to ask for payment.
• Distribution: reaching the places your people already are.
• Building trust: having your name back what you do.
• A sense of quality: knowing when something is actually good.

The good news: all of this can be trained. The bad news: nobody will train it for you. Sound familiar?

// chapter 04

Skipping the rep

Ban AI or use it? When yes and when no?

Jenny has a PhD in neuroscience and a one-year-old son who is fascinated every time she asks the smart speaker to turn off the lights. She, on the other hand, admits she's more scared than excited:

"Our boomer parents prepared us for a world that doesn't exist anymore. And as millennial parents, we're about to make the exact same mistake."

She thinks her son's generation will face a bigger existential crisis than ours, with a very concrete question: what is the point of me when AI can do everything?

What's interesting is what she does about it. She doesn't keep her son away from AI. She protects two things:

• Critical thinking: thinking for himself, holding values that are actually his, looking at a piece of information, analyzing it and forming his own opinion.
• Creativity: imagination, which she considers the hardest thing for an AI to reproduce.

Both are muscles

In neuroscience this is called neuroplasticity: the brain strengthens the connections you use and prunes the ones you don't. If you hand a kid an AI that does the thinking from the very start, they skip the rep. And the muscle never gets built.

The answer key

Freddy tells it from another angle. Knowledge was always there, in libraries. The hard part was never having it, but going there, opening the book, not opening TikTok, doing the exercise, not peeking at the answer… and not opening TikTok.

Using AI mindlessly is studying with the answer key right next to you. If you copy the solutions from your algebra textbook, the only thing you learn is nice handwriting. That's why he believes AI will create two classes of people: for those willing to learn, "the sky's the limit"; for the rest, "more than an accelerator, it's a poison".

His stance is radical: don't write with AI, because writing is thinking. Just as we no longer haul sacks and so we go to the gym, now we need a mental gym.

Banning it isn't the answer

Not at home and not at work. AI is going to be part of that kid's life, and of your team's. Banning it only gets it used in secret and without judgment. What does work is what Jenny proposes: teaching when to use it, when not to, and why. Three simple rules:

// chapter 05

The power was the spot

Why does your position in the network matter more than raw talent?

Regina George, queen of Mean Girls, wasn't the prettiest, or the smartest, or the nicest. And yet she ran the whole school. Why? Spoiler: math.

Remember the cafeteria map Janis draws for Cady? It tells you where everyone sits, but not the most important thing: who's connected to whom.

For that you need a graph: each person is a dot (a node) and each relationship a line (an edge). That simple. And that's how map apps, social networks and a whole lot of AI work.

Three ways to measure who's in charge

1. Degree: how many lines you have. Regina has five, the most. But that doesn't explain everything.
2. Betweenness: Gretchen has fewer lines, but she sits right between groups. "Gretchen knows everybody's business": any gossip going from one group to another goes through her. Remove her and the graph splits in two.
3. Eigenvector centrality: it's not how many friends you have, but how important your friends are. Power reaches you on the rebound. With a similar idea (PageRank), Google started ranking the Internet: a page matters if important pages link to it.

What Cady does

Cady doesn't attack Regina head-on. She cuts her connections: separates her from Aaron, from Karen, from Gretchen. And who fills the gap? Cady. Not by being prettier or smarter: by standing in the same spot.

The power was never Regina's. It was the spot.

Companies have been doing AI with graphs for years

• Search engines: PageRank ranked the web by who links to whom.
• Social networks: they look at who follows whom and how things get shared, and use that to decide what you see and who sees what you post.
• Banks: they map who sends money to whom to catch fraud rings.
• Drugs: a molecule is a graph (atoms and bonds). In 2020, a model that reads molecules this way helped discover a new antibiotic, halicin.

And your brain too: neurons and connections. The neuroplasticity from the previous chapter is, literally, strengthening some edges and pruning others. Learning is changing your graph.

Your career and your company are graphs too

In a world where everyone builds (chapter 3), what sets you apart isn't only what you make, but where you sit in the network:

• Be a bridge: connect groups that don't talk to each other (business and tech, customers and product, your industry and AI). Information and opportunities flow through there.
• Connect with who matters: it's not about collecting contacts, but about relationships with nodes that are themselves well connected: clients who refer you, partners with networks.
• Don't depend on a single node: if your business depends on one client, one supplier or one person, removing them splits you in two. Run the Gretchen test.
• Leadership is a position you maintain: stop tending your lines and someone else will take the spot. Just ask Regina.

// chapter 06

What stays scarce

In a world of abundance, what will have value?

Freddy takes down a myth: the idea that nobody will have a job and money will be infinite "is absurd". The physical world is still finite. Land doesn't grow. People want a home where nobody bothers them. And even though you can buy croissants at any supermarket, what you want is "the little croissant with a bit of sugar on top and little bits of bacon". Beautiful, exclusive, special things will still be paid for.

What does change is the pace. When intelligence is cheap:

That virtuous cycle lets civilization skip steps. We'll get used to it quickly, but it will feel like the singularity.

In that abundant world, value moves to what stays scarce. Look back over the course and check for yourself.

// chapter 07

No more excuses

So what are you going to do?

Back to the lottery. With AI, expert knowledge is in your pocket. Creating is almost free. That won't give you free time (Jevons), but it does take something away: your excuses.

That's why Freddy closes his talk with a question. Here it is, almost word for word:

"What do you dream of doing with your life? Not what you were dealt. Not the limits you have right now. Not the local, particular version of the excuse you give yourself for not living the story you say you'll live. But what are you going to do? Because there are no more excuses."

The seven ideas, on one screen

1. AI doesn't give you results: it takes away your excuses.
2. More efficiency isn't less work: it's more use and a higher bar.
3. Look at the second order: the traffic jam, not the car.
4. When creating is cheap, the line is at building; the opportunity is in getting clients.
5. Judgment and creativity are muscles: if you're learning, you go first.
6. The power is the spot: tend your lines.
7. Value moves to what's scarce: trust, attention, judgment, network, the physical… and will.