The Abundance Boom: A Memo from 2030

It’s 2030, and I’m writing this from a world that looks nothing like what the doomers predicted five years ago.

Remember 2026? When every third think piece was about the AI-driven jobless apocalypse? When serious people and fools alike were really convinced that Claude and ChatGPT and Seedance 2.0 were going to create permanent mass unemployment and usher in some kind of neo-feudal dystopia?

Yeah, that didn’t happen.

And if you actually understood how technology and economics work, if you’d actually paid attention to literally any previous technology transition in human history, you knew it wasn’t going to happen.

But here’s what did happen, and it’s way more interesting than the doom porn everyone was addicted to back then.

It’s March 2029, and a five-person team in Jakarta just dropped a film that’s competing with Marvel for box office dominance. Not competing in some indie-film-festival-participation-trophy kind of way. Actually competing. $340 million opening weekend worldwide. Ninety-five percent on Rotten Tomatoes. Three of the team members are under 25. Their total budget was $2.8 million.

The director used to work at a call center. The lead “cinematographer,” though that term barely means what it used to anymore, was a wedding photographer. They used video generation models that didn’t exist in any practical form in 2026, AI tools that let them create footage that would’ve required $200 million and Industrial Light & Magic five years earlier.

They acted in it themselves, using cardboard props to fill in laser swords and flying cars and then swapped it with advanced AI video editing software they cloned from more expensive software they couldn’t afford. The software got cranked out by one of the new micro software creation houses that have popped up all over India after the crash of some of the big Indian IT outsourcing houses. The coders didn’t go to the breadline. They went to work for the neo-outsourcing-insourcing houses that are booming. Back in 2026, people thought AI would replace cheap outsourcing but cheap outsourcing plus AI just boomed along with the insourcing boom back in the western world.

Here’s the thing nobody saw coming either:

Hollywood didn’t collapse.

The studio system didn’t die. What died was the price structure. What died was the stranglehold that a handful of executives had on what stories got told and how they got told.

By 2030, Marvel was still making movies, but their budgets had cratered from $300 million to $60 million because half the VFX work that used to require 500 artists in three countries was now handled by 50 people using AI tools that did the grunt work in hours instead of months. And you know what Disney did with those savings? They greenlit twelve other projects that never would’ve gotten funding under the old economics. Weirder stuff. Edgier stuff. Stuff that didn’t have to appeal to the broadest possible global audience because the financial risk was 80% lower.

The Jakarta team? They made their money and immediately spun up three more projects, hiring 35 people in the process. Because here’s what the doomers never understood: productivity tools don’t eliminate human work. They eliminate the barrier between human vision and execution.

Look, I get why people were scared in 2026. I really do. When you’re in the middle of a transition, everything feels unprecedented. Everything feels like this time is different. But this time wasn’t different. It never really is. It just looks that way when you’re knee deep in it and it all feels so new and terrifying and exciting.

I’ve been writing about and working in tech since the 1990s. I started working in an internet startup when everyone thought that was a dumb idea and the Internet was just a toy. “You’re wasting your life,” they told me. Really. I went to work in Linux when my recruiter told me all the jobs were in Solaris. I told him “Solaris won’t exist in ten years” and he looked at me like I had two heads. I saw panics over TV and video games and encryption and every other technology. People used to panic about Teddy bears and radios destroying the world. And yeah I’m serious. Look at those news clippings in the links. “Radio Blamed for Freak Weather.” “Radio Harms Children.” Radio induced insanity drove a preacher to kill his wife.

People love a good panic.

We eat it up.

And we always make the same goddamn mistakes: assuming that current limitations are permanent, that one thing changes and everything else stays the same, assuming we can’t and don’t adapt and just stay static, assuming that economic complexity can be reduced to “machines do X, therefore humans can’t do X anymore, therefore unemployment.”

It’s the lump of labor fallacy dressed up in neural network clothing, and it was bullshit then and it’s bullshit now.

Here’s what actually happened to the economy, and why most economists missed it: AI triggered the most dramatic deflationary spiral in modern history. But it was good deflation, the kind driven by productivity explosions rather than demand collapse, and most people don’t understand the difference.

Between 2026 and 2030, the real cost of producing a professional-quality video game dropped by 85%. The cost of producing a feature film dropped by 73%. Legal document preparation: down 68%. Preliminary medical diagnostics: down 54%. Marketing content creation: down 91%. Software development: down 62%.

Now, if you’re an X addict stuck in 2026 thinking, you’re panicking right now. “It’s the end of white collar work!” Sure, it meant some jobs changed.

But here’s what happened to total employment in those sectors:

It went up.

Why?

Because when you drop the cost of making a video game by 85%, suddenly there’s room in the market for 50,000 new game studios instead of 5,000. When you drop the cost of making a film by 73%, you don’t get fewer films, you get an explosion of content, an explosion of niche markets, an explosion of previously impossible creative visions finding audiences.

The nurse making $78,000 in 2026 is making $82,000 in 2029, but her purchasing power is up 40% because everything got cheaper. She’s not just buying the same stuff for less, she’s buying stuff that didn’t exist or wasn’t accessible to someone at her income level five years ago.

That’s not a dystopia. That’s abundance.

Okay, but what about the displacement? What about the concept artists who spent 15 years mastering their craft, only to watch AI generate beautiful artwork in seconds?

Yeah, that was real. That was painful. I’m not going to blow sunshine up your ass and pretend it was painless. It wasn’t.

But here’s what actually happened, and it’s not what anyone predicted:

The coders and concept artists who just wanted to do one thing and who didn’t want to adapt or learn something new, the ones who tried to gate-keep, the ones who didn’t have any big picture understanding and just thought in silos, yeah they struggled. The ones who thought they could wave it all away with moral outrage found out that it wouldn’t go away any more than digital editing was going to go away because people who cut film with scissors screamed about it.

But the coders who understood the larger features and the UX and what they were working towards thrived. Generalists thrived. Cross-trained coders. Full stack coders. And the concept artists who understood storytelling, who could art-direct the AI, who could bridge the gap between “technically impressive” and “emotionally resonant” became more valuable than ever in the age of AI. By 2027, senior concept artists with strong vision were commanding higher rates than they ever had, because now they could execute ideas 10x faster with AI assistance, which meant they could work on 10x more projects.

The solo marketing consultant from 2026, the one who was grinding herself to death trying to do strategy, execution, analytics, and client management as one person? By 2027 she had a team of eight AI assistants who could pull ad stats, analyze them, write client briefs, concept ideas, do research and more. The AI tools handled the grunt work, data analysis, first-draft content, A/B test setup, which freed her up to do actual strategic thinking and client relationships. She spends more time meeting clients in real life, sharing a coffee and a funny story about her kids and theirs and how hard it is to juggle in the modern world. Her revenue went up 340%. Her stress levels went down.

The content writer? He originally got axed because some lazy execs thought “GPT can do it” but got hired back when his clients started realizing they couldn’t tell good copy from a hole in the wall. And all their ad click-throughs dropped to a .001% because the copy was generic garbage without someone to shepherd the AI. He now wields a friendly and helpful AI like a wizard with a Cursor for writing style platform that has editing, researching, fact-checking and proofreading agents baked right in and he’s closing more clients than ever and doing the work in a quarter of the time.

The game developer who used to spend 70% of his time on asset creation and 30% on actual game design? Now it’s reversed. He spends 10% of his time directing AI asset generation and 90% on making the game actually fun, which is the part that still requires human judgment and creativity.

And purely AI driven games that got generated on the fly? Turns out they mostly sucked and nobody wanted them. When a great story suddenly goes off the rails because the AI made a dumb decision, that’s not fun. Neither is getting stuck in a random corner of the board because the AI botched the physics. Turns out storytelling still needs a deft hand.

This pattern repeated everywhere. The routine stuff got automated. The human judgment, creativity, and relationship-building became more valuable than ever in the age of AI.

By 2028, the fastest-growing job category was “AI integration specialist,” people who help businesses figure out which AI tools to use and how to implement them without screwing everything up. Median salary: $95,000. Required education: none of these people have computer science degrees. Most of them came from operations, project management, or customer service backgrounds.

Then there’s “synthetic media director,” people who art-direct AI-generated video, making sure it’s coherent, emotionally resonant, and actually serves the story. They’re making $120,000-$200,000. Their backgrounds? Film school dropouts, YouTubers, wedding videographers, former Etsy crafters who learned the tools and had good taste.

“AI personality auditor” is now a standard corporate role. “Training data curator” is a whole profession. “Prompt architecture consultant” is a thing, and some of them are billing $300/hour.

But here’s the wildest part: by 2030, an estimated 23 million people worldwide are making income, not full-time jobs necessarily, but real money, from what we’re calling “micro-studios.” One to five person teams using AI tools to create content, products, or services that would’ve required 50-500 people in 2026.

A two-person team in Lagos is making educational content that’s competing with Khan Academy. A solo creator in São Paulo is making meditation apps that rival Headspace. A three-person studio in San Diego is making indie games that are hitting top 10 on Steam.

The barrier between “I have an idea” and “I have a product” dropped to nearly zero. And when that happens, you don’t get fewer opportunities. You get an explosion of them.

Let’s go back to the film industry, because this is where the doomers were most confident in their predictions. “AI will destroy Hollywood!” “Actors and writers are finished!”

Here’s what actually happened:

In 2026-2027, there was a genuine rough patch. Studios started using AI for background characters, for crowd scenes, for establishing shots. Some VFX houses closed. Some junior positions disappeared. The doomers did their victory lap.

But by late 2028, something unexpected happened: the total number of people employed in film and TV production was higher than in 2026. Not lower. Higher.

Why? Because the cost of production dropped so dramatically that the market exploded. In 2026, about 150 films got theatrical releases worldwide. In 2030? Over 4,000. Not because there were more theaters, streaming had already won that war, but because the economics of production and distribution had changed so radically that niche films could find their audiences profitably.

A film that needed to make $100 million to break even in 2026 could break even at $15 million in 2030. That meant filmmakers could take risks. When you’re gambling with all the money it takes to make a film now you don’t take risks. You can’t afford to. The price of failure is corporate beheading.

So, if you’re an entertainment industry exec who wants to keep their job, you’re not going to gamble on the strange or the sublime. Risk is the enemy. Instead, you’re going to clone what already works. You greenlight “John Wick,” but with a chick. You order up “Fast and Furious 14: The Search for More Money.” You remake a classic, hoping nostalgia will cover for a lack of new ideas.

But when AI changed the way it all worked, it rewrote the rules. That meant weird, personal, experimental films could find funding. Which meant the monoculture started to fracture into a thousand microcultures, each getting the content they actually wanted rather than the lowest-common-denominator product that studios had to make when each film required $300 million in investment.

Yeah, the $300 million tentpole blockbuster became rarer. They flipped that money into a series because they could now produce Game of Thrones for the budget of a Miramax flick in the 1990s. The $20 million film became ubiquitous. And you know what? Most of those $20 million films were more interesting than the algorithmic superhero content we were getting in the 2020s.

Look, I’m not going to pretend this was all sunshine and abundance. There were real casualties. The transition from 2026 to 2028 was messy as hell.

If you were a mid-level VFX artist doing rotoscoping in 2026, your job probably doesn’t exist anymore. If you were writing generic marketing copy or churning out stock photography, that work evaporated. If your entire value proposition was “I can execute this routine task reliably,” you had a rough few years.

Some people didn’t adapt. Some people couldn’t adapt, not because they were dumb, but because they had spent 30 years mastering a skill that suddenly wasn’t worth what it used to be, and learning a completely new career at that age is genuinely hard.

The safety nets helped. Most developed countries had implemented some form of transition assistance by 2029, though the U.S. was predictably late and half-assed about it. But even with support, the psychological toll of having your expertise devalued through no fault of your own was real.

I’m not going to minimize that. The micro story of creative destruction is often painful even when the macro story is positive.

But here’s what you have to know in 2026: the transition period is always the hardest part. Once you’re through it, once the new equilibrium establishes itself, things stabilize. And the new equilibrium is almost always better than the old one for most people.

I’m writing this in 2030 because I want you to understand something: the people who were screaming about AI-driven unemployment in 2026 weren’t stupid. They were looking at real disruption and real pain points. But they made the same mistake humans always make during technology transitions: they assumed that the immediate displacement was the permanent outcome.

They looked at short-term job losses and extrapolated to long-term jobless dystopia. They looked at specific tasks being automated and assumed entire professions would vanish. But tasks are not jobs. Jobs are the intricacy of a thousand little tasks and changing requirements and little intelligent decisions linking it all together. They fundamentally misunderstood how technology, markets, and human adaptability interact.

The intelligence boom between 2025 and 2030 followed the exact same pattern as every previous technology boom: short-term disruption, followed by adaptation, followed by a higher equilibrium with more opportunities and greater prosperity.

Yeah, the opportunities looked different. Yeah, some people struggled with the transition. But the net result, the thing you can see clearly from 2030 looking back, is that AI made us richer, not poorer.

The nurse can afford more. The teacher can afford more. The small business owner can afford more. Not because their nominal wages skyrocketed, but because everything got cheaper and their purchasing power expanded.

The aspiring filmmaker can actually make films. The game developer can actually ship games. The entrepreneur can actually start a business without needing $500,000 in capital.

That’s abundance. That’s what productivity gains actually look like when they ripple through an economy.

If you’re reading this from 2030, you’re probably nodding along thinking “yeah, obviously.” But I want you to remember something: in 2026, a lot of people believed the opposite. They believed AI would create permanent mass unemployment. They believed we’d need universal basic income or face societal collapse. They believed we were heading into a jobless future.

They were wrong for the same reason the Luddites were wrong in 1811, the same reason the Population Bomb writer was wrong, the automation doomers were wrong in 1960, and the people predicting that ATMs would eliminate bank tellers were wrong in 1975.

They confused task automation with job elimination. They assumed human wants were finite. They underestimated human adaptability. They failed to imagine the new opportunities that would emerge.

And here’s the thing: five years from now, when the next technology breakthrough happens, quantum computing, fusion power, molecular manufacturing, whatever—people are going to make the exact same mistakes. They’re going to look at the immediate disruption and predict permanent catastrophe.

Don’t fall for it.

Technology doesn’t destroy prosperity. Technology creates prosperity by making things cheaper, by expanding what’s possible, by eliminating the barriers between human vision and execution.

Yeah, the transition is messy. Yeah, some people get hurt. But the macro trend has been the same for 200 years: technology makes us richer, creates more opportunities, and expands human potential.

The intelligence boom was no different.

And whatever comes next won’t be different either.

If you’re reading this from 2026, and you’re scared about AI, here’s what you need to understand: the fear is normal. The disruption is real. But the outcome is going to be fine.

Not fine in a “everything stays exactly the same” way. Fine in a “the new equilibrium is better than the old one” way.

The skills that matter in 2030 are the same skills that have always mattered: creativity, judgment, taste, strategic thinking, emotional intelligence, and the ability to adapt. If you can do those things, you’re going to be fine. Better than fine.

The routine stuff, the “I can execute this task reliably,” that’s what AI handles now. Which means humans get to focus on the interesting problems, the creative challenges, the work that actually requires human judgment.

Is that a different kind of economy than we had in 2026? Yes. Is it worse? No way. It’s better. More opportunity. More creativity. More abundance.

The intelligence boom made us richer. And if you were betting against human adaptability and technological progress in 2026, well, I hope you didn’t bet too much.

Because the optimists were right. Again.

They always are.