I am not a great painter, not a composer, and certainly not a 3D artist. Yet I built a game on the side. Not a disposable prototype for a social-media post, but a finished tower-defense game about the Tyrolean uprising of 1809, with more than twenty levels, original music, custom graphics, and a choice between classic 2D and full 3D. It is public, it runs in a browser, and anyone can play it. And of course, I did not stop there. It eventually became eight very different game projects.

That is why I write about this differently from someone who merely collects demo videos. Once you have gone through the process yourself, you stop debating whether it can be done. You start calculating what happens when everyone can do it.

And the result of that calculation is uncomfortable.

Two changes that are constantly confused

When I show people what I built, almost everyone talks about the same thing: how it looks, whether the graphics are good, whether the game is fun. That is understandable, but it misses the central point.

Two completely different developments are happening at the same time. One concerns the quality of the result. The other concerns the length of the path required to reach it. Only one of them determines what happens to prices and how disruptive this becomes.

The leap everyone can see

The first change is visible, and it is a ladder with three rungs. The earliest AI-generated games looked like flat pixel worlds from the early 1980s: one screen, one mechanic, a splash of colour.

When I built the first version of 1809, the technology had already climbed one rung: a solid, playable 2D game, visually somewhere around the early 1990s. Shortly afterwards, the same idea was running as a complete 3D version in the browser, with camera movement, animation and terrain. Not after years. After days.

The ladder keeps rising. Browser games now include vehicle physics, water surfaces, day-and-night cycles and multiplayer servers. What game development assembled between 1980 and 2010 over thirty years of tools, engines and accumulated experience is now being traversed again in a matter of months. The gaps between the rungs are measured in days.

The leap nobody sees

The second change has little to do with how the final game looks. It concerns the route from idea to result.

Six months ago, a game like mine would have required a team: someone for the art, someone for the 3D models, someone for audio, someone for programming, someone for testing, and a lot of time. A year would have been ambitious. The project could have failed in any discipline I did not personally master.

My actual work looked different. I described what I wanted, let the model work, examined the result, criticised it and restarted the loop. Build, test, correct, build again. I could work on other projects while the AI continued through the night.

A year of interdisciplinary development becomes a day of loop engineering.

That is the sentence that matters. Not the graphics. Not the philosophical question of whether a machine is creative. The distance between an idea and a working result has collapsed, for anyone curious enough to try.

A recreation of the post-apocalyptic role-playing game Fallout shows how far this already goes. According to its creator, it was built in a single day and a single file, complete with an explorable world and dialogue trees. View the Fallout demonstration ↗

Why the threshold falls here

A text is one craft. An image is one craft. A piece of music is another. A game combines all of them and forces them to work together: concept, visual design, level design, 3D modelling, animation, mechanics, audio, programming, testing and marketing. If one layer fails, the product fails. That is why game development has long been one of the most demanding forms of knowledge work.

This is also why the current shift is underestimated. It is not merely AI assistance for graphics or code. A single system can keep many disciplines aligned for hours, inspect its own work and improve it. That used to be the definition of project work and the reason teams were necessary.

A Japanese castle town makes this especially clear. It began with a casual instruction to build a realistic castle town. Its creator reports that the model took its own screenshots, derived improvement loops from them and continued to the end without further guidance. View the castle-town demonstration ↗

The question is no longer whether a machine can perform one isolated task. It can coordinate, test and assemble. Once a bundle of a dozen disciplines can be produced in one extended run, smaller bundles will fall sooner, not later.

Why this becomes a pricing problem

The useful concept comes from monetary economics: AI is deflationary in digital markets. When the cost of producing a good approaches zero, supply multiplies while demand remains roughly where it was. The price falls, not because one company chooses to reduce it, but because nobody can continue enforcing the old price.

This does not affect only the margins on new products. It also devalues existing inventory. A finished game, training video, image collection or software module is worth less tomorrow when an adequate alternative can be generated at any time.

A catalogue of digital goods is no longer a store of value. It is perishable inventory with rapidly declining value.

The ceiling nobody can raise

Entertainment operates inside the attention economy. The time available in a human day cannot expand with the exploding supply of media. A model can build a game overnight. It cannot add a twenty-fifth hour to anyone's day.

There is also another development that requires no publication at all. I built my game because I wanted it. I did not buy it from somebody else. A person who generates a racing game using their hometown as the track, a management game based on their own company, or a learning app for their child never places it in a store. They simply stop buying something. These people do not appear in statistics as competitors. They disappear from the demand side.

When supply multiplies and demand remains fixed, the same cake is divided among many more producers. The scale effects that powered the software industry begin to weaken. Attention is never distributed evenly, so the broad middle suffers most.

What does not lose its value

The devaluation is not evenly distributed. Anything that can be regenerated at will becomes cheap. Value remains where the identity of the sender matters or where other people are part of the experience.

A brand retains value because it carries an expectation. A community retains value because a game where your friends are waiting cannot be replaced by a private copy. Live events, physical presence and accountability retain value. Where a person stands behind an outcome, a generation machine cannot offer the same thing. Curation also becomes more valuable in abundance: the person who can credibly identify the three worthwhile titles among ten thousand gains relevance with each new wave of output.

The limit I encountered myself

A game reports reliably whether it crashes, whether a character falls through the floor or whether the frame rate collapses. It does not report whether it is fun. I had to make that decision every time, and it was the part that took longest.

Much of the coming flood will therefore consist of technically competent but interchangeable products. That does not soften the market effect. Interchangeable titles still occupy store shelves, search results and attention. They make everything else harder to find.

Who comes next

I am not a game developer. I built a game because it was the most demanding digital product I could imagine and because I wanted to discover where the boundary was. That is exactly why the result transfers to other fields.

A campaign, an explainer video or an app: all are composite forms of creative and production work whose result can be viewed and judged, but each contains fewer moving parts than a game. Anyone who assumed their work was too multifaceted to automate is losing their strongest argument. It is not one craft that has been automated. Complexity itself is being automated.

The real miscalculation

Many people still think of AI as an answer machine, a better Google. Others debate whether a machine can ever be truly creative. That question is intellectually interesting and economically irrelevant.

For the developer whose title disappears among a hundred thousand alternatives, it makes no difference whether the model was creative in a strict philosophical sense. The same is true for the designer whose commission no longer arrives. Debating consciousness while supply and demand pull apart misses the actual event.

I built a game I could never have built before. That is the good news, and it applies to millions of people with an idea but without the required training.

The bad news is exactly the same. When everyone can produce what once required a team, production itself stops being the scarce part.

Everyone will be able to build. Fewer and fewer will be able to make a living from it.

Anyone who makes a living producing digital things should not ask whether their work is good enough. They should ask whether it can be generated.

Many people hope AI will create deflationary effects. It undoubtedly will. What they often overlook is why prices become cheaper: the people behind those entertainment products will be able to earn much less from them.

The labour of many human experts is what disappears from the calculation. In entertainment, that lost work cannot simply be compensated for by producing many times more supply.