Tag: insight

“Someday a generative AI will be able to create a release a complete videogame. Can you imagine that?“

Yes, I can. But I am very skeptical about the quality, the value, and the timeline for that.

The creative process is very uncertain and risky. Specifically, you could work for months on something and then earn nothing. Many non-creative people would like to mitigate that risk. I get that for the true capitalist that’s juicy.

Now, think about yourself as a Player. You are downloading a fantastic new game that you purchased. And you know that a machine made the whole game. As a Player, you know you have to beat some useless obstacle not created by a team of people. You don’t have a true mind challenging you and presenting an opera. A machine did that and a company is asking to pay for it.

Can something like that be appealing to the people?

As a developer think about passing your days writing prompts and editing the results. Or better, remove the editing part. You have an idea and TA DA! Compile a superb game. A game you feel you couldn’t even imagine. And you didn’t have to pitch, discuss, get approvals. You didn’t have to struggle to find the right art style, the good coding structure, the best mechanics. You have it all in a few minutes.

Now think about it: how would you feel if you have to sacrifice one of the most important parts of being a person for speed, success, and revenue?

At the present time, I feel that there will be a split in game developers in case of the realization of this crazy prediction.

A tool without a good mind can become a piece of garbage, an obstacle, a weapon, and many other things. The problem is never the tool, but the fact that not any tool is useful to everyone.

That’s why I tend to stay suspicious when I see best practices. That is why I don’t use any tool without making it mine, somehow.

If you give me a space rocket, which can be seen as a space travel tool, I will probably sell it. Or make a mess, I don’t know. The problem is that I am not prepared to use that tool. It’s amazing, but just not for me.

I see a dangerous trend on social networks like LinkedIn. It is proven that strong opinions spread better with the algorithm. People tend to make declarations like brainstorming are useless. Roadmaps are killing your product. Design documents are a waste of time.

All of those things are just tools. Great games have been created by using those tools at certain points. It’s a matter of mindset, not tools.

Returning to our example, best practices are great for unlocking meaningful discussions. But most of the time, they are bad to just speed up the process. We can say that the no.1 best practice is that you need time to make things simpler and better.

Over the last 10 years, I have assisted in the rise of many services and information providers that offer concrete predictions based on data. I had to quit a big company too, because of that. They were also testing game concepts based on the people’s responses to some text. So everything we proposed was texted out using a text redacted by someone with a high salary and very few things to do.

I went to a local indie fair where a friend pitched a game to publishers. One of them said, “Don’t you know that games with vegetables do not work?”. Then we ask why the publisher’s business model doesn’t work. It’s because of things like that!

Games are made by people who believe in a concrete vision and work hard to deliver. Many games will fail, because maybe people are not interested, because of the quality or many other factors. But you cannot use data to predict the success/failure of something without having tested it out.

Data-driven (or better, data-informed) development works when you work with concrete data from your things and compare them with your past. It doesn’t work when you read data from others and try to replicate it blindly. Sometimes it works out, but it’s because of other factors. It’s always because there is a passionate team behind that did something great. And lots of luck, the state of the market, and factors you can never control.

You can avoid risks by going iterative, of course. You can test prototypes and demos and see the actual reaction of people to that. That is good. But you cannot assume “this kind of game with these features is working in the market, so if we made something like this we would probably have success”.

When we play games for work we often misunderstand the real motivations for the true fans to play that game.

Maybe we are working on a social casino game but we don’t really like this kind of games, as players. So that we study that game from a cold perspective. And we can also think that it would be easy to replicate mechanics and dynamics. Social casino games have really simple interactions, right?

Then the degeneration of that discourse leads to something worse. We start believe that a machine can build this in series. Today everyone is talking about AI, but also before of that there were kinds of fun experiments.

But then we notice that these kind of experiences are hardly successful out there. Best social casino games have teams of more than 50 people working hard and passionately every day to deliver the best experience.

To me there is a silent contract between the Player and the Designer. For designer I mean the whole team, also. That silent contract states that there is a creator from one side that propose a challenge to another person on the other side. The motivation to play (or fun, if you prefer) comes mainly from this contract.

You decide to play a game. You know that the game has been made by someone. Part of the challenge is to beat that someone’s mind. If you read reviews of games you will notice that many comments go in the directions of creators.

What happens if the Player know that a machine created that game? Will they give these games the same value? People are smarter (and dumber) than we think.