Technology has always changed the way we work.
I’ve been working with technology for many years, from mechanical systems and industrial machines to software, games, cloud services, and artificial intelligence.
But few technological changes have felt as significant as the rise of generative AI.
AI is no longer something that exists only in research papers or science fiction.
It is already part of the tools developers use every day.
And I believe we are still at the beginning of understanding what that means.
AI Is a Tool
One of the biggest discussions surrounding AI is whether it will replace programmers, artists, writers, and other professionals.
I don’t think the question is quite that simple.
Throughout my career, I’ve seen technology replace some tasks while creating entirely new ones.
A better question is:
What can we accomplish when humans and these new tools work together?
For me, AI is a tool.
A very powerful one.
But still a tool.
A calculator didn’t replace mathematicians.
A compiler didn’t replace programmers.
Game engines didn’t replace game developers.
And AI doesn’t eliminate the need for people who understand what they are trying to build.
The Difference Between Generating and Understanding
AI can generate code remarkably quickly.
It can explain an API.
It can suggest an architecture.
It can help debug a problem.
It can generate documentation.
It can translate text.
It can create images, audio, and other forms of content.
But generating something and understanding something are not the same thing.
If I ask an AI to write a piece of C++ code and it gives me something that compiles, that doesn’t necessarily mean the code is correct.
It might have a subtle performance problem.
It might introduce a race condition.
It might use an inappropriate architecture.
It might solve the immediate problem while creating a much larger one somewhere else.
This is why experience still matters.
You need to know enough to evaluate the answer.
AI Makes Knowledge More Accessible
There is another side of AI that I find much more exciting.
It lowers the barrier to learning.
Someone who has never used a particular technology can ask questions and receive explanations immediately.
A developer can explore an unfamiliar API without spending hours searching through documentation.
Someone learning programming can ask for examples and explanations adapted to their level.
An experienced developer can use AI as a second pair of eyes when investigating a problem.
This doesn’t remove the need to learn.
It changes how we learn.
And I think that distinction is important.
Programming Is Changing
I’ve been programming for many years, and the way we write software has changed significantly during that time.
The tools are different.
The languages are different.
The frameworks are different.
The expectations are different.
AI is simply the next major change.
Developers will increasingly spend less time typing repetitive code and more time defining what needs to be built, evaluating solutions, designing systems, and making decisions.
That doesn’t make programming less important.
In some ways, it makes understanding software even more important.
When generating code becomes easier, knowing which code should exist in the first place becomes more valuable.
AI and Game Development
The impact on game development could be particularly interesting.
Games contain enormous amounts of content and systems.
Characters.
Animations.
Dialogue.
Quests.
Textures.
Concept art.
Sound effects.
Music.
Level design.
AI behaviors.
Tools.
Testing.
Localization.
And much more.
AI can potentially assist with many of these tasks.
But there is a critical distinction between creating content and creating a game.
A game is not simply a collection of assets.
Someone still needs to decide what the player should experience.
Why does a character exist?
Why does a mechanic exist?
Why is a particular level designed this way?
What emotions should the player feel?
What makes the game different from everything else?
Those are creative and design decisions.
AI can help with them.
But I don’t believe they can simply be automated away.
The Indie Developer
For indie developers, AI could be especially transformative.
One person can now access tools that previously required an entire team.
A programmer can generate placeholder assets.
A writer can brainstorm ideas.
A developer can translate content.
A designer can explore concepts.
A solo developer can create prototypes much faster.
That doesn’t mean one person can suddenly produce a AAA game.
There are still enormous limitations in time, money, expertise, and production capacity.
But the amount of leverage available to a single developer is increasing.
And that is exciting.
The New Skill: Knowing What to Ask
Working with AI has also introduced another skill that I think will become increasingly important.
Knowing how to communicate what you want.
A vague problem produces a vague answer.
The better you understand the problem, the better you can describe it.
And the better you can describe it, the more useful the AI becomes.
This creates an interesting feedback loop.
The more you know, the more effectively you can use AI.
And the more effectively you use AI, the faster you can learn new things.
AI Doesn’t Remove Responsibility
There is one thing I don’t think should change:
The developer is still responsible for the result.
If AI generates broken code, the responsibility isn’t the AI’s.
If AI introduces a security vulnerability, someone still has to fix it.
If generated content violates a license or creates legal problems, the person using it still has to deal with the consequences.
Using AI doesn’t remove responsibility.
It increases the importance of reviewing what it produces.
That is why blindly copying AI-generated code is dangerous.
The same applies to anything else AI creates.
Creativity Isn’t Just Generation
There is also a common misconception that creativity means generating ideas.
I don’t think it does.
Creativity is also about choosing.
You can generate a thousand ideas.
The difficult part is deciding which one is worth pursuing.
You can generate hundreds of character designs.
Which one belongs in your game?
You can generate dozens of mechanics.
Which one actually improves the experience?
You can generate thousands of lines of code.
Which architecture should your project use?
The ability to generate possibilities is powerful.
But judgment is still required.
What Comes Next?
I don’t know exactly where AI will take us.
Anyone who claims to know precisely what development will look like ten or twenty years from now is probably making a very confident guess.
Technology has a habit of surprising us.
But I do believe that development is going to change significantly.
The tools will become more capable.
The barrier to creating software will continue to decrease.
Small teams will be able to accomplish more.
Individuals will have access to increasingly powerful capabilities.
And the developers who learn how to use these tools effectively will probably have a significant advantage.
Embracing the Change
I’ve spent my career adapting to technology.
I’ve gone from working with physical machines to software systems, from traditional applications to games, from desktop applications to distributed systems, and now into a world where AI is becoming part of the development process.
I don’t see AI as something we should simply fear.
I see it as another technological shift that we need to understand.
There will certainly be problems.
There will be misuse.
There will be jobs and tasks that disappear or change.
There will be new challenges that we haven’t even anticipated yet.
But there will also be new possibilities.
And for someone who enjoys building things, that’s the part I’m most interested in.
Technology keeps changing.
The tools keep changing.
The way we work keeps changing.
But the fundamental question remains the same:
What can we build with what we have today?
That’s what keeps me interested in technology.
And that’s why I’m looking forward to seeing what we build next.