19 June, 2026
What it truly means to be productive in an era where AI can do (almost) everything.
I remember a time where my group at school was asked to make a working video game. I spent the whole week writing the core engine that allowed it to run, and my teammates were surprised that I was able to go that far in such a short time: having a fully working map, and a working character that can move around.
But now, if I were to do the same thing, people would just use AI to generate the code for them, and they would be able to get a working game in a matter of hours, if not minutes.
That got me thinking: before, when AI was not as prevalent as it is today, I realized that measuring productivity was simple: if I got good scores and understood the material, I was productive. But now with AI, everyone can still get good scores without understanding the material.
This shift raises an important question: what does it mean to be productive in an era where AI can handle complex tasks quickly?
What is productivity? #
For me, productivity is where I have a list of TODOs and I can check them off one by one, and at the end of the day, I feel accomplished. It has both the "quantity" factor as a measurable unit, but also the "emotional" factor as a subjective unit. The achievement of complting tasks gives a sense of satisfaction, it makes people happy. And at the same time, it brings quantity to the table, like getting high scores, good grades, a promotion, a raise, etc.
It also has a "time" factor, and this is where the problem lies. If the time it takes to complete a task is shorter, great - you are more productive. But this is only true if the quality of the end product is the same. If the quality is lower, then you are not productive, you are just fast. And that's cheating.
But more importantly, the time factor is not just measured by the time it takes to complete a task, but also by the time it takes to think, reflect, and learn. If we are constantly rushing to complete tasks, we may not be giving ourselves enough time to think critically and creatively, which can lead to a lack of innovation and growth.
The false sense of productivity #
So, how does AI affect the way we perceive productivity?
It can make us feel more productive because we can accomplish tasks faster with comparable quality (of course, not the same, but comparable). The result is that we can get more done in less time, which can lead to a false sense of productivity. We may feel like we are achieving more, but in reality, we are just doing things faster to make space for more tasks.
The invisible danger is that we may start to deprioritize the time we spend on thinking, reflecting, and learning, which are essential for long-term growth and development. We may become more focused on quantity over quality, and this can lead to burnout and a lack of fulfillment in our work.
Perhaps productivity should be measured not by the speed of completion, but by the creativity, critical thinking, and problem-solving skills that humans bring to the table.
And that's the thing people often overlook: in the age where many things can be converted to money, the value of human ingenuity and the ability to think outside the box becomes harder to quantify.
A concrete example #
One example I encounter often is people making their first contribution to open source projects using AI to generate the code for them.
From their perspective, it makes sense: they contributed to the project, they have something to put on their resume, the checkbox is ticked. But in reality, they haven't learned anything meaningful. The contribution happened, but the growth didn't. And open source is not just about code, it's also about learning, collaborating, and being part of a community. If the AI did all the thinking, then who really made the contribution?
I wrote about this in more depth in my last post: [The value of open source](/the-value-of-open-source).
What should we measure instead? #
So how should we measure productivity in the age of AI?
First and most importantly, think of what you learned by doing the task. If you relied entirely on AI to get it done and couldn't explain what happened under the hood, then the task contributed to your output, not to your growth.
Second, think of alternative ways to do the task, even without AI. This doesn't mean you should not use AI, but it means that you should be able to "be creative" with the process behind it, so that you can improve the same thing in the future. (As a bonus: pay attention to the emotional factor: how it affects your decisions? For example: the feeling of frustration when we encounter a problem is what drives us to think outside the box and come up with new ideas.)
Third, think about the quality of the end product and the future plan. This is where human ingenuity and creativity come handy, and it's something AI can easily replicate. By focusing on quality over quantity, we can ensure that we are producing work that is meaningful and valuable.
In the end, I think the shift that AI brings to productivity is good, but it should be viewed as a tool to enhance our abilities, not a replacement for them. We should be mindful of the false sense of productivity that AI can create, and instead focus on the skills and qualities that make us truly productive as humans.