Field notes Volume 01
I still remember the smile on a friend’s face when he built his first calculator in high school.
It wasn’t much: a simple program that could do basic arithmetic. Nothing like the programs we can write for calculators today. And yet, to him, it was something special.
He had an idea. He wrote the code, learned and relearned, and eventually got it to work. He had built something.
I don’t remember the code, the language, or how long he spent on it. I remember his smile. Sometimes I wish we celebrated that feeling as much now as we seemed to then.
When building something meant something
Computers and the internet gave us a new way to express ideas and share them. People who learned to create with those tools found themselves close to the edge of a technological shift. But becoming a programmer wasn’t easy.
You had to learn a language, understand data structures, work with databases and memory, and make sense of frameworks that could be baffling at first.
You wrote programs, watched them fail, and looked for the problem. Sometimes hours of debugging came down to one stray character.
There was no one to hold your hand. You had to find the answers yourself. And when the program finally worked, it could be hard to explain the pride you felt to someone who hadn’t done it themselves.
But that wasn’t the point, was it?
For a student, it might be a small application that finally works. For an engineer, a fix to a production issue affecting thousands of people. For a creator, it might be watching someone use something that didn’t exist a month earlier. Each experience says: I can learn this, work through the uncertainty, and make something real.
When someone looked at what we had made and asked, “You built this?”, there was a particular pride in answering, “Yes, I did.”
The way we build has changed
AI can write functions and applications, explain unfamiliar ideas, suggest solutions, find bugs, and speed up the work of making things. Tasks that once took days can take hours. Work that took weeks can take days. That isn’t necessarily a bad thing.
AI can make software development more accessible, help people learn, and let someone try an idea that once felt out of reach. People can build things they didn’t think they were capable of building. That deserves to be celebrated.
But celebration can come with an unintended cost: we can start to devalue everything else.
Imagine spending weeks researching a problem, deciding how a product should behave, testing approaches, working through failures, and making dozens of decisions. You use AI to help write some of the code, perhaps most of it, and eventually you finish the product.
You show it to someone. Their first reaction isn’t to ask what it does or what you learned. It’s to ask how much of it the AI wrote.
Suddenly, the work behind the result is in doubt. Are you no longer worthy of credit because you used a tool?
“Oh, so the AI did it?”
Just like that, weeks of thought and effort are reduced to a soundbite.
The work behind what we make
I think we’re starting to confuse the means of creation with the people who make something useful. A tool can produce an answer, but someone still has to decide whether it’s the right answer.
Someone has to check whether it solved the problem, introduced new ones, and will hold up when circumstances change or something goes wrong.
AI can make parts of a process faster or easier without removing the need for judgment. And effort can be hard to see from the outside. Something difficult can look simple because someone worked hard to make it that way. We already know this from practice: a skill that looks effortless often took a long time to learn.
AI adds another wrinkle. If a tool makes a task quick for one person, they may not realize how hard it would be for someone else. Sometimes the tool really does most of the work, and we should be honest about that. Other times, the hardest part wasn’t producing the output. It was knowing what to ask for, judging what came back, and making it work.
We’re good at seeing what’s in front of us. We’re less good at noticing the invisible work around it. Appreciation may be becoming another casualty of progress.
Think about a student learning to program. Their first project is a calculator, then maybe a game. Over time they try more ambitious ideas and apply what they’ve learned. Every small achievement shows them they can take on the next challenge.
Now imagine that every time they share something they’ve made, the response is always the same: “You used AI.” They might keep learning, but sharing their work could start to feel like an invitation to defend themselves. Instead of wondering what they can build next, they may start wondering whether anyone will consider them capable of building it.
This isn’t only a problem for programmers. Writers, designers, artists, researchers, analysts, and people in almost every profession face a similar question: if a tool helped you create something, how much credit do you deserve?
Does what you made become less interesting because you had help? At what point does assistance become replacement, and who gets to decide?
As our ways of working change, we should be careful not to dismiss someone’s thought and skill because we can speed up part of the process. Productivity matters, but so do substance, experience, and the ability to understand a difficult problem and solve it.
The smile is still there
I don’t think AI has to take the joy of creating away from us. It could help more people experience it: people who might not otherwise have tried programming, people who need a working prototype to explore an idea, and people who would rather spend less time on repetitive work and more time on interesting problems.
There is still a lot to be proud of. Maybe being a creator will involve new skills: directing tools, understanding their limits, evaluating what they produce, and combining the results into something useful.
But as our tools become more powerful, our ability to recognize one another’s work needs to grow too. There should still be room to recognize the beginner building her first calculator, the engineer debugging a vexing problem through the night, and the independent creator who used AI to help bring an idea to life.
Not because every output is extraordinary or deserves applause, but because learning, solving problems, and bringing ideas into the world are meaningful parts of being human. We can appreciate a tool without dismissing its user. We can acknowledge that someone got help without assuming they did nothing.
The question I can’t stop thinking about
I started this essay with a simple sentence: “I built it.”
Now it often seems to come with an explanation:
“I built it, but I used AI.”
Why do we feel the need to explain that before anyone has even asked?
Maybe we’re still figuring out what it means to create something ourselves when machines can do some of the heavy lifting. Maybe we’re trying to separate the value of what we make from the effort it took to make it. Or maybe we’re so impressed by what technology can do that we’ve stopped asking what it should do for the people using it.
I don’t want to return to a world where building things is unnecessarily difficult. I don’t want people to spend hours on problems a good tool can solve in minutes. And I don’t want anyone to feel that using a tool makes them unworthy of recognition.
My friend’s calculator wasn’t special because it had many lines of code, used complicated ideas, or took a long time to build. It was special because he had an idea, learned through trial and error, and made the program do what he wanted.
It was special because of the smile on his face when it worked. I hope we never forget to see that smile.
Perhaps “I built it” isn’t dying because we’ve lost the ability to create. Perhaps we’re slowly forgetting how to appreciate the creator.