I've been losing interest in programming because AI can now handle much of the coding and explain technical systems on demand. I used to build small projects to explore ideas, understand how things worked, and enjoy programming and system design for their own sake. Now I can ask an AI for the explanations and have it generate the implementation, which makes personal projects feel pointless.
I'm also unsure how to present anything I build as my own work when people may assume it was mostly generated by AI. It feels like anything I create will just become part of an endless pile of mediocre AI-generated software. I don't particularly enjoy making products for their own sake; I enjoyed the problem-solving and engineering process. Has anyone else felt this way, and how are you finding motivation or redefining what it means to create something in the age of AI?
5 Answers
A lot of the value has shifted from typing code to defining the right problem, designing a good solution, reviewing the output, and making sure the result actually works. AI-generated code is often overcomplicated or subtly wrong, so understanding systems, debugging, testing, and making sound architectural decisions still matter. A project can be your work because you chose the goal, made the design decisions, evaluated the trade-offs, and took responsibility for the result.
AI doesn’t make personal projects meaningless any more than cameras made painting meaningless or recorded music made playing an instrument pointless. If the activity itself was rewarding, you can still do it without optimizing for market value or proving that every character was typed by hand. If you genuinely no longer enjoy coding, though, that may be a sign to explore a different kind of work rather than forcing yourself to continue.
If you enjoyed programming because of the reasoning and discovery, keep ownership of those parts. Design the system yourself, draw the data flow, make the trade-offs, and predict how the experiment should behave before asking AI for help. Then use it for boilerplate, repetitive code, or implementation details. It can act like a very fast keyboard, but you’re still doing the engineering if you’re making and validating the important decisions.
The calculator analogy fits here: engineers stopped doing arithmetic by hand, but they still had to choose the right equations and check the results. The danger is treating generated code as correct without understanding or testing it.
You don’t need a grand reason to do something in your spare time. If coding is fun, do it because it’s fun; if it isn’t, take a break and follow whatever curiosity feels genuine. For work, the practical answer may simply be learning to use these tools while building expertise that AI can’t reliably supply on its own: understanding users, choosing worthwhile problems, communicating with people, and judging quality.
I still write most things manually and use AI more like a search tool or reference. I care about improving as an engineer and understanding the code, not just producing a large volume of output I can’t explain. AI can be useful, but handing over the architecture and all the thinking can remove the exact part of programming that made the work enjoyable.
That seems like a good middle ground. Avoiding AI completely probably isn’t realistic, but letting it replace your understanding and design skills is a different problem.
The comparison isn’t perfect because some skills do lose professional value when technology changes. But that doesn’t stop a person from practicing them for enjoyment or choosing projects where judgment, taste, and curiosity matter.