The developer built a tool that wrote code automatically.

Thousands of lines appeared instantly.

The senior developer asked, “Who understands this generated code?”

The developer replied, “The generator does.”

“And who understands the generator?”

Sitting with the Koan

Code generators represent one of the most transformative shifts in modern software development. They promise speed, consistency, and the ability to scaffold entire systems in moments. Yet this koan asks us to pause and examine a deeper tension: the relationship between creation and comprehension.

When we generate code, we’re introducing an intermediary between our intention and our implementation. The generator becomes an abstraction layer over our own thinking. This isn’t inherently problematic – all programming involves abstractions – but it requires us to be mindful about where we stand in the chain of understanding.

Consider what happens when generated code fails. Can you read it? Can you modify it? Can you explain to a teammate why it works the way it does? If the answer is no, then the code isn’t truly yours – you’re renting functionality from a tool you don’t fully understand. This is technical debt of a subtle kind, one that doesn’t show up in code smells or test coverage but reveals itself when the unexpected happens.

The deeper question – “who understands the generator?” – points to an even more profound challenge. Most modern code generators are based on large language models trained on billions of lines of code. Their inner workings are partially opaque even to their creators. We’re not just using tools we don’t fully understand; we’re using tools that, in some meaningful sense, no one fully understands.

This doesn’t mean we should reject code generators. It means we should approach them with awareness. Use them to accelerate the parts of development that are well-understood patterns. Use them to explore possibilities quickly. But don’t let them replace the fundamental work of understanding your system. Read the generated code. Question it. Refactor it. Make it yours.

The path forward isn’t to choose between writing every line by hand and automating everything. It’s to develop a practice of mindful generation – using these powerful tools while maintaining the chain of understanding that connects your intention to your implementation. The generator can write the code, but only you can take responsibility for it.