How Code in the Age of Artificial Intelligence Becomes Write-Only and Disposable - InfoQ
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How Code in the Age of Artificial Intelligence Becomes Write-Only and Disposable
Culture & Methods
How Code in the Age of Artificial Intelligence Becomes Write-Only and Disposable
Aug 20, 2026
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Ben Linders
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Artificial intelligence (AI) makes all code write-only, Phillip Mortimer argued in his talk Complexity and Creativity in Software Engineering at QCon London. It’s too dense to read, and tests define the behaviour and become the documentation. Code is also disposable; it becomes easier to rewrite than to debug. Humans can’t review AI-generated code at scale. Mortimer suggested automating reviews and letting agents self-heal software via observability. Intent decouples from implementation; developers should focus on creativity.
In the age of AI, all code is write-only, Mortimer argued. He quoted Eric S Raymond:
Write-only code is code so arcane, complex, or ill-structured that it cannot be modified or even comprehended by anyone but its author, and possibly not even by him/her.
Certain languages are write-only by design, trading readability for incredible power and performance, Mortimer said. He mentioned APL and regular expressions. These languages represent a kind of complexity that comes from extreme density.
A principle to deal with such code is that the tests define the behaviour:
When you write code that is too dense to read, the only way to understand what it does is through extensive test cases. The tests become the documentation for your code.
You read the input-output pairs, which tells you what the code is supposed to do, because you can’t read it very easily from the code itself, Mortimer said.
Another principle Mortimer mentioned was that the code is disposable. Write-only code is so hard to debug. It’s often easier to rewrite the code from scratch than it is to modify what you’ve already written. You keep the tests, throw away the code, and write it again, he said.
Humans can’t review generated code due to the sheer volume, Mortimer argued:
There’s no point in having humans try to review AI-generated code line by line, because humans very quickly become the bottleneck.
Mortimer suggested writing really detailed tests and automating your code reviews. He also suggested that software should heal itself:
A powerful thing to do is to have an AI coding agent listen to your observability platform, aggregate alerts over some time window, and start raising pull requests to fix the problems that it’s seen, starting with the most common ones.
We should decouple intent from implementation. AI uses natural language, making developers portable across programming languages, Mortimer said.
The role for the software developer today is creativity, Mortimer argued:
Creativity is iterative. It’s step-by-step improvement over long periods of time. Anyone can create. You just need to start working.
We should embrace a write-only principle, Mortimer argued. AI has solved the implementation problem; the...