Oh, that's so smart. So it effectively spell checks the code before you even see it. Exactly. If the linter comes back and says syntax error on line five, the system can either just hide that bad suggestion, or even better, it can feed that error message back to the model and say, you made a stake, fix it, and then show the corrected version to the user. So the stack here actually includes a feedback loop with a traditional compiler. It's a hybrid system. It's a hybrid system. It's using the best of the old world to validate the best of the new world.

This is where Shimoda talks about integrating a validation loop. A validation loop. Think about your own workflow as a developer. You write a piece of code, you try to run it, and it gives you an error. You read the error message, you go back to the code, you fix it, and you try again. That's pretty much my entire day, yes. A well-designed AI coding system can automate that loop. The LLM generates a block of code. The system then immediately tries to compile or run that code in a secure sandbox environment. If it fails, the system captures the exact error message from the compiler. Syntax error on line 5, unexpected indent, and feeds that error message back to the LLM as part of a new prompt.