You've been called into the board room. It has been a sleepless 48 hours since you found the bug that took down all of prod: some long-forgotten intern had typed goto twice. You're barely keeping your eyes open, and now the CTO is asking you a good question you hadn't thought of:
"It's a dumb mistake, right? If it's so easy to make… where else have we made it?"
"Good question! I'll check real quick," you stammer out, as you rack your brain for the right command. Ah, there it is, good ol' grep. Grep for goto, and check the next line; if it's at the same indent level and is also a goto, it's probably the same bug.
Results arrive quickly. "It's only in one other spot..." you say, relaxing as you see the path. "Old test code in a deprecated project. I'll ping the committer to fix it." The room breathes a sigh of relief.
This scenario plays out every day in conference rooms around the world. And when it does, the next thing that happens is that your script gets forgotten. Soon enough, it rotates out of shell history, and maybe you even move on to another company. And with that move, the memory is lost, and inevitably the mistake—that "could have happened to anyone"—will indeed happen again.
lint.ai is your path to breaking this cycle. It enables you to take that code you just wrote, exactly as you wrote it, and drop it into a file in your repo. Now, every new commit, every new PR is checked with your code. Now, every line in the repo is not just searched retroactively, but protected proactively, forever.
lint.ai codifies and makes permanent the institutional memory of what went wrong and how to avoid a recurrence. And by easing the onramp for code quality enforcement to the lowest imaginable common denominator—a shell script—it allows you to capture rules in the moment and often at zero cost, by giving you a place to check in the code that has already been written and a framework that runs it on every future iteration.