Neural networks keep mercilessly replacing us. This time, in investigations and debugging.
Given: an editor lost a bit of content. Clicked something and everything was gone. Never happened before, and here we go again.
— Hey Claude, here are cleaned-up database dumps from several sites, an editor was doing something on the master, and content disappeared on several sites. Find where it went and figure out what the editor clicked. Just be careful, it is three gigs.
— Avec plaisir. And I will not parse the dumps, don't you worry.
He looks at the content synchronization logic. Spins up mysql containers in Docker on his own, loads the dumps. Unwinds the page revisions across the tables. 15 minutes later he writes a report: right here, on such-and-such date and time, the editor unsubscribed from the content and everything was gone. Here he restored the subscriptions, but it was too late, ha-ha-ha. And here is what to configure so that it is never too late again. But that is for another time, for now, sorry, the content cannot be brought back. Thank you, you are welcome, write again.
And how could this be automated even further? Let him into production, perhaps, and into Jira, so that he explains it to the editor himself? Some people, I know, already do, but we are still scared to let him into production. And not every project allows it anyway.
And what comes next at all? What did they do in Frank Herbert's books to completely ban all these computers?
upd: Humans in leather are still needed after all.
A thorough study of the report revealed several problems that the AI decided not to explain and that, in principle, cannot be explained by the report's findings. I dug deeper myself into places the neural network could not reach and found a bug in a third-party SaaS service used in the project.
I think Claude would have found it too, but who would let him in there.
I feel mighty. Take that, robots!