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Joined 1 year ago
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Cake day: June 17th, 2023

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  • This is the kind of AI stuff that really annoys me. Looking at one of the mutation examples I didn’t see anything that wouldn’t normally be tested by a typical mutation tool. You took a simple, idempotent process and you got an llm to do it slower, less accurately, and using more resources.

    If you wanted to marry the two in a new and possibly useful fashion I would say use an llm to analyze the results of a standard mutation test and give guidance on what issues should be acted upon first. An off-by-one calculation could mean somebody loses a million dollars or it could mean a button is grayed out. Standard mutation tools don’t give you that context.









  • Got hands on experience with this. Wasn’t my design choice but I inherited an app with a database where one of the keys was tied to a completely separate database. I mean at the time it probably made sense but the most unlikely of scenarios actually happened: that other database, the one I had zero control over, was migrated to a new platform. All of those keys were synthetic so of course they were like, “Meh, why we gotta keep the old keys?” So post-migration my app becomes basically useless and I spent 6 hours writing migration code, some of it on off hours, to fix my data.

    So it’s questionable whether a foreign key of a completely different system is a natural key, but at the very least never use a key YOU don’t control.










  • I’ve never heard anyone explicitly say this but I’m sure a lot of people (i.e. management) think that AI is a replacement for static code. If you have a component with constantly changing requirements then it can make sense, but don’t ask an llm to perform a process that’s done every single day in the exact same way. Chief among my AI concerns is the amount of energy it uses. It feels like we could mostly wean off of carbon emitting fuels in 50 years but if energy demand skyrockets will be pushing those dates back by decades.