It’s not, they are correct. There are so many telltale signs of AI code it’s not even funny. The most obvious being the absolutely garbage comments that people invariably leave in. And the god awful naming of things.

But it’s more than that. If you’re in this industry long enough, you get pretty good at reconstructing a real author’s thought process when they wrote the code. Part of understanding code is understanding why it was written the way that it was, which means understanding how the author thought. Sure, there was plenty of garbage code and stupid thinking, but it was still thought and usually had its own kind of internal consistency. AI code has no thought process, no reason. It is pure mimicry, an amalgamation of millions of authors all at once. It has no internal consistency. It produces code no human ever would, because it doesn’t make any fucking sense. It’s like reading an alien language, where the constructs it produces are so aberrant to how any human would ever think that it could be nothing but an LLM.

I definitely can’t tell you everything about a piece of code by reading it, but I sure as hell can smell an LLM in it, because it fucking stinks.

I work remote, so no.

Hmm, every company monitors their web traffic. That’s standard operating procedure.

I’m not sure what you mean by “standard DB queue” (perhaps you mean a message queue, I guess?), but yeah Redis (or really, Valkey, now, since Redis tried to change license on everyone) is a very important tool in the toolbox for system design. In-memory databases trade persistence guarantees for raw throughput, and are very well-suited for different workloads than a traditional database is. It’s great for caching, rate-limiting, realtime analytics, leaderboards… Basically anything with ephemeral data or data that can easily be reconstructed from some other source of truth. It’s an optimization tool that can significantly reduce the load on your primary application database for certain workloads (and achieve higher throughput).