[ACCount37]

I have some repair shop experience, and in my experience, a massive bottleneck in repairing truly complex devices is diagnostics. Often, things are "repaired" by swapping large components until the issue goes away, because diagnosing issues in any more detail is more of an arcane art than something you can teach an average technician to do.

And I can't help but think: what would a cutting edge "CLI ninja" LLM like Claude be able to do if given access to a diagnostic interface that exposes all the logs and sensor readings, a list of known common issues and faults, and a full technical reference manual?

[BatteryMountain]

So try it. Ask claude to call the tool that tails the diagnostics/logs. For some languages, like in android or C#, simply running the application generates a ton of logs, never mind on OS level, which has more low-level stuff. Claude reads through it really well and can find bugs for you. You can tell it what you are looking for, tell it a common/correct set of data or expectations, so it can compare it to what it finds in the logs. It solved an issue for me in 2 minutes that I wasn't able to solve in a couple of months. Basically anything you can run and see output for in the terminal, claude can do the same and analyse it at the same time.

[ACCount37]

For many cases, I'd have to build the tooling first. For many more, the vendor would have to build the tooling into their products first.

Cars have the somewhat standardized OBD ports that you could pry the necessary data out from, but industrial robots or vending machines or smartphones? They sure don't.

But what inspires this line of inquiry is exactly the kind of success I had just feeding random error logs to AI and letting it sift through them for clues. It doesn't always work, but it works just often enough to make me wonder about the broader use cases.

[jvanderbot]

Ah, would you have to build it or would "you" (an AI) have to build it.