What I don't quite understand is why would one of the most advanced AI labs use rudimentary broken text match heuristics to track and detect abuse. Why not run simple inference on actual turns out of band, and if abuse is detected, adjust the quotas semi-retroactively.
They’re idiots who hacked together a shockingly useful tool by leveraging the billions of dollars they received from shamelessly hyping up chatbots. The Claude Code leak makes this very clear.
You seem to be implying that the company that employs the best chemists should therefore also make the best cakes. I don't see an obvious reason why this should hold true. I think it's fair to ridicule a bunch of chemists acting as master patissiers.
They're completely vibe-coding one of their flagship products. It's not unreasonable to consider that the people who took that decision are, indeed, idiots.
> most advanced AI labs use rudimentary broken text match
> It's vibe-coded
I called this out when I saw Claude Code CLI source code reach for regex on a certain task a while back and got told it was very unlikely that nobody reviewed the diff. Looks like the bar was lower than imagined.
Maybe running additional inference on all sessions to detect OpenClaw usage would require spending more money than they would save with that detection in the first place (which is the original goal). I also suspect the Claude Code team is just a regular software team without immediate access to ML pipelines (or competence to run them) to quickly develop proper abuse detection systems with extensive testing (to avoid false positives, which people would also complain about), and they're under pressure by the management to do something right now, so a regex is all they can do within those constraints.
