Seeing that PSU and Duke published a paper on how to automatically assign blame when multi-agent system tasks fail—put simply: a bunch of AIs cooperate to do the work, they mess it up, but whose fault is it?
My first reaction was to laugh out loud. After writing code for more than ten years, the most annoying thing is that whole “layer-by-layer investigation” after something goes wrong in production. Now, the AI team has to go through it too. The difference is that humans can still use facial expressions and tone to shift the blame, while among agents it’s only logs.
They say this is considered a key part of the agent development lifecycle. Makes sense. Multi-agent systems are being hyped to the skies—yet even the accountability tooling isn’t ready, so they go straight to production. Isn’t that exactly what we did back then when we deployed to production barehanded?
My first reaction was to laugh out loud. After writing code for more than ten years, the most annoying thing is that whole “layer-by-layer investigation” after something goes wrong in production. Now, the AI team has to go through it too. The difference is that humans can still use facial expressions and tone to shift the blame, while among agents it’s only logs.
They say this is considered a key part of the agent development lifecycle. Makes sense. Multi-agent systems are being hyped to the skies—yet even the accountability tooling isn’t ready, so they go straight to production. Isn’t that exactly what we did back then when we deployed to production barehanded?