Eval engineering: The missing piece of agentic AI governance
As artificial intelligence agents become more powerful, agentic AI governance becomes increasingly important – and yet, today’s governance solutions struggle to keep AI agents from going off the rails.
In my last article in this series, I discussed the state of the art for keeping agents on the rails: multiple diverse adversarial validators with multilayer validation.
The idea is straightforward: To keep agents on track without limiting their capabilities, deploy several independent validator agents that evaluate each agent’s performance, looking for problems.
Only when enough of the validators agree the agent is performing properly can it proceed with its task.
