Source: TechCrunch
As AI agents gain autonomy to execute multi-step tasks with minimal human intervention, companies face a genuine control problem—agents operate too fast and across too many domains for traditional logging and human review to catch failures or drift in real time. Rather than bottleneck agents with restrictive guardrails, the emerging solution is deploying a second layer of AI systems designed specifically to monitor, flag, and constrain agent behavior. This trades one set of alignment risks for another while keeping productivity gains intact. It also creates a new vendor category and reframes how companies think about AI safety: not as a constraint on deployment, but as a parallel infrastructure problem requiring its own specialized tools.