How do you safely deploy agents to multiple users?

"It's really, really hard to roll out agents to production," Adarsh acknowledged. Gartner's 2026 Hype Cycle for Agentic AI affirms this, and notes that fully autonomous agents are not ready for most enterprise use cases, and that human oversight remains essential. In Adarsh’s experience, the secure way to deploy agents is through a staged model that limits the scope of failure at every step. Start in a personal-assistant context, where if the agent fails, only one person is affected. From there, connect it to tools in a sandbox without real data.

Run your eval suite to stress-test performance before any real users get involved. When the evals clear, you can test with real users but not real data. If the agent succeeds in each stage, you can execute a phased rollout. "If the agent fails, the impact is on the order of magnitude of failing for one person, as opposed to maybe a million people," he said. "The key is not jumping the gun and following the whole process.