Summary: This article demonstrates how to move authorization inside the agent loop by inserting a Cedar-backed policy decision point into OpenClaw, so that every tool invocation is evaluated at runtime.
That’s precisely the issue I’m addressing. I think the answer is policy guardrails that limit what the agent can do. I don’t claim this is a solved problem by any means. There are still lots of interesting questions. No security is perfect, but where we’ve secured systems in the past it’s been through the application of rules and policies to limit action. I think the same tactic is useful here.
How do you see us handling the OpenClaw issue: https://www.technologyreview.com/2026/02/11/1132768/is-a-secure-ai-assistant-possible/
That’s precisely the issue I’m addressing. I think the answer is policy guardrails that limit what the agent can do. I don’t claim this is a solved problem by any means. There are still lots of interesting questions. No security is perfect, but where we’ve secured systems in the past it’s been through the application of rules and policies to limit action. I think the same tactic is useful here.