Vendor-Neutral Agent Runtime Policy Layer That Enforces Org-Level Rules Across OpenAI Agents SDK, Anthropic Managed Agents, And Custom LangGraph Stacks
An HN asker put it directly: 'A runtime layer for AI agents that enforces execution boundaries: traces, replay, and a hard "no" when something unsafe is about to run.' OpenAI just shipped a native sandbox in the Agents SDK and Anthropic shipped Managed Agents, but both are vendor-specific and both are sandboxes for the code, not policy gates for the decisions (no rm -rf, no payment over $X without approval, no DB writes outside business hours). The gap is a Falco-for-agents that wraps any agent runtime with org policy.
Position as the open-policy-agent layer for agents... import once, declare rules in Rego or YAML, intercept every tool call regardless of which SDK fired it. The real product is the rule library, not the runtime. Get an enterprise design partner with a horror story (an agent ran rm -rf, an agent wired money) and use that to seed the rule pack.
landscape (3 existing solutions)
Vendor-specific sandboxes and observability are both well-served. Vendor-neutral, real-time policy enforcement that can pause or veto an agent's next tool call is not.