When every line of code generated by Cursor’s AI assistant is captured, replayed, and tied to an engineer’s identity, you gain full visibility into AI‑driven changes through session recording. That visibility turns a mysterious AI edit into a traceable event you can audit, debug, or roll back at a moment’s notice.
In many internal SaaS deployments, teams give the Cursor agent a static service account or embed a long‑lived API key directly into the code‑generation pipeline. The agent talks straight to the internal code‑host, the database, or the git repository without any intervening control point. No one sees what the AI actually sent, and no log ties the operation back to a human request or what exactly was transmitted. The result is a blind spot: a powerful assistant can write, delete, or alter production assets without any record of who triggered the action.
Session recording matters for three reasons. First, compliance frameworks often require evidence that every change to critical systems is attributable. Second, debugging AI‑generated code becomes dramatically easier when you can replay the exact request and response sequence. Third, security teams can spot anomalous patterns, such as an AI assistant repeatedly issuing destructive commands, before they cause damage.
The obvious fix is to add a logging layer, but most teams stop at the identity side of the problem. They provision OIDC or SAML tokens, assign the AI a group, and assume that the token itself is sufficient proof of who acted. That approach decides *who* may start a connection, but it never observes *what* travels over the wire. Without a data‑path enforcement point, session recording cannot be guaranteed.
hoop.dev provides the missing data‑path control. It is a Layer 7 gateway that sits between the Cursor AI agent and the internal services it needs to reach. By proxying the connection, hoop.dev can inspect the protocol, capture every request and response, and store the interaction for later replay. Because the gateway runs outside the AI runtime, the agent never sees the underlying credentials, and the recorded session is bound to the original identity token.
Conceptually, the flow works like this: a gateway instance is deployed in the same network segment as the internal services. The Cursor endpoint, whether it is a git server, a database, or an HTTP API, is registered as a connection in hoop.dev, and the required service credentials are stored only in the gateway. When the AI assistant initiates a request, it authenticates to hoop.dev using an OIDC token. hoop.dev validates the token, verifies group membership, and then forwards the request to the target service. As the traffic passes through, hoop.dev records the full session, applies any configured masking rules, and optionally requires human approval for risky commands. The resulting audit trail is tied to the original token, providing a complete record of the AI‑driven operation.