When an AI coding agent such as Devin writes code, runs tests, and pushes artifacts in a CI/CD pipeline, the lack of session recording means every command and response disappears from audit logs. If the agent makes a mistake, leaks a secret, or is compromised, there is no built‑in way to prove what actions were taken.
Because the agent authenticates directly to each target, the pipeline logs capture only high‑level job statuses. Detailed command streams, query results, and file contents vanish, leaving security and compliance teams without evidence. The cost of that blind spot can be a data breach, a failed audit, or costly remediation after a rogue change.
Why session recording matters for AI coding agents
Session recording provides a replay of every interaction the agent has with a backend system. With a complete transcript, investigators can answer questions such as:
- Did the agent issue a destructive command?
- Which rows were read from a production database?
- Were credentials exposed in a response payload?
Those answers are essential for incident response, for meeting audit requirements, and for building confidence that autonomous code generation does not introduce hidden risk.
Minimal identity hardening without recording
Most teams already enforce a baseline of identity controls. They configure OIDC or SAML trust between the CI system and the cloud provider, issue short‑lived tokens to the agent, and restrict the service account to the minimum set of roles required for the build. This setup solves the "who can connect" question and prevents the agent from using a permanent credential.
However, the request still travels straight to the target service. The gateway that could observe the traffic is missing, so the system cannot block a dangerous command, cannot mask a secret that appears in a response, and cannot create an audit trail. In other words, the identity layer alone does not give session recording.
Embedding session recording with hoop.dev
hoop.dev is a Layer 7 gateway that sits between the AI agent and the infrastructure it talks to. By placing hoop.dev on the data path, every protocol exchange, whether it is a PostgreSQL query, a Git push, or an SSH command, is inspected before it reaches the target.
When Devin initiates a connection, hoop.dev authenticates the OIDC token, verifies group membership, and then proxies the traffic. While proxying, hoop.dev records each request and response in a replay‑ready log. The recording is tied to the identity that initiated the session, so later reviewers can see exactly what Devin did, when, and against which resource.
Because the recording happens inside the gateway, the agent never sees the credential that hoop.dev uses to talk to the backend. This satisfies the three attribution categories:
- Setup: OIDC or SAML provides the identity of the CI job and the short‑lived service account.
- Data path: hoop.dev is the only place where enforcement logic runs.
- Enforcement outcome: hoop.dev creates the session recording that compliance and security teams rely on.
The result is a single control surface that delivers just‑in‑time access, optional approval workflows, inline masking of sensitive fields, and, most importantly for this article, session recording.
How the architecture fits into a CI/CD pipeline
A typical pipeline step that runs Devin would be modified to point the client (for example, psql or git) at the hoop.dev endpoint instead of the raw hostname. The pipeline still uses the same CLI tools, so developers do not need to learn a new interface. The hoop.dev agent, deployed as a Docker container or a Kubernetes sidecar, sits on the same network as the database or Git server, ensuring low latency while keeping the traffic under control.
From a security perspective, the pipeline now has three observable moments:
- The identity check that allows Devin to start the session.
- The optional approval step if a command matches a risky pattern.
- The session recording that persists after the job finishes.
All three are enforced by the same gateway, eliminating the need to stitch together separate logging, approval, and masking solutions.
Getting started with hoop.dev
To add session recording to your CI/CD workflow, start with the official getting‑started guide. It walks you through deploying the gateway, configuring OIDC trust, and registering a connection for the target service. Once the gateway is running, update your pipeline definition to use the hoop.dev endpoint. The documentation also explains how to retrieve and replay recorded sessions for audit or debugging.
All of the setup steps are open source and can be inspected in the repository. The community provides examples for common CI systems and for the most popular back‑ends that Devin may need to talk to.
For a deeper dive into the feature set, the learn section describes the full range of guardrails, including masking, command blocking, and just‑in‑time approvals.
FAQ
Is session recording stored in a separate system?
hoop.dev writes the logs to a configurable storage backend that you control. The storage is independent of the CI system, ensuring that recordings survive job deletion.
Can I exclude certain commands from being recorded?
The gateway records the entire protocol exchange. You can filter the replay view, but the raw data remains available for forensic purposes.
Does this add noticeable latency to my builds?
Because the agent runs close to the target service, the additional hop adds only a few milliseconds, which is negligible compared with typical build times.
Implementing session recording for AI coding agents like Devin gives you the confidence that every automated change is observable, replayable, and auditable. By placing hoop.dev on the data path, you turn a blind CI pipeline into a fully governed workflow.
Ready to see it in action? Explore the open‑source repository on GitHub and start building a recorded, compliant CI pipeline today.
