Why session recording matters for AI coding agents
An AI coding agent that automatically generates pull‑requests is scheduled to run nightly against an AWS account. The job authenticates with a long‑lived access key stored in the CI secret store, reaches S3, DynamoDB and Lambda directly, and nobody watches the traffic. When the agent mis‑classifies a resource and deletes a bucket, the damage is discovered only after the fact.
Without a transparent audit trail the organization cannot answer basic questions: which code change triggered the deletion, what exact API calls were issued, and whether the behavior was intentional or a hallucination of the model. The lack of recording also defeats internal policies that require every interaction with production resources to be replayable for forensic analysis and regulatory review.
Session recording means capturing the full request‑response exchange for every operation performed through the gateway, storing it in a secure log store, and making it available for later replay or inspection. The record includes timestamps, identity information, and the exact payloads that crossed the wire.
Where enforcement must happen
Identity providers can verify who the AI agent is, and role‑based policies can limit which AWS actions are allowed, but none of those layers observe the actual traffic. Enforcement such as recording must happen where the data flows, otherwise the gateway can be bypassed and the session remains invisible.
How hoop.dev provides session recording
hoop.dev provides the missing data‑path control. It is deployed as a Layer 7 gateway with a network‑resident agent placed next to the AWS resources. The AI agent authenticates to hoop.dev using its OIDC token; hoop.dev validates the token, looks up the groups, and then proxies the request to the AWS service using credentials that only the gateway knows. While the traffic passes through hoop.dev, it records every command and response, creating a full session log that can be replayed later.
The gateway stores the AWS access keys in its own vault and never exposes them to the AI process. When a request arrives, hoop.dev opens a connection to the target service, streams the protocol frames, and simultaneously writes each inbound and outbound frame to the audit store. Because the gateway runs outside the AI container, the agent cannot alter the logging behavior. The resulting session record includes the exact API call, parameters, and response payload, tied to the original identity token, and is retained for the duration required by policy.
Operational workflow and just‑in‑time approvals
Because hoop.dev sits in the data path, it can also enforce just‑in‑time approvals before a high‑risk AWS API call is allowed. When the AI agent attempts an operation such as deleting an S3 bucket, hoop.dev can pause the request, surface the intent to a human reviewer, and only forward the call after explicit consent. The same workflow automatically logs the decision, tying the approval to the session record for full accountability.
Replay for debugging AI behavior
Replay capability turns opaque AI behavior into a reproducible test case. Engineers can pull the recorded session, feed the same inputs into a sandboxed environment, and observe whether the model’s reasoning matches expectations. If a future version of the model generates a different outcome, the discrepancy is evident in the replay logs, enabling rapid root‑cause analysis without re‑creating the exact timing or credentials.
Retention, access control, and compliance
hoop.dev stores session logs in a configurable backend that can be locked down with role‑based read permissions. Teams can define retention policies that align with legal requirements, ensuring logs are kept for the necessary period and then safely archived. Access to the recordings is audited as well, so only authorized auditors can retrieve the data, preserving confidentiality while still providing evidence.
Getting started
To try this yourself, follow the Getting started guide and deploy hoop.dev alongside your AWS workloads. The documentation walks through provisioning an OIDC client, configuring the AWS connection, and enabling session recording. You can also learn more about recording features in the feature docs. All source code and deployment manifests are available in the public GitHub repository.
FAQ
- Can I record sessions for services other than AWS? Yes, hoop.dev supports many targets; the same gateway model applies.
- Does session recording add latency? The gateway writes logs asynchronously, so the impact on typical API calls is minimal.
