---
title: "Engineering Teams"
description: "IAM for teams running multiple AI agents"
url: "https://gazebohq.com/agents/teams"
---

Engineering teams running multiple AI agents face an access-design problem that does not fit a shared developer environment. Cursor, Claude Code, workflow automations, CI helpers, and custom agents may all touch the same source repositories, deployments, databases, billing systems, and incident tooling, but they do not need the same rights or the same lifetime. Treat each agent or workflow as a workload with an owner, project, environment, approved services, and an expiry or review point. That makes it possible to add a new automation without quietly expanding the authority of every agent already in use.

## Why do engineering teams need AI agent IAM?

When every agent shares one set of API keys, a compromised laptop, a prompt-influenced task, or a misconfigured automation inherits the whole shared account boundary. It is also difficult to distinguish an agent's credential retrieval from a human's use of the same secret, and rotating a key to contain one incident can interrupt unrelated systems. Gazebo gives the team a separate policy and evidence layer for credential delivery: each profile can be scoped to an agent and environment, reviewed with provider permissions, and revoked independently. Provider-side roles, repository protection, deployment approval, and production change management still determine whether an action should be possible after a credential is delivered.

## How it works

1. Inventory the agents, workflows, repositories, environments, and provider credentials already in use. Prepare provider-side roles and tokens with the smallest practical project, account, repository, or environment scope before adding them to Gazebo.
2. Create a named profile for each agent or bounded workflow, recording its owner and intended purpose. Separate development, staging, diagnostic, and production paths so a routine coding session cannot retrieve a production deployment or billing secret.
3. Configure each approved runtime to use its own Gazebo credential path and keep bearer tokens and service credentials out of repository files, shared shell configuration, and agent prompts.
4. Review retrieval records with the task, pull request, CI run, workflow execution, and provider audit trail. A credential request identifies the access path; the provider records establish the API operation or change that followed.
5. Revoke one profile to contain a retired, changed, or unexpected agent without interrupting unrelated workloads. If a delivered secret may have been copied, rotate or revoke it at the original provider and review the affected environment before issuing replacement access.

## Use cases

**Dev, staging, and production separation:** Create separate profiles and provider credentials for development, staging, and production. Give a developer-facing agent the diagnostic or test access it needs, then require a distinct, reviewed profile for any production deployment, data change, billing action, or infrastructure mutation. Environment names alone are not enough if the same broad token is reused underneath.

**Contractor access management:** Give a contractor or temporary automation a profile scoped to one repository, service, environment, and time-bounded task. Preserve the owner and expected expiration in the access review, revoke the profile at handoff, and rotate the provider credential if the execution environment is no longer trusted. This avoids creating a long-lived exception in a shared developer key.

**Cross-team audit trail:** Use Gazebo's record to identify which agent profile requested a credential, then combine it with provider audit events, repository history, CI output, and change approvals. This is more useful than a single shared service account because it keeps access attribution, the actual API action, and the human approval record distinct during a review or incident.

**Primary integrations:** stripe, github, vercel, cloudflare, supabase, linear