> ## Documentation Index
> Fetch the complete documentation index at: https://docs.usechamber.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Getting Started

> Enable the AI Ops Agent for your organization and configure it for your team's workflow

<Note>
  **Private Beta** — The AI Ops Agent is currently in private beta and available to select customers. To request access, [contact us](mailto:support@usechamber.io) or reach out to your account representative.
</Note>

Get the Chamber AI Ops Agent running for your organization in minutes. The agent connects to your existing Chamber deployment — no additional cluster-side components required.

## Prerequisites

* A Chamber account with admin access
* At least one Kubernetes cluster with the [Chamber agent installed](/agent/installation)
* A Slack workspace for your team

## Setup

<Steps>
  <Step title="Enable AI Ops in the Chamber Console">
    Navigate to **Settings > AI Ops Agent** in the [Chamber dashboard](https://app.usechamber.io). Toggle **Enable AI Ops Agent** to on.
  </Step>

  <Step title="Connect to Slack">
    Click **Add to Slack** to authorize the AI Ops Agent in your workspace. This creates the `@chambie-ops` bot in your Slack — separate from any existing Chamber integrations.

    Select the channels where the agent should post:

    * **Alerts channel** — real-time incident notifications (e.g., `#ml-ops-alerts`)
    * **Daily reports channel** — scheduled summaries (e.g., `#ml-ops-daily`)
    * **Approvals channel** — approval requests for high-risk actions (e.g., `#ml-ops-approvals`)
    * **Escalation channel** — unresolved issues that need human attention (e.g., `#ml-ops-escalation`)
  </Step>

  <Step title="Configure Your Tenant Policy">
    Set the operational boundaries for the agent. The default policy allows read-only operations and requires approval for all write actions — a safe starting point.

    You can customize:

    | Setting                      | Default    | Description                                         |
    | ---------------------------- | ---------- | --------------------------------------------------- |
    | **Heartbeat interval**       | 5 minutes  | How often the agent checks your infrastructure      |
    | **Daily budget limit**       | \$500      | Maximum GPU spend the agent can authorize per day   |
    | **Monthly budget limit**     | \$10,000   | Maximum GPU spend per month                         |
    | **Max GPUs per auto-submit** | 4          | Jobs up to this size can be auto-submitted (Tier 2) |
    | **Tier 3 approval channel**  | —          | Slack channel for high-risk approval requests       |
    | **Tier 4 approvers**         | —          | Specific users who can approve destructive actions  |
    | **Approval timeout**         | 30 minutes | How long before unanswered approvals escalate       |
  </Step>

  <Step title="Verify the Agent is Running">
    Once enabled, the agent starts its first heartbeat check within 5 minutes. You'll see a message in your alerts channel:

    ```
    @chambie-ops connected

    Monitoring: 3 capacity pools, 48 GPUs, 12 active workloads
    Policy: Tier 0-2 auto, Tier 3+ approval required
    Heartbeat: every 5 minutes
    Daily report: 9:00 AM to #ml-ops-daily

    All systems healthy. HEARTBEAT_OK
    ```

    If everything is healthy, the agent will be silent until something needs attention.
  </Step>
</Steps>

<Tip>
  Start with the default policy (read-only auto, approval for writes) and gradually expand autonomous permissions as you build confidence in the agent's behavior.
</Tip>

## What Happens Next

Once running, the AI Ops Agent immediately begins:

1. **Monitoring** your active workloads, GPU health, and capacity utilization
2. **Posting daily cost reports** to your configured channel
3. **Responding to failures** as they occur — diagnosing, recommending, and acting within your policy
4. **Building its knowledge base** — learning the patterns specific to your infrastructure

<Info>
  The AI Ops Agent is a separate Slack bot (`@chambie-ops`) from Chamber's conversational assistant (`@chambie`). The conversational assistant handles ad-hoc questions and manual tasks. The AI Ops Agent handles autonomous monitoring and remediation.
</Info>

## Adjusting the Policy Over Time

As the agent proves itself, you can gradually expand its autonomous capabilities:

| Phase        | Recommended Policy                                      | What Changes                                            |
| ------------ | ------------------------------------------------------- | ------------------------------------------------------- |
| **Week 1**   | Read-only auto, all writes need approval                | Observe how the agent diagnoses issues                  |
| **Week 2-4** | Auto-submit small elastic jobs (up to 4 GPUs)           | Agent handles routine OOM resubmissions automatically   |
| **Month 2+** | Auto-submit up to 16 GPUs, auto-resubmit preempted jobs | Agent handles the majority of routine incidents         |
| **Ongoing**  | Tune based on your comfort level                        | Review the audit trail and expand or restrict as needed |

## Next Steps

<CardGroup cols={2}>
  <Card title="AI Ops Overview" icon="robot" href="/ai-ops/overview">
    Learn what the AI Ops Agent does and why it matters
  </Card>

  <Card title="Supported Scenarios" icon="list-check" href="/ai-ops/capabilities">
    See the full range of failures the agent can handle
  </Card>

  <Card title="Safety & Governance" icon="shield-halved" href="/ai-ops/safety">
    Deep dive into the five-layer safety model
  </Card>

  <Card title="Slack Integration" icon="hashtag" href="/platform/integrations/slack">
    Configure your existing Slack integration
  </Card>
</CardGroup>