> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2-codex-homepage-20260719-015142.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Next Steps

> Add teams, workflows, scheduled tasks, and interfaces to your agent platform.

Your platform now runs locally and on Railway with persisted state, authentication, traces, evals, and a coding-agent development loop. Extend it with teams, workflows, schedules, and the interfaces your users already use.

## Add teams and workflows

| Pattern      | Use it when                                                               | Reference                                 |
| ------------ | ------------------------------------------------------------------------- | ----------------------------------------- |
| **Agent**    | A single LLM with tools and instructions can handle the request.          | [Agents overview](/agents/overview)       |
| **Team**     | Multiple specialists should route, coordinate, or collaborate.            | [Teams overview](/teams/overview)         |
| **Workflow** | The process needs explicit steps, branches, loops, or parallel execution. | [Workflows overview](/workflows/overview) |

Teams come in four modes:

| Mode           | Behavior                                                                                                       |
| -------------- | -------------------------------------------------------------------------------------------------------------- |
| **Coordinate** | A leader plans the work, calls the right specialists, synthesizes.                                             |
| **Route**      | A router picks one specialist to handle the request.                                                           |
| **Broadcast**  | Every specialist runs in parallel; the leader synthesizes.                                                     |
| **Tasks**      | A leader breaks the goal into a task list, delegates tasks to members, and loops until every task is complete. |

## Scheduled tasks

The scheduler is on by default in `app/main.py`, and the template prepares two workflows for scheduled runs:

| Workflow             | What it does when enabled                     | Toggle                                    |
| -------------------- | --------------------------------------------- | ----------------------------------------- |
| **Deployment check** | Checks daily that AgentOS is wired correctly. | `ENABLE_DEPLOY_CHECK` (on by default)     |
| **Run evals**        | Runs the `smoke`-tagged eval cases daily.     | `ENABLE_SCHEDULED_EVALS` (off by default) |

Schedule your own agents and workflows the same way:

| Use case           | Example                                                            |
| ------------------ | ------------------------------------------------------------------ |
| **Maintenance**    | Purge sessions older than 90 days. Vacuum Postgres tables.         |
| **Proactive runs** | Every weekday morning, summarize overnight news and post to Slack. |

See [scheduling](/features/scheduling) for the cron API.

## Connect to interfaces

Connect agents to Slack, Telegram, WhatsApp, or a custom UI inside your product.

Expose the agent via an interface in `app/main.py`:

```python theme={null}
interfaces: list = []
if SLACK_BOT_TOKEN and SLACK_SIGNING_SECRET:
    from agno.os.interfaces.slack import Slack

    interfaces.append(
        Slack(
            agent=agent_builder,
            streaming=True,
            token=SLACK_BOT_TOKEN,
            signing_secret=SLACK_SIGNING_SECRET,
            resolve_user_identity=True,
        )
    )

agent_os = AgentOS(
    ...,
    interfaces=interfaces,
)
```

| Interface         | Reference                                                        |
| ----------------- | ---------------------------------------------------------------- |
| Slack             | [Slack interface](/agent-os/interfaces/slack/introduction)       |
| Telegram          | [Telegram interface](/agent-os/interfaces/telegram/introduction) |
| WhatsApp          | [WhatsApp interface](/agent-os/interfaces/whatsapp/introduction) |
| Custom UI / AG-UI | [AG-UI interface](/agent-os/interfaces/ag-ui/introduction)       |
| MCP clients       | [AgentOS MCP interface](/agent-os/mcp/mcp)                       |
| All interfaces    | [Interfaces overview](/agent-os/interfaces/overview)             |

## Keep the repo coherent

As the platform grows, the same agent needs to stay aligned across its source file, `app/main.py`, `app/config.yaml`, environment variables, and documentation. The `review-and-improve` skill checks those files together:

```text theme={null}
Run the review-and-improve skill in .agents/skills.
```

It fixes straightforward issues such as stale paths, missing `example.env` entries, and agents that exist on disk but are not registered in `app/main.py`. It returns a list of changes that need your judgment. Run it before a public release or after a refactor.

## What you have built

| Capability       | What is in place                                                                                 |
| ---------------- | ------------------------------------------------------------------------------------------------ |
| Runtime          | AgentOS running locally and on Railway                                                           |
| State            | Postgres for sessions, memory, knowledge, traces, and eval history                               |
| Access           | REST, MCP, the AgentOS UI, and optional chat interfaces                                          |
| Security         | JWT authorization configured for Railway, with per-user isolation available as an opt-in         |
| Development loop | Six coding-agent skills for setup, creation, extension, improvement, evaluation, and maintenance |