Next Steps

Go beyond: build teams, workflows, scheduled tasks, and interfaces.

You now have a deployed agent platform with evals, JWT auth, and a set of coding-agent skills that cover the full lifecycle: create → improve → evaluate → maintain.

The sections below cover the next level: teams and workflows for multi-step logic, scheduled tasks for proactive runs, and interfaces that put your agents where your users are.

Going beyond agents

Pattern	Use it when	Reference
Agent	A single LLM with tools and instructions can handle the request.	Agents overview
Team	The right specialist isn’t known up front. A leader routes or coordinates.	Teams overview
Workflow	The process needs to run the same way every time. Determinism matters.	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 ships two scheduled workflows:

Workflow	What it does	Toggle
Deployment check	Checks daily that the 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 for the cron API.

Connect to interfaces

Your agents should be available where your users are. Slack threads, Telegram chats, WhatsApp for the field team, or a custom UI inside your product.

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

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
Telegram	Telegram interface
WhatsApp	WhatsApp interface
Custom UI / AG-UI	AG-UI interface
All interfaces	Interfaces overview

Keep the repo coherent

As you ship more agents, configuration drifts, env vars rot, and new agents miss imports. The template ships a fifth skill for the recurring sweep:

/review-and-improve

It auto-fixes mechanical drift (stale paths, missing example.env entries, agents on disk not registered in app/main.py) and surfaces the rest as a punch list. Best run before public releases and periodically during active development.

You’re done

You now have a platform that runs locally and on Railway with JWT auth built in, stores its sessions, memory, knowledge, and traces in Postgres, connects to every frontend through its MCP server, and manages and improves itself through five coding-agent skills.