Workflow Automation

Run repeatable processes with workflows, background execution, human review, and schedules.

Engineering and operations teams use workflows to automate processes that need consistent execution and a traceable result. Agno combines model-driven steps with branches, loops, parallel work, approval gates, background execution, schedules, and persisted run history.

incident_workflow.py

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.workflow import Workflow

triage = Agent(
    name="Triage",
    model="openai:gpt-5.5",
    instructions="Extract the issue, severity, and responsible team.",
)

action_plan = Agent(
    name="Action Plan",
    model="openai:gpt-5.5",
    instructions="Turn the triage result into a short action plan.",
)

incident_workflow = Workflow(
    name="Incident Triage",
    steps=[triage, action_plan],
    db=SqliteDb(db_file="tmp/workflows.db"),
)

incident_workflow.print_response(
    "Checkout requests return HTTP 500 after the latest deployment."
)

Create a virtual environment, install the OpenAI, AgentOS, and SQLite integrations, and set OPENAI_API_KEY before running the workflow:

uv venv --python 3.12
uv pip install -U "agno[openai,os,sqlite]"
uv run python incident_workflow.py

Each step receives the previous step’s output. The database stores workflow runs so they can be inspected after execution.

Choose the control model

Requirement	Use
One model-driven task	Agent
Dynamic delegation among specialists	Team
Fixed steps, branches, loops, or parallel groups	Workflow

Production building blocks

Need	Capability
Continue work after the client disconnects	Background execution
Pause before sensitive or irreversible work	Human-in-the-loop workflows
Run recurring jobs	Scheduling
Trigger work from another service	Agent API
Inspect runs, latency, and failures	Observability

Common patterns

Pattern	Workflow shape
Intake and triage	Extract input, classify it, route it, and request review when needed.
Data enrichment	Fetch records, enrich them in parallel, validate output, and persist results.
Recurring reports	Collect data, analyze it, render a report, and run on a schedule.
Long-running research	Start in the background, persist events, and reconnect to the stream.

Next steps

Task	Guide
Define workflow steps	Building workflows
Choose an orchestration pattern	Workflow patterns
Run a workflow through AgentOS	Using the AgentOS API