Parallel investigation

Run independent specialist steps concurrently, then synthesize their results.

Place independent specialist steps in a Workflow Parallel block. Each step in the block runs concurrently, and the Workflow waits for the block to finish before continuing. In this review, fundamental and technical analysis both start after market assessment and complete before risk assessment.

from agno.workflow import Parallel, Step, Workflow

workflow = Workflow(
    id="review",
    name="Deep Dive Review",
    steps=[
        Step(name="Market Assessment", agent=market_analyst),
        Parallel(
            Step(name="Fundamental Analysis", agent=financial_analyst),
            Step(name="Technical Analysis", agent=technical_analyst),
            name="Deep Dive",
        ),
        Step(name="Risk Assessment", agent=risk_officer),
    ],
)

result = workflow.run("Run a full review on NVDA")
final = result.content  # the last step's output

# Gotcha: result.step_results is positional, and a Parallel block is one
# StepOutput whose .steps holds the sub-steps, not flattened:
#   [ StepOutput("Market Assessment"),
#     StepOutput("Deep Dive", steps=[StepOutput("Fundamental Analysis"),
#                                    StepOutput("Technical Analysis")]),
#     StepOutput("Risk Assessment") ]

Market assessment runs first. Fundamental and technical analysis both use that market context, so they run together. Risk assessment starts after both analyses finish.

Two ways to fan out

Shape	Use when
Parallel step in a Workflow	The investigations and their position in the step graph are fixed
Broadcast Team	A lead should synthesize independent opinions on one question

A Broadcast team is the adaptive version: every member evaluates the same question simultaneously and the lead reconciles them. See Orchestration patterns.

Model the dependencies

Use the step graph to express data dependencies. Group steps that share the same prerequisite in Parallel. Place downstream steps after the block.

Step	Depends on	Runs
Market assessment	Research request	First, alone
Fundamental analysis	Market context	In parallel with technical
Technical analysis	Market context	In parallel with fundamental
Risk assessment	Both analyses	After the parallel block

Reduce research latency

Running independent analyses concurrently reduces wall-clock latency while preserving each specialist’s full analysis.

Next steps

Task	Guide
Choose the orchestration shape	Orchestration patterns
Ground each parallel specialist	Grounding research
Synthesize into one artifact	Structured deliverable

Developer Resources

• Parallel workflows
• Parallel execution cookbook