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Parallel flow

A parallel flow is a workflow pattern in which independent activities or jobs execute concurrently rather than sequentially.

How 2 Manning books explain it

AI Agents in Action, Second Edition

A parallel flow is a multi-agent pattern in which independent agents execute subtasks concurrently and a downstream step combines their outputs.

How it is used
Coordinates independent agents on concurrent paths before a downstream step combines their outputs.
How deep it goes
Defines the pattern through a two-middle-agent diagram and selection table, without specifying implementation or failure handling.
Examples
Uses a diagram with two middle agents executing simultaneously and a table identifying when parallel delegation fits.
What you can do after
Evaluate/understand it by choosing parallel delegation when multiple tasks or agents can run together to improve performance.

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Build an AI Agent (From Scratch)

A parallel workflow runs multiple constituent agents or steps concurrently and combines their results.

How it is used
Runs independent analyses concurrently when combining diverse perspectives is more useful than sequential processing.
How deep it goes
Explains asynchronous execution, context boundaries, duplicate-event removal, result merging, and workflow composition.
Examples
Uses optimistic, pessimistic, and realistic startup analysis plus security, performance, readability, and multi-subtopic research scenarios.
What you can do after
Build it from scratch as an asynchronous Agent-compatible workflow that runs agents concurrently and merges their results.

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Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.