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Pipeline

As explained in Introduction to Generative AI, Second Edition

A data pipeline is a sequence of processes that collects, transforms, transports, and prepares data for downstream use.

In prompt engineering, a pipeline can link prompts so that one step’s output becomes the next step’s input. Prompt chaining splits a larger task into steps, each handling a specific part. section 7.4

A chained workflow can:

  • Extract relevant quotes from a document in one step, then use them to generate an answer in another. section 7.4
  • Make debugging and optimization easier by separating a task into smaller steps. section 7.4
  • Support enterprise applications, retrieval-augmented generation (RAG) workflows, and tool-augmented assistants. section 7.4

How Introduction to Generative AI, Second Edition covers it

How deep it goes
Defines prompt chaining and explains its modular benefits with an example, without detailing implementation.
Examples
Illustrates chaining by extracting relevant document quotes before generating an answer.
What you can do after
Understand how to divide a task across prompts so one step’s output informs the next.
How it connects
Connects prompt chaining with prompt engineering, retrieval-augmented generation, and tool-augmented assistants.

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This explainer was generated by Manning's knowledge graph from the text of Introduction to Generative AI, Second Edition. The section links point to the parts of the book it draws on.