Query rewriting

As explained in The Art of AI Product Development

A retrieval technique that rewrites an input query into a form better suited to searching a target information collection.

Query rewriting improves retrieval by turning a vague user question into a more targeted search query. In retrieval-augmented generation, the system can rewrite or expand the raw input before searching the target collection. section 7.3.3

From broad question to targeted searches

A user asks, “What trends should we be aware of in AI?” The system can create focused searches such as “What are the latest trends in AI for SaaS platforms?” and “What AI developments are impacting workflow automation?” These queries reduce irrelevant results from areas such as healthcare or finance. section 7.3.3

A practical retrieval flow can:

• Detect vague or poorly structured input. section 7.3.3
• Rewrite or expand the query into focused subqueries. section 7.3.3
• Classify the query so retrieval can prioritize appropriate sources and pipelines. section 7.3.3

Figure 7.10 Optimization potentials in the RAG system

Use the optimization overview to relate query rewriting to other retrieval and generation improvements. section 7.3.3

How The Art of AI Product Development covers it

How deep it goes

Demonstrates rewriting, expansion, and classification through product examples without detailing implementation internals.

Examples

Uses broad AI-trend questions, SaaS and workflow-automation subqueries, and irrelevant healthcare or finance results.

What it assumes

Assumes familiarity with search or retrieval systems while illustrating query quality problems through concrete user questions.

What you can do after

Apply it by converting broad questions into focused subqueries and routing them toward relevant sources.

How it connects

Connects query rewriting with retrieval-augmented generation, query expansion, query classification, and prompt optimization.

liveBookmanning.com

Read The Art of AI Product Development on liveBook Get the book at manning.com

Also explained in

• 

  liveBookmanning.com
  AI Agents and ApplicationsQuery rewriting is a technique that transforms an original search request into one or more clearer or more targeted queries to improve retrieval results.
• 

  liveBookmanning.com
  AI-Powered SearchQuery rewriting is the transformation of an original search query into an alternative query that preserves or enhances its intended retrieval behavior.
• 

  liveBookmanning.com
  Essential GraphRAGQuery rewriting is the transformation of a user query into a formulation that better matches the language and context of target documents.
• 

  liveBookmanning.com
  Grokking AI ApplicationsA technique that rephrases a user query to improve its semantic match with retrievable document content.

Compare how 5 books explain query rewriting →

Related concepts

• language modeluses · A language model is a computational model that represents patterns in linguistic tokens to estimate sequence probabilities and predict or generate language from context.
• step-back promptingincludes · Step-back prompting is a prompting technique that reframes a specific question as a broader, more abstract question before addressing the original question.
• HyDEincludes · HyDE is a retrieval technique that generates hypothetical document or answer content from a query and uses that content or its embedding to retrieve relevant documents.
• ruleimplemented by · A PostgreSQL rule is a query-rewrite definition attached to a database relation that modifies or adds statements when specified events occur.
• retrieval-augmented generationpart of · Retrieval-augmented generation is a technique that retrieves relevant information from external sources and supplies it as context to a generative model when producing an output.

This explainer was generated by Manning's knowledge graph from the text of The Art of AI Product Development. The section links point to the parts of the book it draws on.