In multi-agent workflows, cycles support multi-step reasoning and agent collaboration. LangGraph connects agents or processing steps as nodes, with edges defining workflow flow and conditional edges routing dynamically. section 8.1.2
Multi-step reasoning
Reasoning that reaches a conclusion through multiple connected inferential steps.
How Building Reliable AI Systems covers it
- How deep it goes
- Identifies cycle management and graph components, but does not detail reasoning implementation.
- What you can do after
- Build multi-agent workflows with LangGraph cycles for collaborative, multi-step reasoning.
- How it connects
- Connects to multi-agent systems, state management, graph nodes, edges, and conditional routing.
Also explained in
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Inside AILogical reasoning is the process of deriving conclusions from information by applying rules of consistency and inference.
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Sutskever's ListReasoning is the ability to derive conclusions or solve problems by applying structured relationships among facts or representations.
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Knowledge Graphs and LLMs in ActionReasoning is the process of analyzing information, applying rules, and drawing conclusions from evidence or premises.
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Build a Reasoning Model (From Scratch)The process of deriving conclusions from premises through explicit inference rather than surface pattern recognition.
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Machine Learning Platform EngineeringA multistep reasoning chain is an orchestrated sequence of intermediate operations that transforms a user query into a final model response.
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AI Agents in ActionReasoning is the process of deriving conclusions, plans, or solutions by relating information through intermediate steps.
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Natural Language Processing in Action, Second EditionReasoning is the process of deriving conclusions or solving problems by applying relationships among facts, premises, or representations.
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Deep Learning with R, Third EditionReasoning is the process of deriving conclusions or selecting actions from representations, premises, or rules.
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Interview SpeakThe sequence of mental reasoning steps used to analyze information and reach, evaluate, or justify a conclusion or action.
Compare how 10 books explain multi-step reasoning →
Related concepts
- Tree-of-thoughtcontrasts with · Tree-of-thought is a reasoning technique that explores and evaluates multiple branching paths of intermediate reasoning to develop a solution.
- chain-of-thought promptingused by · Chain-of-thought prompting is a technique that elicits or guides a model to produce or follow intermediate reasoning steps before a final answer.
- ReActused by · ReAct is an agent technique that iteratively interleaves reasoning, actions, and observations so results can guide subsequent actions.
- reasoning modelused by · A reasoning model is an AI model designed or optimized to perform multistep inference or analysis before producing an answer or result.
- intuitioncontrasts with · Intuition is the formation of a judgment or insight without deliberate, explicit analytical reasoning.
This explainer was generated by Manning's knowledge graph from the text of Building Reliable AI Systems. The section links point to the parts of the book it draws on.