Graph Prompting

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Graph Prompting

Here are several prompt samples designed to implement Graph Prompting, moving the AI from linear explanation to relational, network-based reasoning.

The core principle is to explicitly ask the AI to map relationships, compare the strength of connections, and trace causality through a web of factors, not a single chain.

Prompt Sample 1: Marketing & Customer Behavior Analysis

Scenario: You've noticed a spike in website traffic but not in sales.

Simple Prompt:
"Why are our conversions low despite high traffic?"

Graph Prompt:
"Analyze the customer journey for our online store by modeling it as a causal graph. Your goal is to identify the leaky bucket.

Entities/Nodes to consider: Homepage Visit, Product Page View, Add to Cart, Cart Abandonment, Checkout Initiation, Purchase, Site Speed, Product Reviews, Shipping Cost, Mobile Usability.

Task:

  1. Map the Relationships: Propose a directed graph showing how these entities influence each other. Use arrows like [A] --positively influences--> [B] or [A] --creates friction for--> [B].
  2. Identify Critical Paths: Trace the most common paths from Homepage Visit to Purchase. Then, trace the paths that lead to Cart Abandonment.
  3. Pinpoint the Weakest Link: Based on this graph, which single connection (edge) is the most likely cause for the low conversion rate? Justify your answer by explaining the strength and impact of that relationship.
  4. Recommendation: Propose one action to strengthen that specific weak connection."

Prompt Sample 2: Business Strategy & Root Cause Analysis

Scenario: A product launch underperformed.

Simple Prompt:
"Why did the product launch fail?"

Graph Prompt:
"Conduct a root cause analysis of the product launch by building a fault tree or a causal graph. Do not provide a single reason; show how multiple factors interacted.

Core Problem Node: Low Product Sales.

Potential Factor Nodes: Marketing Reach, Message Clarity, Product-Market Fit, Pricing, Competitor Launch (X), Supply Chain Delays, Early Negative Reviews.

Task:

  1. Construct the Graph: Draw a graph showing how the factor nodes connect to each other and ultimately to Low Product Sales. For example, did Supply Chain Delays cause Early Negative Reviews?
  2. Categorize Connections: Label the connections as either a Direct Cause (strong, immediate link) or an Amplifying Factor (makes a problem worse).
  3. Find the Root Causes: From your graph, which nodes have the most outgoing arrows (i.e., are the biggest catalysts)? Identify the 2-3 root causes that initiated the cascade of problems.
  4. Intervention Points: Looking at your graph, if you could go back in time, which two connections would you try to sever or reinforce to prevent the failure? Explain why."

Prompt Sample 3: Content Strategy & Ideation

Scenario: You want to create a comprehensive blog post on a complex topic.

Simple Prompt:
"Give me ideas for a blog post about 'Sustainable Fashion'."

Graph Prompt:
"Act as a content strategist. Your task is to plan a pillar-cluster content strategy for the topic 'Sustainable Fashion' by first creating a knowledge graph.

Central Node: Sustainable Fashion.

Task:

  1. Create Sub-topic Nodes: Brainstorm 5-7 core sub-topics (e.g., Ethical Sourcing, Circular Economy, Greenwashing, Slow Fashion Movement, Sustainable Materials). These are your primary cluster nodes.
  2. Map the Relationships: Connect these sub-topic nodes to each other. Describe the nature of each connection. For example: Circular Economy --enables--> Slow Fashion Movement, while Greenwashing --threatens the credibility of--> All Other Nodes.
  3. Identify Central Hubs: Which 2-3 sub-topic nodes are the most connected? These will be your most important, interlinked articles (the 'hubs').
  4. Generate Content Briefs: Based on this graph, write a content brief for the two most central hub articles. The brief should explicitly mention which other cluster topics it should link to and explain their relationship."

Prompt Sample 4: Personal Productivity & Decision Making

Scenario: You're feeling consistently unproductive and can't pinpoint why.

Simple Prompt:
"How can I be more productive?"

Graph Prompt:
"Help me diagnose my productivity issues by modeling my week as an influence graph.

Here is my context: I have Sleep <6 hours, Back-to-Back Meetings, No Clear Daily Priority, Constant Email Checks, Low Energy in PM, Procrastination on Project X.

Task:

  1. Build a Personal Graph: Arrange these factors as nodes. Draw a directed graph showing how they influence each other. For example: Sleep <6 hours --> Low Energy in PM --> Procrastination on Project X.
  2. Find the Flywheels and Vicious Cycles: Identify any reinforcing loops (vicious cycles) in the graph. For instance, does Procrastination lead to Late Work which leads to Sleep <6 hours, creating a cycle?
  3. Locate Leverage Points: Based on the graph, which one or two factors, if improved, would have the largest positive ripple effect through the entire network? Justify your choice by tracing the potential positive path.
  4. Actionable Insight: Propose a small, concrete change targeting that high-leverage factor."

Why These Prompts Work as "Graph Prompting":

  • They Explicitly Define Nodes: They force the AI to think in terms of discrete entities (Sleep, Cart Abandonment, Pricing).
  • They Demand Connection Mapping: The core task is not to list, but to link, using verbs that define the relationship.
  • They Encourage Non-Linear Thinking: The AI must consider multiple paths, feedback loops (vicious/virtuous cycles), and the relative strength of influences.
  • They Focus on Causality & Ripple Effects: The output isn't just a description; it's an explanation of how things are connected and which connections matter most, leading to more insightful, actionable, and interpretable results.

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