Prompt Chaining

Prompt Chaining is used for complex tasks involving multiple steps, such as analyzing large text documents. The first prompt typically extracts relevant information, and the second prompt uses this extracted information to answer a specific question.
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Scenario: Analyzing a large report on "Emerging Market Trends."

Step 1: Extracting Key Information

Prompt: "Identify and extract key sections from the report that discuss the rise of artificial intelligence in Asian markets."
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Output: "Extracted Section: 'In Asian markets, there has been a notable surge in AI adoption, particularly in sectors like finance, healthcare, and retail. This is attributed to increased technological investments and a robust digital infrastructure.'"

Step 2: Detailed Analysis Based on Extracted Information

Prompt: "Based on the extracted section, what could be the potential impact of AI on the business landscape in Asian markets?"
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Output: "The rise of AI in Asian markets could lead to transformative changes in various sectors. In finance, it may enhance risk assessment and fraud detection. In healthcare, AI could improve diagnostic accuracy and patient care efficiency. Retail could see personalized customer experiences and optimized supply chains. These impacts indicate a significant shift towards technology-driven solutions, positioning Asia as a key player in AI innovation."

The first step involves extracting relevant data from a comprehensive report, focusing on AI in Asian markets. The second step uses this information to analyze the potential impacts of AI on different business sectors. This demonstrates how Prompt Chaining can be used for in-depth analysis, starting with information extraction and culminating in a nuanced understanding of a complex topic.