Generated Knowledge Prompting

Generated Knowledge Prompting improves AI responses by first generating relevant background knowledge and then using it to answer the actual question.

How does it work?

This technique consists of two steps:

Practical Examples

Scientific Explanations

Step 1 - Generate knowledge about photosynthesis:
"Explain the key aspects of photosynthesis"

AI Response:
"Photosynthesis is the process where plants convert light energy into chemical 
energy. Chlorophyll in the leaves absorbs light, which together with water 
and CO2 is converted into glucose and oxygen."

Step 2 - Answer specific question:
"Based on this knowledge: Why are most leaves green?"

Answer:
"Leaves are green because they contain chlorophyll. Chlorophyll efficiently 
absorbs red and blue light but reflects green light, which is why we 
perceive leaves as green."

Business Decisions

Step 1 - Generate market knowledge:
"What are the current trends in e-commerce for sustainable products?"

AI generates information about:
- Growth of the sustainable products market
- Consumer behavior and preferences
- Successful business models

Step 2 - Use this knowledge:
"As a traditional retailer, should we invest in sustainable products?"

Well-founded answer based on the generated market data

Technical Problems

Step 1 - Generate technical knowledge:
"Explain the most common causes of slow website performance"

AI lists:
- Large, uncompressed images
- Too many HTTP requests
- Missing browser caching
- Slow server response times

Step 2 - Solve specific problem:
"Our e-commerce site loads very slowly. What should we check first?"

Targeted recommendations based on the generated knowledge

Variants of the Technique

Automatic Knowledge Generation

"Answer this question and first generate relevant background knowledge:
What factors influence employee satisfaction in remote teams?"

Structured Knowledge Generation

"Generate the following knowledge about project management:
1. Most important methods
2. Typical challenges
3. Best practices

Then use this knowledge to explain how to optimally structure an 
IT project with 50 employees."

Multiple Knowledge Generation

"Generate three different perspectives on this topic:
1. Technical view
2. Business view
3. User view

Topic: Implementation of a new CRM software"

Best Practices

Advanced Applications

Domain-specific Knowledge

"As a financial expert, generate knowledge about:
- Current interest rate developments
- Inflation impacts
- Investment strategies in volatile markets

Use this knowledge: How should a conservative investor 
structure their portfolio in 2024?"

Creative Applications

"Generate knowledge about successful sustainability advertising campaigns.
Based on this, develop three campaign ideas for our 
new environmentally friendly product."

Problem Solving

"Gather information about typical causes of high employee turnover.
Then analyze our situation:
- 30% turnover in the last year
- Mainly young employees affected
- IT industry
What are the most likely causes?"

When to Use This Technique

✅ Ideal for:

• Complex questions requiring background knowledge
• Situations where context is important
• Decision-making with multiple factors
• Explanations of scientific or technical concepts

❌ Less suitable for:

• Simple factual questions
• When you already have all necessary information
• Time-critical requests (two steps take longer)

Practical Templates

Business Analysis

1. "Generate knowledge about [industry/market/technology]"
2. "Based on this, analyze [specific situation]"

Technical Solution

1. "Explain the basics of [technology/concept]"
2. "How can this help with [specific problem]?"

Strategy Development

1. "What are best practices for [area]?"
2. "Develop a strategy for [specific challenge]"

Exercise

Try Generated Knowledge Prompting for:

1. A technical challenge in your company
2. A strategic business decision
3. Explaining a complex concept to laypeople