Prompt-Engineering

Prompt Engineering in the Context of Cultural Strategic Foresight

Prompt Engineering is an independent discipline focused on designing and optimizing text-based inputs for Artificial Intelligence. As a methodological bridge between human thought and machine processing, it enables precise control of language models to achieve high-quality, targeted outcomes.

At the heart of Prompt Engineering is the ability to formulate clear and precise instructions, requiring a deep understanding of the AI models used, their limitations, and weaknesses. Prompt Engineers often develop and maintain Prompt Libraries - collections of inputs for specific models or tasks that are intended to yield optimal results.

Integration into the Cultural Strategic Foresight Framework

The framework for Cultural Strategic Foresight aims to identify deep cultural drivers, analyze their impact on the future, and develop robust and adaptive strategies based on this analysis. In this context, Prompt Engineering can be used as a key tool in the phase of deconstruction using Causal Layered Analysis (CLA).

Within the scope of Cultural Strategic Foresight, Prompt Engineering is particularly used in the RAPID Foresight Cycle to conduct deep research based on reproduced results for a fundamental overview. This cycle describes accelerated sense field analysis, where generative AI is used to quickly analyze important "sense fields." The generative AI is understood as a tool that uncovers the "first artificial intelligence" (culture) in its patterns and dynamics.

Supporting the Causal Layered Analysis (CLA)

The CLA, as the core of deconstruction within the Cultural Strategic Foresight Framework, examines a problem from its most superficial level down to its deepest cultural roots in four layers:

• Litanies: Identification of superficial issues and repetitive narratives

• Systemic Causes: Analysis of structural causes and rational explanations

• Worldviews/Ideology: Examination of deeper thought patterns and paradigms

• Myths/Metaphor: Exploration of collective narratives and emotional foundations

Using Prompt Engineering for CLA-based Deconstruction

Targeted Prompt Engineering allows large language models to be guided in identifying and structuring relevant information, patterns, and connections for each of the four CLA levels.

1. Resonant Deep Research Approaches

Prompt Engineering makes it possible to instruct large language models to go beyond obvious facts and recognize deeper structures and patterns. Precisely formulated prompts can bring the models to adopt various perspectives and examine the subject of investigation from different viewpoints.

2. Systematic Level Analysis

• Litanies Prompts: Instructions for identifying and collecting frequently repeated headlines, public discourses, and "official truths" on the topic

• System Prompts: Guidance for analyzing structural, institutional, and organizational factors influencing the problem

• Worldview Prompts: Instructions to uncover underlying paradigms, thought patterns, and ideological positions

• Myths Prompts: Requests for identifying deep-seated collective narratives, emotions, and cultural assumptions

3. Basis for Discussion Through Structured Outputs

The insights gained through targeted Prompt Engineering can serve as an initial basis for discussion in the CRITICAL mode (Analysis and Critical Thinking). In this phase, the results of the AI analysis are critically questioned and interpreted in exchange with partners and experts to understand deeper cultural logics.

Practical Implementation

For the practical implementation of Prompt Engineering within the CLA, a systematic approach can be pursued:

1. Create a Prompt Library: Develop a collection of prompt templates for each CLA level that can be tailored to various issues

2. Iterative Approach: Continually refine the prompts based on the generated results and their usefulness for the analysis

3. Combination of Expertise: Collaboration between Prompt Engineers, subject matter experts, and Cultural Foresight specialists to optimize the quality and relevance of the prompts

4. Resonance Analysis: Evaluate the generated results regarding their resonance with known facts, expert opinions, and societal discourses

Added Value for the Cultural Strategic Foresight Process

The use of Prompt Engineering within the CLA offers several advantages:

• Efficiency Increase: Enables a consistent and rapid entry into the deconstruction phase through machine pre-work.

• Diverse Perspectives: Expands viewpoints through systematic exploration of all CLA levels and access to a catalog of potentially unrecognized sources.

• Reduction of Bias: Structured prompts can help minimize cognitive biases.

• Deeper Analysis: Assists in identifying non-obvious connections and patterns.

• Better Discussion Basis: Provides a structured basis for the subsequent OPEN Foresight (Deliberation) process.

Therefore

Prompt Engineering represents a powerful tool to support Causal Layered Analysis within the Cultural Strategic Foresight framework. Through the targeted control of large language models, deeper insights into cultural structures and dynamics can be gained, serving as a foundation for well-founded future strategies. Especially when public sources can be researched with the help of prompts. The combination of machine pre-work and human expertise enables a more comprehensive and efficient deconstruction of complex issues, phenomena, and questions.

Manual post-processing, review, and evaluation of the results are particularly important. Each automated research should be used reflexively.