Differential Geometry and Strong Attractor Prompt: 3 Example - Analogy Trigger

 

Differential Geometry and Strong Attractor Prompt:  
3 Example - Analogy Trigger

The Kernel Prompt

Kernel: Analogy Trigger (ATK-v0)
Detect:
  source_domain: <EN>
  target_domain: <EN>
  anchors: [<Key Concept 1>, <Key Concept 2>]
Control (Invariants):
  - mappings.count in [3,6]
  - each mapping has {source, target, rationale}
  - include 1 failure case (where analogy breaks)
Playbook:
  - build schema_map: roles|flows|constraints
  - test transfer: which rules survive? which need adaptation?
Failure_Modes:
  - poetic-only
  - overfit
Integration (Output):
  mappings:
    - {source: ..., target: ..., rationale: ...}
  limits: [<break_conditions>]
  next_actions: [<how_to_apply>]

 

Example 1 

Detect:
  source_domain: <Cooking>
  target_domain: <Software Development>
  anchors: [<Chef>, <Programmer>]

 

Response from Grok3

Analogy Trigger (ATK-v0) OutputDetect:

• Source Domain: Cooking
• Target Domain: Software Development
• Anchors: [Chef, Programmer]

Control (Invariants):

• Mappings: 4 (within [3,6])
• Each mapping includes {source, target, rationale}
• 1 failure case included

Playbook:

• Schema Map: Roles (Chef → Programmer), Flows (cooking process → development process), Constraints (kitchen resources → computational resources)
• Test Transfer: Evaluate which cooking rules apply to software development and which require adaptation.

Mappings:

1. Source: Recipe
   Target: Codebase
   Rationale: A recipe provides structured instructions to achieve a culinary outcome, like a codebase provides instructions for software functionality. Both require precision and clarity to ensure the desired result.
2. Source: Ingredients
   Target: Libraries/Frameworks
   Rationale: Ingredients are pre-prepared components combined in cooking, similar to libraries or frameworks that programmers integrate to build software efficiently.
3. Source: Cooking Techniques
   Target: Programming Paradigms
   Rationale: Techniques like baking or grilling define how a dish is prepared, akin to paradigms (e.g., object-oriented or functional programming) that shape how code is written.
4. Source: Taste Testing
   Target: Debugging/Testing
   Rationale: Taste testing ensures a dish meets quality standards, just as debugging and testing verify that software functions correctly.

Failure Case:

• Source: Plating/Presentation
  Target: User Interface (UI) Design
  Rationale: Plating enhances the visual appeal of food, seemingly analogous to UI design. However, this breaks because plating is often secondary to taste (core functionality), while UI can be integral to software usability, making the analogy overfit to aesthetics.

Limits:

• Cooking emphasizes sensory outcomes (taste, smell), which don’t directly translate to software’s focus on functionality and performance.
• Resource constraints differ: kitchens have physical limits (e.g., oven size), while software development faces computational limits (e.g., memory, processing power).

Next Actions:

• Apply analogy to streamline onboarding: teach new programmers by comparing coding to following a recipe.
• Use the analogy to explain debugging to non-technical stakeholders, likening it to taste testing for quality assurance.
• Adapt cooking’s iterative experimentation (e.g., tweaking recipes) to encourage iterative development in agile methodologies.

 © 2025 Danny Yeung. All rights reserved. 版权所有 不得转载

 

Disclaimer

This book is the product of a collaboration between the author and OpenAI's GPT-5 language model. While every effort has been made to ensure accuracy, clarity, and insight, the content is generated with the assistance of artificial intelligence and may contain factual, interpretive, or mathematical errors. Readers are encouraged to approach the ideas with critical thinking and to consult primary scientific literature where appropriate.

This work is speculative, interdisciplinary, and exploratory in nature. It bridges metaphysics, physics, and organizational theory to propose a novel conceptual framework—not a definitive scientific theory. As such, it invites dialogue, challenge, and refinement.

I am merely a midwife of knowledge.