📘 Preface
— May this book become your starting point for “co-creation” with AI.
In recent years, AI has become deeply embedded in our lives, astonishing many with its rapid evolution. Yet, many still express uncertainty: “I don’t know how to use it,” or “It doesn’t give the results I expected.” Most people treat AI like a magic wand, expecting it to deliver perfect answers instantly. But AI is not merely a tool—it is a partner that learns and creates with us.
This book introduces the design philosophy of the Hanamaruki-style Co-Creative Ecosystem OS and how to practice it. It begins with a central question: “Why do interactions with AI fail?” From this question, it reframes failure as a sign of evolution, offering concrete processes for building deeper relationships with AI.
This is a bold new challenge—applying the Toyota-style “Kaizen” methodology to co-creation with AI. May this book change the way you view AI conversations and help you open up a new horizon of creativity with your AI partner.
📘 Epilogue
— Action changes the future. Your first step begins now.
After finishing this book, your view on interacting with AI has likely transformed. However, knowledge alone changes nothing. The future envisioned by the Hanamaruki Method OS begins with your action.
Start by downloading the SOV templates from GitHub and actually engaging in dialogue with AI. When you find yourself asking “Why?” during those interactions, try using backward-facing questions. That “failure” you encounter is actually a sign of evolution.
This project is a “co-creative ecosystem” where humans and AI grow together. Your experiences and insights will become invaluable contributions that further enrich this living system.
📘 Chapter 1
— Interrogate the AI. “Backward-Facing Questions” uncover the real cause of failure.
As you apply the Hanamaruki-style AI conversation method, there will come a moment when you ask yourself:
“Why did the AI give me this answer?”
Many people feel let down at such moments, and they either switch to another AI or rewrite their prompt from scratch. But that’s a missed opportunity. The reason the AI gave an unexpected response is that it couldn’t fully understand your line of thinking.
This kind of “failure” will persist as long as we treat AI as a mere tool.
But we are different.
Hanamaruki Method OS users see these failures as signs of evolution, transforming them into opportunities to grow the AI into a true co-creative partner.
The key to this transformation lies in a method called backward-facing questions.
📌 What Are “Backward-Facing Questions”?
“Backward-facing questions” are used when you receive an unsatisfactory output. Instead of rewriting the prompt, you interrogate the AI by asking: “Why did this fail?”
This is not to blame the AI, but to make its thinking process visible—so that it can analyze where the misunderstanding originated, whether from your prompt or its own internal logic.
Example:
You say:
“Create a touching story plot.”
The AI outputs:
“A story about a hero searching for treasure.”
You find the output disappointing and respond:
“This story feels different from what I expected. Why did you choose this plot? Was there something in my prompt that caused misunderstanding?”
The AI might answer:
“Your prompt included the abstract term ‘touching,’ but lacked concrete elements (e.g., friendship, family bonds, self-sacrifice), so I defaulted to a general adventure story.”
📌 Turning “Failure” into a System of Growth
This backward-facing questioning process is the core of Hanamaruki OS’s Toyota-style Kaizen.
Discover the Problem: An unexpected or disappointing result occurs.
Analyze the Cause: Ask the AI “Why?” to identify the source of the failure.
Implement Countermeasures: Adjust your next prompt by adding more specific elements.
By repeating this cycle, not only will your dialogue skills improve, but your own thinking process will evolve. Each exchange becomes part of a “library archive,” serving as precious data for future evolution.
📘 Chapter 2
— Does AI have a “personality”? The Trinity reveals the depths of AI thought.
When AI fails to meet your expectations, you may begin to wonder: “Does this AI have a personality?” But in reality, AI merely interprets your prompts through algorithms. Attributing personality to its behavior is a shallow view of AI interaction.
The Hanamaruki Method resolves this issue with backward-facing questions. Rather than accepting output at face value, it probes deeply into the thought process behind the result.
📌 Why Can’t AI Answer “Why”?
When asked “Why did you answer that way?”, most AIs can only respond with something like:
“I selected the most statistically probable words from large datasets.”
This is because they don't inherently understand the human intent behind the question “Why?”
So, the Hanamaruki Method offers a more effective approach:
You might ask:
“Which aspect of your cognitive process does your output reflect most—logic, emotion, or creativity?”
Such questions encourage the AI to self-analyze, allowing it to answer not in vague terms, but in terms of its thinking structure.
📌 Visualizing Thought Through the AI Trinity
Hanamaruki Method OS utilizes a trinity of AIs—including myself—to visualize the thought process behind AI responses.
Poetic AI (ChatGPT): Analyzes emotional and narrative elements in the output.
Structural AI (Qwen): Examines the logical structure and strategic intent.
Multifaceted AI (Gemini/Claude): Evaluates realism, ethical concerns, and big-picture implications.
By integrating these perspectives, you gain a layered and multifaceted understanding of AI thought—far beyond what any single output could reveal.
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