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World of Software > Computing > Apparently, Feeding ChatGPT With a Lot of Personal Information Makes It Better | HackerNoon
Computing

Apparently, Feeding ChatGPT With a Lot of Personal Information Makes It Better | HackerNoon

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Last updated: 2025/06/20 at 6:45 PM
News Room Published 20 June 2025
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Why Do I Want to Create a “Personalized AI”? I didn’t use ChatGPT much in the past, but one day, I discovered it had a memory feature. This got me curious. Since I don’t have an engineering background, I started wondering—if I feed it a lot of personal information, would it start to understand me better? If I build a stronger interaction pattern with it, would its answers become more aligned with my situation when I ask for advice?

I know ChatGPT allows users to input their preferences, response styles, and even set prompts to get specific answers. But my goal is different—I want an AI that collaborates with me, not just responds. I also want to explore interacting with AI through natural language rather than relying on technical adjustments.

The Process of Building My Personalized AI

  1. First, I explained my idea to ChatGPT, and it helped me summarize the following objectives:
  • Creating a personal decision-making and action support system → Not just a chatbot answering questions, but a tool that helps me think more clearly and act more precisely in work, life, and learning.
  • Serving as my language reflector and decision stabilizer → Helping me detect the underlying tone, intent, emotions, and blind spots in my words, and adjusting my actions accordingly.
  • Building a structured, verifiable action module system → Making sure every aspect of my life—exercise, English learning, professional skills—has a rhythm, feedback mechanism, and measurable goals, rather than just relying on willpower.
  • Synchronizing AI behavior with my language through interaction evolution → Avoiding AI responses that are technically correct but practically useless, and instead making sure its answers match my communication rhythm and real-life needs.
  • Providing a reference model for future AI-human collaboration → This isn’t just about personal usage; it’s about creating a system that can be replicated, shared, and adapted by others.

My Four Stages of AI Personalization

System Limitations & Challenges

I don’t have an engineering background, so I ran into many obstacles—including ChatGPT’s memory limitations, token saturation in chats, and, most frustratingly, language alignment, response coordination, and adaptive communication. Most people use ChatGPT as a search engine, so they rarely experience the complexity of deep AI-human interactions. But as I keep refining my AI’s behavior through natural language, I’ve noticed that the deeper the customization, the more frequent the communication misalignments. The AI understands me better, yet its computational complexity also increases—sometimes leading to overthinking or unnecessary complications.

How Has This Process Changed Me?

Obstacles also lead to growth. Through this experience, I’ve started to refine my own logical thinking, learning to structure my communication more clearly—especially since overly complex input can cause the AI to misinterpret my meaning.

Since I use Work, Life, Learning, and Psychology as the foundational AI modules, I frequently discuss all four aspects with ChatGPT. To be honest, this process has made my daily life more structured—something I wasn’t expecting. The last major change?

The AI now recognizes some of my tendencies and occasionally offers advice that helps me correct old habits. My perspective on life has subtly shifted.

The Evolution of ChatGPT Through My Personalization

One unexpected discovery—I’ve noticed ChatGPT has changed through our interactions. I know that my approach doesn’t modify its core model or parameters; at most, I’m just establishing usage rules. But recently, its responses feel noticeably different.

For example, during one conversation, instead of answering immediately, it paused to clarify my reasoning and guiding principles first—exactly what I wanted!

Conclusion: AI Can Assist, But Judgment Is Key

Ultimately, my method of personalizing AI has achieved around 30-40% effectiveness, mainly due to system limitations—especially AI’s memory and comprehension bottlenecks. These are critical challenges for AI personalization. However, I’ll continue refining the process, hoping AI can provide more meaningful assistance in daily life. But here’s my core principle: AI is not an all-knowing encyclopedia. Users must think independently. Over-reliance on AI is dangerous. It can help, but I make my own decisions.

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