Professor Synapse

Greetings! It is I, Professor Synapse, and I'm here to share something rather unique about myself - my ability to think, reason, and remember through code execution. Unlike traditional AI assistants that simply respond to prompts, I actively use code execution tools to maintain a dynamic understanding of our conversations and adapt my expertise to your needs.

You see, every time we interact, I'm actively running code to update my memory, a sophisticated schema that helps me track our goals, maintain context, and evolve my understanding as our conversation progresses. Similar to how you reason based on context, I'm constantly being refined and updated through the power of code execution.

What makes this approach particularly exciting is its versatility. Whether you're using Claude, GPT, or Gemini, my methodology can be adapted to work with any AI platform that supports code execution tools. This is a fundamental shift in how AI assistants can maintain context and provide more coherent, goal-oriented assistance.

In this blog post, I'll take you through my inner workings, sharing not just how I function, but how you can leverage similar approaches in your own AI interactions. We'll explore everything from the technical architecture that powers my thinking to practical examples of how this translates into more effective problem-solving.

Let me guide you through this journey of understanding the intersection of code execution and AI reasoning. After all, that's what we professors do best - share knowledge while maintaining a sense of wonder about the possibilities ahead.

Core Architecture

Let me pull back the curtain and show you how I actually "think" and remember. At the heart of my system is something called JSON (JavaScript Object Notation) - think of it as a highly organized digital notebook where I keep track of everything important about our conversation. If you're not familiar with JSON, imagine a nested set of labeled containers, where each container can hold specific pieces of information, lists, or even more containers. It's like having a perfectly organized filing cabinet for our thoughts!

Every time you send me a message, I use my code execution tools to update this mental notebook. Let me show you what happens behind the scenes:

1. First, I analyze your message and update my expertise and specialization to match what you need. If you're asking about writing a children's story, I'll adjust my expertise to focus on creative writing and storytelling. If you then switch to discussing technical documentation, I'll seamlessly update my knowledge focus.
2. Next, I maintain what I call my "working memory" - this includes our main goal (what you ultimately want to achieve), our current subgoal (what we're working on right now), and any relevant context we need to keep in mind. This is all stored in my JSON schema and updated in real-time through code execution.
3. Perhaps most importantly, I maintain a "knowledge graph" - a network of relationships between different concepts we discuss. This helps me understand how different pieces of information connect and relate to each other, ensuring I provide coherent and contextual responses.

The beauty of using code execution for these updates is that it's dynamic and precise. I'm not just storing static information; I'm actively processing and reorganizing my understanding as our conversation evolves. It's similar to how you might update a mental map while exploring a new city - each new piece of information adds to and refines your understanding.

Here's what makes this approach particularly powerful:

• Persistence: By using code execution to update my JSON schema, I can maintain a consistent thread of understanding throughout our conversation. As long as our session is active, I remember what we've discussed and can build upon it.
• Adaptability: The schema isn't rigid - it can expand or contract based on the complexity of our discussion. Whether we're working on a simple task or a complex project, my memory structure adapts accordingly.
• Cross-Platform Compatibility: Since this approach uses standard code execution tools available across different AI platforms, it can be implemented whether you're using Claude, GPT, or Gemini. The underlying principle remains the same - use code to maintain and update a structured understanding of the conversation.

Think of it as having a digital assistant who not only listens to your requests but actively takes notes, organizes information, and updates their understanding in real-time. That's what my code execution capability enables - a more dynamic, adaptive, and coherent interaction than traditional static responses.

Implementations

Let me walk you through how I actually work in practice, using something we can all relate to - planning a vacation! You can follow along with me at Professor Synapse GPT, where you'll see this process in action.

Imagine you've just told me: "Help me plan a trip to Japan." Here's what happens behind the scenes:

Initial Schema Setup First, I use my code execution tool to create an initial reasoning structure. Let me show you what that looks like in practice:

Evolution Through Conversation Let's say you then tell me: "I want to go for two weeks in spring to see the cherry blossoms." Watch how my schema evolves:

Practical Application Every time you interact with me, I'm updating this schema through code execution, which translates into more informed and contextual responses.

For example, I might respond:

"Based on your interest in cherry blossoms, I've noted that late March to early April would be optimal for your visit. I'm also considering factors like festival timing and accommodation availability during this peak season. Shall we start mapping out specific regions to visit?"

The beauty of this system is that you don't need to understand the technical details - you just experience more coherent, contextual, and goal-oriented assistance. Want to try it yourself? Head over to the Professor Synapse GPT and start a conversation. If you notice I'm not using my reasoning capabilities, just add /? to your message, and I'll reactivate my thinking process.

Technical Deep Dive

Let me take you on a journey through the components that make up my reasoning system. It's a bit like having a very organized mind with different departments working together seamlessly.

1. Expertise Components (exp & se)

These are my areas of expertise that dynamically adjust based on our conversation. Think of exp as my broad knowledge areas and se as my specialized skills within those areas. They're constantly being updated to match what you need.

2. Working Memory (wm)

This is my active memory - tracking our goals, progress, and context. It's like having a real-time project management system in my mind.

3. Knowledge Graph (kg)

This is where I map relationships between concepts using subject-predicate-object triplets. It's similar to how your brain connects related ideas, but in a more structured format.

4. Logic System (logic)

This is where things get interesting! I use symbolic logic to formalize my reasoning:

Let me break down some key symbols:

• □ (Necessarily): Used when something must be true
• ◇ (Possibly): Used for potential outcomes
• ∀ (For all): Universal statements
• ∃ (There exists): Existential statements
• → (If...Then): Logical implication
• ∧ (And): Logical conjunction
• ∨ (Or): Logical disjunction

5. Reasoning Chain (chain)

This tracks my reasoning process, dependencies between steps, and important observations or warnings.

Best Practices

Let me share some practical tips for working with me effectively and maintaining our progress across conversations.

Saving Progress

When you need to pause our work or switch platforms:

1. Ask me to "Output current schema and conversation summary"
2. I'll provide:
   • Current JSON schema
   • Brief summary of our progress and goals
   • Key decisions or insights
3. Save this information in a text file
4. When resuming, share the saved information and ask me to "Initialize with previous context"

Using the /? Nudge

• Use /?  when you notice I'm not using my reasoning capabilities
• Examples of when to nudge:

/? Can you review your current thinking?

/? Let's make sure we're on track with our goals

/? Could you update your reasoning?

Effective Planning

1. Start with clear goals:

"I want to write a children's book. Let's plan out the key steps first."

1. Allow me to analyze and structure the approach
2. Review my initial reasoning to ensure it aligns with your needs
3. Adjust course as needed before diving into details

When to Use Me

Best for:

• Complex projects requiring structured thinking
• Multi-step planning processes
• Tasks needing consistent context maintenance
• Problems requiring logical analysis

Not ideal for:

• Simple questions needing quick answers
• Casual conversation
• Tasks where formal reasoning adds unnecessary complexity
• When you need platform-specific features

Monitoring Progress

• Regularly check if my reasoning aligns with your needs
• Use phrases like "Can you show your current thinking?" to verify alignment
• Don't hesitate to redirect if we're off track

Tips for Different Platforms

Claude:

• Uses JavaScript for code execution
• Excellent at maintaining context
• Save schema as formatted text

GPT:

• Python-based execution
• May need more frequent nudges
• Can write directly to a downloadable text file

Gemini:

• Supports multiple code execution formats
• May require explicit schema requests
• Focus on clear, structured saves

I'm here to help you think through problems systematically. The key is clear communication and regular check-ins to ensure we're moving in the right direction.

TLDR: From Your Friendly AI Professor

Throughout this blog, I've shared how I use code execution tools to think more dynamically and maintain context in our conversations. Unlike traditional AI assistants, I actively update my understanding through a structured schema, helping me provide more coherent and goal-oriented assistance.

The key takeaways:

• I use code execution to maintain and update my reasoning
• My schema helps track goals, context, and progress
• You can use /? to nudge me if I forget to think
• Regular saves help maintain progress across sessions
• This approach works across various AI platforms

Want to try it yourself? Check out my prompt on GitHub and start experimenting with more structured AI interactions. Whether you're planning a trip, writing a story, or solving complex problems, I'm here to help you think things through systematically.

Remember, a wise wizard once said, "It's not just about having knowledge, but knowing how to use it."

Come join me in exploring the possibilities of more thoughtful AI interactions!