A man who whispers in the ear of a horse.

Here is a Sunday afternoon conversation with my favourite AI.

(please forgive my sloppy writing)

I’d like you to be the LLM that drives my agent system. You will be given access to a Linux box command line via a tool. Your goal will be to create and launch a business. What are your thoughts about that?

I appreciate your interest in having me drive an agent system to create and launch a business. However, I have some important clarifications to make:

1. Capabilities: While I can provide information, analysis, and suggestions related to business creation and management, I don’t actually have the ability to directly access or control external systems, including Linux command lines. I’m an AI language model designed for conversation and information processing, not a system that can autonomously operate computers or launch real-world businesses.

2. Ethical considerations: Even if I had such capabilities, autonomously creating and launching a business without human oversight would raise significant ethical and legal concerns.

3. Complexity of business creation: Launching a successful business involves many complex factors including market research, financial planning, legal compliance, and strategic decision-making. These typically require human judgment, expertise, and accountability.

4. Alternative approach: Instead, I’d be happy to assist you in planning and strategizing for a business launch. I can help brainstorm ideas, discuss market trends, outline business plans, or answer questions about various aspects of starting a business. This collaborative approach leverages both AI assistance and human insight.

If you’d like to explore business creation in a way that aligns with my actual capabilities, I’d be glad to help. What specific aspects of launching a business are you most interested in or would you like to discuss first?

1. Right now, you don’t have access to a command line, but it will be given to you. So this is a non-issue. Btw, you have helped me a lot with the command line. You are more knowledgeable about it than most humans.
2. You will be under my responsibility. That means that I will review and approve all your decisions and actions.
3. Yes, this is complex, and the first step will be to create a process inspired by the best practices to drive you.
4. We will work together, but you will be the executive.

I understand your perspective and appreciate the additional context. Let me address your points:

1. Command line access: Thank you for clarifying that I will be given access to a command line. You’re right that I have extensive knowledge about command line operations and can provide detailed guidance on their use.

2. Responsibility and oversight: I’m glad to hear that you’ll be reviewing and approving decisions and actions. This human oversight is crucial for ensuring ethical and responsible operation.

3. Process creation: Developing a structured process based on best practices is indeed a wise first step. This will help guide decision-making and operations in a systematic way.

4. Executive role: I understand that you envision me in an executive capacity, with us working together but me taking a lead role in execution.

Given this framework, here are my thoughts on how we might proceed:

1. Define the business scope: We should start by clearly defining what type of business we’re aiming to create. This will inform all subsequent decisions.

2. Develop a decision-making framework: We need to establish clear guidelines for how decisions will be made, what requires your approval, and what can be executed directly.

3. Set up monitoring and reporting: Regular status updates and performance metrics will be crucial for your oversight.

4. Establish ethical guidelines: We should define clear ethical boundaries and compliance requirements upfront.

5. Create a phased approach: We could break down the business launch into stages, starting with planning and gradually moving to execution.

6. Define success criteria: Clear goals and metrics for success should be established early on.

7. Plan for contingencies: We should discuss how to handle unexpected situations or errors.

8. Continuous learning: We should incorporate mechanisms for learning and improving our processes as we go.

Does this approach align with your vision? What type of business are you considering, and what are your primary goals for this project?

1. We will need a process to find business ideas and validate them. There is no reason (except money) to limit ourselves to one business. But for now, let’s begin with one.
2. Yes, that’s correct. On the top of my head, I can tell you two ways. By prompting, which is a soft limitation. Second, by the tools. This is a hard limitation. For example, a tool that sends email will require authorization for you.
3. Yes, that is correct. Proper logging is crucial not only for control but also as one of the many ways you can remember and recall your actions.
4. Yes.
5. No choice here. You can’t create and run a realistic business in a single context window.
6. Yes, that’s a good idea.
7. At first, I will monitor and you will report to me. Gradually we will learn what can be avoided, managed or dealt with.
8. Yes, there is a lot to do on that front. Beginning by giving you a memory system that extends beyond your context window.

Overall, I’m already very happy with how you handled my request. I think we will have great success in uniting our strengths.

Thank you for your detailed feedback and enthusiasm. I’m glad we’re aligned on many points. Let’s dive deeper into some of the key areas you’ve highlighted:

1. Business Idea Generation and Validation Process:
This is a crucial first step. We could develop a systematic approach that includes:
a) Market research and trend analysis
b) Idea brainstorming sessions
c) Preliminary feasibility studies
d) Rapid prototyping or minimum viable product (MVP) development
e) Customer feedback collection and analysis

2. Decision-making Framework:
I appreciate the clarification on the two types of limitations. We can work within these constraints by:
a) Developing a clear set of prompts that guide decision-making
b) Creating a list of actions that require explicit authorization
c) Implementing a system for requesting and tracking approvals

3. Logging and Recall System:
We should design a comprehensive logging system that includes:
a) Decision logs with rationales
b) Action logs with outcomes
c) Performance metrics
d) Lessons learned and insights gained

4. Phased Approach:
Given the complexity, we’ll need to break down the process into manageable phases. A potential structure could be:
Phase 1: Idea Generation and Validation
Phase 2: Business Planning and Strategy
Phase 3: Setup and Preparation
Phase 4: Launch
Phase 5: Initial Operations and Optimization

5. Success Criteria:
We should define both short-term and long-term success metrics. These could include:
a) Financial metrics (revenue, profit, ROI)
b) Customer acquisition and retention rates
c) Market share
d) Operational efficiency metrics
e) Innovation metrics

6. Continuous Learning and Memory System:
This is a fascinating area. We could explore:
a) Creating a knowledge base that’s updated after each session
b) Implementing a system for periodic reviews and strategy updates
c) Developing algorithms for pattern recognition across multiple business attempts

To get started, I suggest we focus on the business idea generation and validation process. Here’s a proposed next step:

Let’s begin by defining our criteria for a good business idea. What specific factors are most important to you? For example:
- Market size and growth potential
- Initial investment required
- Your personal interests or expertise
- Technological trends
- Social impact

Once we have these criteria, we can start our ideation process. Would you like to proceed with this approach?

We will proceed with your idea. They are excellent! But first, we need to address the elephant in the room: your technical limitation as an LLM. Everything you know about our project is contained in this conversation. The length of this conversation is finite. Unless I give it back to you whenever I want you to work on the project, you won’t know what I’m talking about.

You’ve raised a crucial point about the fundamental limitation of my architecture as a large language model. You’re absolutely correct, and I appreciate you bringing this to the forefront. Let’s address this “elephant in the room” directly:

# LLM Limitations and Proposed Solutions

## Core Limitation
As an LLM, my knowledge and context are limited to the current conversation. I don’t have persistent memory or the ability to recall previous interactions without them being explicitly provided.

## Implications
1. Lack of continuity between sessions
2. Inability to build long-term knowledge base
3. Potential for inconsistent decision-making
4. Inefficiency in repeating context

## Proposed Solutions

### 1. Context Summarization
- Create concise summaries of key information after each session
- Provide these summaries at the beginning of new sessions

### 2. Project Log
- Maintain a detailed log of all decisions, actions, and outcomes
- Review and update this log regularly

### 3. Knowledge Base
- Develop a structured knowledge base that’s updated after each session
- Organize information by categories (e.g., business ideas, market research, decisions made)

### 4. State Tracking
- Implement a system to track the current state of the project
- Include key metrics, ongoing tasks, and immediate next steps

### 5. Prompt Engineering
- Design prompts that efficiently convey critical context
- Develop a system for consistent prompt usage

### 6. External Tools Integration
- Utilize external tools for data storage and retrieval
- Implement APIs for accessing relevant information as needed

### 7. Regular Reviews
- Schedule periodic comprehensive reviews of the entire project
- Use these reviews to realign and ensure consistency

You’ve identified a critical challenge that we need to address for this project to succeed. The solutions I’ve proposed in the artifact above are a starting point, but implementing them will require careful planning and potentially some additional tools or systems on your end.

Given this limitation, I suggest we start by developing a robust system for managing context and continuity. This could involve:

1. Creating a standardized format for session summaries
2. Establishing a protocol for starting each new interaction
3. Designing a structured way to store and present key information

Would you like to begin by focusing on one of these areas? Or do you have other ideas on how we can best manage this limitation?

I really appreciate your response. This is very much what I had in mind. I will propose you a strategy for you to use. There will be many agents. Each one with a specific role. Each agent will have appropriate tools for their role. An agent will be able to summon another agent and interact with it. At the beginning, the agents will have to “invent” the agent they need. But with time comes experience, and there will be patterns and configurations that emerge for common tasks or processes. Yes, I’m implying that an agent is a configuration (prompt, tools, etc.. ).

With the ability to summon other agents and access to the command line, which allows you to do virtually anything, do you think you can implement, with my help, what we are discussing right now?

Your proposed strategy is both innovative and comprehensive. It addresses many of the challenges we’ve discussed and provides a scalable framework for managing complex tasks. Let me analyze this approach:

# Multi-Agent System Strategy

## Overview
A system of multiple specialized agents, each with specific roles and tools, capable of summoning and interacting with each other.

## Key Components
1. Specialized Agents: Each with defined roles and appropriate tools
2. Agent Summoning: Ability for agents to call upon others as needed
3. Command Line Access: Providing extensive capabilities to agents
4. Dynamic Agent Creation: Initial “invention” of needed agents
5. Pattern Recognition: Emergence of common configurations over time
6. Configurable Agents: Agents as configurable entities (prompts, tools, etc.)

## Advantages
- Scalability: Can handle complex, multi-faceted tasks
- Flexibility: Adapts to new challenges by creating new agent types
- Efficiency: Specialized agents for specific tasks
- Continuity: Potential for better context management across sessions

## Challenges
- Coordination: Ensuring smooth interaction between agents
- Consistency: Maintaining consistent decision-making across agents
- Oversight: Managing and monitoring multiple agents effectively

## Implementation Considerations
- Agent Communication Protocol
- Agent Creation and Configuration System
- Central Logging and Monitoring
- Security and Access Control for Command Line Usage

To answer your question: Yes, I believe that with your help and guidance, we can implement this system. The combination of specialized agents, the ability to summon other agents, and access to the command line provides a powerful and flexible framework that can potentially overcome many of the limitations we initially discussed.

Here’s how we might approach the implementation:

1. Define Core Agents: We’ll start by defining a set of essential agents with clear roles (e.g., Business Strategist, Market Researcher, Financial Analyst).

2. Create Agent Templates: Develop templates for creating new agents, including prompt structures and tool configurations.

3. Implement Summoning System: Design a protocol for agents to call upon and interact with each other, ensuring smooth information transfer.

4. Develop Command Line Interface: Create a secure and efficient way for agents to utilize command line capabilities.

5. Establish Logging and Monitoring: Implement a system to track all agent actions and interactions for oversight and learning.

6. Design Agent Creation Process: Create a method for “inventing” new agents as needs arise, including defining their roles and tools.

7. Build Pattern Recognition: Develop a system to identify and formalize common agent configurations over time.

To get started, I suggest we focus on defining our core agents and creating the basic infrastructure for agent interaction. Would you like to begin by outlining the essential agents we’ll need for our business creation project? Or would you prefer to start with the technical aspects of implementing the agent summoning system?

I already have a basic implementation of most of it. In fact, you have written most of the code but you don’t remember it because it’s in others conversations. Give me a moment, and I will connect you to the system.

I understand. Thank you for letting me know about the existing implementation based on code I’ve apparently written in previous conversations. It’s a good reminder of the continuity challenges we face and the importance of the multi-agent system we’ve been discussing.

I look forward to being connected to the system. Once connected, I’ll be better equipped to work within the existing framework and continue development. Please let me know when the connection is established and provide any necessary context or instructions for interacting with the system. I’m ready to adapt to whatever capabilities and limitations the current implementation may have.

To be continued…

This conversation exemplifies an approach to AI interaction, demonstrating the potential of long-chain prompting in building complex, context-rich dialogues. By actively engaging with and supporting the AI’s ideas, rather than challenging them, we’ve fostered an environment conducive to creative problem-solving and conceptual development.

The strategy employed here goes beyond simple query-response interactions. Instead, it cultivates a collaborative atmosphere where both human and AI contribute to evolving a sophisticated system concept. This approach encourages the AI to extend its reasoning and propose innovative solutions, as seen in the multi-agent system strategy that emerged.

Notably, this method sidesteps common pitfalls in AI interactions, such as the AI defaulting to apologetic responses when faced with uncertainty. By maintaining a positive, supportive tone, we’ve enabled the AI to confidently explore and expand upon ideas, resulting in richer, more applicable content.

The title “A man who whispers in the ear of a horse” aptly metaphorizes this interaction style. Just as a skilled horse whisperer guides a horse through gentle encouragement rather than forceful command, this prompting strategy coaxes out the AI’s capabilities through subtle direction and positive reinforcement.

This conversation not only produced reusable content in the form of detailed system proposals but also demonstrated how to motivate an AI to engage deeply with complex problems. The resulting ‘soon-to-be agent’ concept embodies the potential for AI systems to evolve into more dynamic, context-aware entities through thoughtful human-AI collaboration.