How to Build Your PERSONAL Prompt Engineer Agent with n8n (for any model!)
AI Summary
Summary of Mini Prompt Engineer with n8n
Overview: The video demonstrates creating a mini prompt engineering tool using n8n to facilitate prompt creation for various language models (LMs) such as OpenAI, Anthropic, and Gemini.
Workflow Components:
- AI Agent: Central node for handling chat inputs and generating prompts.
- Chat Node: Users input their desired prompt specifications, which the AI agent processes.
- Sub-Workflows: Individual workflows optimized for specific LMs (OpenAI, Anthropic, Gemini) to produce tailored prompts.
Prompt Creation Process:
- User Input: Users specify prompt details (e.g., topic, expected output).
- AI Model Selection: Users select the desired LM for prompt optimization.
- Response Generation: The AI generates a prompt that aligns with the user’s request.
Optimization Techniques:
- The workflow verifies and refines the initial prompt for quality.
- Different LMs require varying prompt structures; for example, reasoning models require less explicit guidance than non-reasoning models.
Performance Considerations:
- Users must ensure the prompt fits within the token limitations of the selected LM (e.g., OpenAI models have lower token limits compared to Gemini).
- Workflow allows for flexibility in choosing models based on context size and operation specifications.
Future Adaptability:
- The creator emphasizes the need for ongoing research to refine prompting techniques as new models emerge and adjust strategies based on model behavior and performance.
This tool serves as a versatile solution for efficiently crafting prompts tailored for various AI applications, aiming to reduce the guesswork involved in effective prompt engineering within n8n.