I Built An n8n Agent That Builds Other Agents (Game Changer)
AI Summary
Video Summary: Building an On-Demand Agent Creation Workflow
- Introduction
- The presenter built a neural network (NN) agent to generate new agents on demand by scanning a database of automations and researching documentation.
- The system creates workflows and provides hyperlinks for easy import into workspaces.
- Main Workflow Structure
- Minimalistic chat interface for requesting agent builds.
- The AI agent invokes secondary workflows based on user prompts.
- Example: A Slack to Google Sheets workflow.
- Generality of Workflow
- The process can adapt to various tools (e.g., Jira, Zoom) and can handle vague prompts effectively.
- Uses OpenAI for refining vague requests.
- Automation Database
- The agent can access a library of automations for reference.
- This library increases the likelihood of successfully constructing workflows based on user input.
- Detailed Steps
- Chat and AI Module Integration: sending user queries to the AI to generate structured workflows.
- Utilizing OpenAI: to analyze and refine requests.
- Perplexity for Research: searches for relevant documentation to support workflow creation.
- JSON Construction
- Workflows are constructed in JSON format, which is essential for successful imports into the NN environment.
- Addressing common JSON issues like property names and comments that can cause import failures.
- Final Steps
- The result is a new workflow URL generated and displayed in the chat.
- Demonstration of how to create workflows based on user requests.