This n8n workflow automates sending personalized direct messages (DMs) to your new Twitter followers using AI and vector-based memory. By integrating Cohere embeddings, Pinecone vector database, OpenAI, and Google Sheets, the system intelligently processes follower data, stores vector context, and enables Retrieval-Augmented Generation (RAG) responses—creating a smarter and more human-like auto-DM experience.
Key Features
✅ Webhook-Triggered Automation
Starts when a new Twitter follower triggers the webhook.
✅ Text Processing & AI Embeddings
Splits and embeds input content using Cohere to build contextual understanding.
✅ Vector Storage via Pinecone
Stores embedded follower context in Pinecone for semantic memory.
✅ RAG-Powered AI Agent
Uses OpenAI’s chat model combined with stored context for natural and personalized message generation.
✅ Google Sheets Integration
Logs status or results to a Google Sheet for tracking and record-keeping.
✅ Slack Error Alerts
Automatically notifies your Slack channel if any step fails.
Use Case
Perfect for creators, influencers, SaaS founders, or Twitter marketers who want to automatically engage new followers with intelligent, tailored DMs—without sounding robotic.
