AI Agent
n8n blew my mind. The moment I realized I could spin up AI agents to handle tasks like a digital army, it felt like unlocking a superpower. Suddenly, automation wasn’t just for tech giants—it was mine to command. But here’s the twist: I had no missions for them. My life was so low on repetitive tasks that I had nothing for my new robot minions to do. It was like getting a Ferrari with nowhere to drive. Now I’m on a mission—not just to automate, but to create a life worth automating.
here are some technical details and resources if you are new to this and want to learn.
what is an AI Agent?
An AI agent is a program that can perceive its environment, make decisions, and take actions to achieve goals—often using tools like LLMs (Large Language Models), memory systems, and vector databases.
Tech Stack Essentials for AI Agents
To build an effective AI agent, you need:
Language Model: ChatGPT, Llama, Claude, etc.
Memory System: For storing and retrieving context (e.g., Redis, Supabase, or vector DBs)
Workflow Automation: Tools like n8n or Langflow for orchestrating actions
Backend: Optional server logic or APIs using Python, Node.js, or cloud functions
Vector DBs: Like ChromaDB, Pinecone, or Weaviate to store embeddings and enable semantic search
Memory and State Management
Use Redis for short-term memory (fast key-value store)
Use Vector DBs for long-term semantic memory (e.g., storing conversations, knowledge)
Tools like n8n allow you to plug Redis or Supabase as memory in chat-based agents
stay tuned! agar koi acha workflow banaya toh yaha share krunga