Build an AI Agent in Telegram with Vercel, Cursor, Composio

Building a functional AI agent involves combining a base chatbot template with external tools for long-term memory, app integrations, persistent personality settings, and scheduled automation to create an autonomous assistant that operates across web and mobile platforms.

• Base foundation — Start with the Vercel AI SDK chatbot template to handle core requirements like authentication, database setup, and the user interface [09:43].
• Tool integration — Use Composio to connect third-party apps like Gmail or Slack, abstracting the complexity of API management and preventing context window bloat [24:08].
• Long-term memory — Add Supermemory to store and retrieve user facts, preferences, and persistent data across various conversation sessions [37:03].
• Agent personality — Define a "soul" (system prompt) in the database to dictate how the AI communicates and behaves, rather than hardcoding instructions [43:58].
• Mobile accessibility — Link the agent to Telegram using a webhook and bot token to allow mobile interaction while sharing the same backend logic as the web version [50:04].
• Scheduled automation — Implement Vercel Cron to create a "heartbeat" that triggers predefined tasks automatically at regular intervals [1:00:06].
• Development workflow — Use Cursor as the primary code editor to build features, run database migrations, and troubleshoot bugs with AI assistance [05:05].

How does Supermemory allow an agent to recall information across different chat sessions? What is the function of context engineering when managing the number of available tools?