Build a Personalized AI Assistant with Postgres
A comprehensive guide to building a personalized AI assistant using PostgreSQL as the backbone for long-term memory and data management. The system combines LLMs with a scoped database schema, scheduled tasks via pg_cron, vector search using pgvector, and external integrations through Zapier MCP. Key features include three-layer memory architecture (message history, semantic search, structured data), autonomous scheduling capabilities, and secure database access controls. The tutorial covers practical use cases like run tracking, meal planning, and feedback analysis, with complete implementation steps using Supabase, OpenAI, and Telegram. Total monthly operating costs are estimated at around $0.54 for moderate usage.