Building Multi Agentic Text to SQL with Guided Error Correction | RAG Development | Tech Edge AI

What if your AI could think through database queries, spot its own mistakes, and fix them automatically? That’s exactly what SQL-of-Thought does — a new multi-agent Text-to-SQL framework that reaches 91.59% accuracy using guided error correction and chain-of-thought reasoning. In this video, we break down: ⚙️ How 6 specialized AI agents collaborate to convert text → SQL 🧩 Why single-agent systems like GPT-4 fail on complex joins and aggregations 🔍 How SQL-of-Thought classifies 31 types of SQL errors across 9 categories 🔁 How the correction loop diagnoses schema mismatches and fixes queries 🚀 Live demo: building and debugging real SQL with GPT-4o-mini and DuckDB 💡 Future ideas — value retrieval, latency tradeoffs, and fine-tuned agent roles This is AI-driven data engineering, where language models reason, debug, and self-correct — step by step. 📄 Paper: arxiv.org/pdf/2509.00581 #SQLofThought #TextToSQL #AIagents #MachineLearning #ArtificialIntelligence #DataScience #LLM #GPT4 #OpenAI #DatabaseAI #Automation #ChainOfThought #AIresearch