What is EduRag's backend stack?

FastAPI for endpoints, Supabase PostgreSQL (eight tables, RLS everywhere), Hindsight for memory, SlowAPI rate limiting, WebSockets for chat.

How do you fix silent async failures in FastAPI?

Ditch fire-and-forget tasks. Go synchronous or use proper queues. Track status with job IDs and polling.

Why use Supabase for AI vector search?

Built-in array ops for cosine similarity. No Python overhead. RLS secures it. But watch vendor lock-in.

🏗️ DevOps & Infrastructure

[Backend Secrets] AI Platform Infra Nobody Talks About

A backend engineer's confession: Good infra vanishes until it breaks. Here's the gritty truth from EduRag's Supabase-to-Hindsight stack that powers real AI without the hype.

Open Source Beat Apr 16, 2026 4 min read

Terminal screen showing Supabase schema for EduRag AI backend with PDF indexing pipeline

⚡ Key Takeaways

Supabase with RLS enforces auth at DB level, preventing app bugs from leaking data. 𝕏
Asyncio background tasks caused silent PDF indexing failures — fix with sync calls or tracked jobs. 𝕏
Hindsight memory auto-retains RAG facts per-user, powering personalized AI recommendations. 𝕏
Eight-table schema handles users, searches, PDFs, chunks, and embeddings without local storage. 𝕏