Let’s talk about the promise vs. reality of “vibe coding.” We were sold this idea that you prompt an agent, it builds your app, you deploy, and everything is fine. That works for simple demo apps. But the moment you need a real backend—user data, schemas, auth, storage, migrations—most AI coding agents start hallucinating APIs, generating broken config, and you end up manually debugging infrastructure (which is the exact thing you were trying to avoid). In this video I walk through an approach that actually matches how agents work: using InsForge as a semantic layer between the coding agent and backend infrastructure. It’s open-source (Apache 2.0), can be self-hosted in Docker, and also has a cloud option (which I used here). I connected Codex to InsForge via MCP, then had it deploy a production-style backend for my agentic file search RAG project. In 28 minutes it stood up Postgres/pgvector tables for corpora, documents, chunks, schema, and embeddings—plus file storage, row-level policies, secrets, and optional OAuth auth. The key takeaway: if you give agents a real “infrastructure environment” instead of raw backend complexity, they stop guessing and start shipping. And because it’s open source, you can inspect what’s happening and run it on your own stack if you don’t want a hosted platform.