Agents are easy to demo. The backend they need is the part I keep thinking about.

Reddit r/AI_Agents Tools

Summary

The author argues that while AI agent demos are simple (model + tools + loop), production agents require a robust backend covering auth, persistent data, vector search, permissions, retries, and LLM usage tracking, and describes building Singlebase as that agent-ready backend with MCP access.

Agent demos are usually: model + tools + loop. Production agents seem to immediately need a lot more: identity/auth, persistent application data, vector/search, files, tool permissions, retries/background work, LLM usage tracking, and a clean way to expose capabilities. That's the direction I've been taking Singlebase: instead of making "an agent framework," I'm trying to make the backend an agent can actually use, including MCP access to application data/services. Curious what people here consider the minimum production backend for an agent. What do you always end up adding after the first prototype?
Original Article

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