An AI app security checklist for builders moving from demo to production
A production AI app needs more than a safe-looking system prompt. Before you ship, you need a boundary around every input, model call, tool invocation, database write, and user-visible output. This AI app security checklist gives you that boundary in concrete terms.
The short version: authenticate the caller, authorize each resource, treat retrieved text as untrusted data, validate model output before using it, keep tools narrow, store secrets outside code, cap spend and rate, and log enough context to investigate a bad result without logging private data by accident. These controls matter whether your first version was written with Cursor, Claude Code, or another AI coding tool.
This is an excerpt. Read the full post at otf-kit.dev/blog/ai-app-security-checklist — full-stack kits your AI coding agent can actually ship to production. Browse the kits →
