AI coding agents are fast enough to create a new problem: bad patterns now scale at machine speed. A human developer might copy a risky error-handling shortcut once. An AI agent can repeat it across ten files, wrap it in confident comments, update the tests to match the mistake, and open a pull request nobody wants to review. That does not mean AI coding tools are useless. It means SaaS teams need AI code guardrails : repo-level checks that catch fragile, unsafe, or off-pattern code before it reaches review. This guide shows how to build those guardrails with pre-commit hooks, static analysis, tests, CI checks, and simple policy-as-code. No vendor pitch. No magic prompt. Just practical workflow design for builders shipping AI-assisted SaaS. Why AI-Written Code Needs Guardrails AI coding agents are good at producing plausible code. That is also the risk. They can generate boilerplate, refactor several files, write tests, and connect APIs quickly.…