Yes, AI agents can break your codebase if they edit without enough context, skip tests, touch too many files, or merge changes without review. The prevention strategy is isolation, scoping, validation, and human approval.
Common failure modes include changing shared APIs without updating callers, introducing wrong dependencies, deleting useful code, weakening security checks, or fixing one test while breaking another. These are not reasons to avoid agents. They are reasons to run them with engineering controls.
Verdent's Workspace Isolation is the key prevention angle. Each workspace can be isolated through git worktrees, so risky changes do not affect the stable base workspace. Pair that with Plan Mode, test commands, diff review, and selective rebasing. The safest workflow is simple: let agents draft changes, but merge only the changes that pass checks and review.
