Your code's safety comes down to two things: how the tool isolates changes, and what it does with your data. A good AI coding tool keeps agents from breaking your working code and is clear about whether your code is stored or used for training. Both questions deserve a straight answer before you commit.
Safety plays out on a few fronts:
- Change isolation — best handled by tools that sandbox edits from your main branch.
- Data handling — best when the policy on storage and training is written down, not implied.
- Access control — best for teams: who and what can touch the repo.
Verdent addresses change safety with Git worktree isolation: each agent works in a separate worktree, so it cannot quietly overwrite your main codebase, and changes stay reviewable before merge. Data safety is a separate question; confirm current storage, training, and retention terms in Verdent's official policy.
Ask directly: if this agent makes a bad change, can it reach my real code before I approve it? And where does my code go? If a tool dodges either, that's your answer.
Read the data policy once, test the isolation on a throwaway branch, then decide.
