The most common mistakes with AI coding agents are giving vague goals, allowing overly broad changes, skipping review, and treating passing tests as complete proof of correctness. These mistakes increase rework and hide risk behind fast output.
Other recurring problems include:
- sending secrets or proprietary data without reviewing provider policies;
- asking for an entire product in one prompt;
- running several agents on the same files without ownership boundaries;
- accepting new dependencies without checking maintenance or licenses;
- letting an agent weaken tests to make them pass;
- mixing refactoring, feature changes, and formatting in one diff;
- ignoring model and usage costs on long tasks.
Use a plan for complex work, assign bounded tasks, isolate workers in separate git worktrees or clones on distinct branches, and require explicit acceptance checks. Review diffs for unrelated edits and run deterministic tooling in CI. Track agent errors and update project rules so the same problem is less likely to recur.
Verdent provides planning, parallel workers, workspace isolation, and review controls that can support this discipline. Features do not enforce judgment automatically, so teams should define permission levels and merge gates. The goal is not maximum autonomy; it is reliable delegation with clear evidence and accountability.
