AI coding agents work from available context. If they misunderstand the goal, miss an important file, assume the wrong framework behavior, or skip a failing path, they can produce incorrect code.
In practice
Common failures include off-by-one bugs, broken edge cases, style mismatches, missing migrations, weak tests, hallucinated APIs, and changes that pass a narrow check but fail real usage.
What to watch
The best defense is normal engineering hygiene: clear tasks, small diffs, tests, linters, code review, and staging before production.