Maintaining a Government Custom GPT Demands More Skill Than Building It

A custom GPT built for a government ministry training program may appear complete once the training session ends, but real challenges emerge months into actual use. As procedures are revised, terminology shifts, and departments are reorganized, the tool's knowledge base quietly drifts out of sync with current reality. Unlike outright failures, this degradation is hard to detect because the system continues responding confidently even when its information is outdated. Maintenance requires periodically auditing the existing knowledge base against live source material — a more delicate task than the original build, since it must identify what has become inaccurate without disrupting what remains correct. Yet this ongoing work rarely receives the same resources or attention as initial development, as it lacks the visibility of a concrete deliverable.