A developer at PH3 studio reported that an AI agent successfully implemented a feature to track game achievements but introduced inefficient code. The AI added a full scan of up to 11,000 game entities on every simulation frame to verify conditions.
The developer noted that the task could have been completed by extending existing processing and storing a maximum of five elements. According to his estimates, the AI's initial solution consumed at least 100 times more CPU time than necessary, though it did not cause a noticeable drop in game performance.
The author emphasizes that functional tests alone do not account for performance costs. Evaluating generated code requires checking the impact on the system, as repeated inefficiencies across multiple functions can lead to significant slowdowns.
The article suggests that when using AI for coding, teams should measure the total time spent on task definition, review, and corrections rather than just the speed of patch generation. This approach helps determine the actual efficiency of integrating AI tools into the development workflow.
