A recent study conducted by the nonprofit research organization METR has found that artificial intelligence (AI) coding tools can reduce the productivity of experienced software developers by approximately 19%. The study tracked 16 veteran developers as they addressed 246 real issues within large-scale codebases exceeding one million lines, with half of the tasks performed using AI tools such as Cursor and Claude. Contrary to popular expectations that AI would accelerate coding processes, the findings reveal that seasoned developers working with AI tools often experienced slower completion times. This slowdown is attributed to factors including the need to provide context to AI, verify AI-generated code, and correct errors, which offset potential speed gains. The study's results have been reported and analyzed across various media outlets, highlighting a growing skepticism among senior programmers regarding the reliability and efficiency of AI-assisted coding. Additional commentary from sources like the Federal Reserve suggests that while AI may enable workers to perform tasks faster, it does not necessarily translate to increased overall productivity, as some time saved may be offset by breaks or other factors. Meanwhile, AI continues to advance in other areas such as game testing, where it is helping to accelerate quality assurance cycles and iteration speeds.