MTTR is the wrong metric for Engineering Teams today (www.ito.ai)

The article argues that the traditional metric Mean Time to Recovery (MTTR) is no longer suitable for engineering teams in the AI era, as it fails to capture the rapid increase in code production and the associated rise in bugs and pull requests. With AI tools generating 41% more bugs and complicating deployment processes, MTTR—which focuses on recovery speed—does not effectively address the new challenges posed by AI-generated code and autonomous agents. Instead, the article advocates shifting to Mean Time to Failure (MTTF), which emphasizes preventing negative customer experiences before they occur, rather than simply responding to them after the fact. This transition from MTTR to MTTF reflects an essential change in mindset for engineering teams, prioritizing pre-deployment reviews and runtime analysis to mitigate failure impact. As teams rush to keep up with increased code output, the bottleneck in code review processes becomes more pronounced, potentially leading to widespread negative experiences for users. The shift to MTTF aims to realign team objectives with customer-centric values, ensuring that engineers focus on delivering quality experiences rather than merely fixing issues post-deployment, thereby enhancing overall reliability and user satisfaction in an increasingly AI-driven software landscape.