Improved data health and incident reduction have revealed issues while AI direction still needs workMonte Carlo needs to stop their reliance on AI, as it is not going well and is degrading the entire product. They need to find their way back, establish a product roadmap, and have real engineers work on improvements rather than heavily push AI down users' throats. They need to stop relying on AI as heavily as they have been doing, as this has really degraded the user experience. The overall direction they are taking with AI needs to be examined, as at some point it seems they have simply stopped making any improvements. We have not used Monte Carlo's AI capabilities significantly. We primarily use it for investigating alerts from time to time. However, we do not use it extensively, so I do not think it is fair to comment comprehensively on it. Their incident tracking and incident debugging bot is useful for new analysts who are starting onboard. It helps them debug incidents, get a clearer picture, and achieve a clear head start to reach the root of the problem faster. Regarding accuracy and reliability, I would rate it at eighty to eighty-five percent. Given the current inherent non-reliability of AI models, every single thing that Monte Carlo says needs to be validated.
