According to @godofprompt, Anthropic's latest research demonstrates that increased computation time during inference, known as 'Inverse Scaling in Test-Time Compute,' can actually degrade the accuracy of AI reasoning models instead of improving it. This phenomenon, documented in Anthropic’s official paper (source: Anthropic blog, 2026), shows that giving AI models more time to 'think' can lead to worse decision-making, undermining reliability in real-world production systems. For businesses deploying AI for critical reasoning tasks, such as financial analysis or automated compliance, this insight signals a need for rigorous validation and increased oversight in production environments to prevent costly errors and ensure trustworthy outcomes.