Hi HN,I built a live tracker to visualize the lifecycle and performance changes of flagship AI models.We've all experienced the phenomenon where a flagship model feels amazing at launch, but weeks later, it suddenly feels a bit off. I wanted to see if this was just a feeling or a measurable reality, so I built a dashboard to track historical ELO ratings from Arena AI.Instead of a massive spaghetti chart of every single model variant, the logic plots exactly ONE continuous curve per major AI lab. It dynamically tracks their highest-rated flagship model over time, which makes both the sudden generational jumps and the slow performance decays much easier to see. It took quite a lot of iterations to get the chart to look nice on mobile as well. Optional dark mode included.However, I have a specific data blindspot that I'm hoping this community might have insights on.Arena AI largely relies on testing API endpoints. But as we know, consumer chat UIs often layer on heavy system prompts, safe...