What to focus on when choosing AI: which benchmarks really matter?
Today is Friday, which means a new long article has been published on the paid platform Boosty — in it, I discuss key benchmarks. When a new version of a model appears, the first thing we do is look at the numbers in the tables. Where is there real progress, where does the model stay the same, and where is there a slight regression?
But comparing metrics in percentages is only part of the story. It’s important to understand how these results apply when selecting AI. Some tests are already outdated, others are designed for complex scientific tasks, and most everyday users need entirely different skills — for example, writing engaging blog headlines or helping with a child’s homework.
In the article, I highlight the benchmarks that everyone should pay attention to — office workers, lawyers, product managers, editors, those who enjoy chatting with AI or quickly launching a project in a couple of evenings. It’s also useful to know how to find information online or solve complex problems using OpenClaw.
Finally, I share some observations about two important benchmarks — ARC-AGI and FrontierMath. Monitoring these tests helps understand the overall progress of AI development and the approximate path toward achieving Artificial General Intelligence (AGI).
In conclusion, I recommend subscribing to Boosty: new long articles are released every week. In the future, I plan to compile a small course on AI based on them — it will be useful for both beginners and experienced users.
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