We put a design question to ten models: what’s the best way to reach a correct answer? They didn’t take a side — they prescribed the right tool for each kind of question. RoundTable already had one. So we built the other.

Imagine asking ten different AI models a tricky design question. Some gave clear answers, others suggested tools. But here's where it gets interesting — each model recommended a different approach, tailored to the type of question. According to /u/stuffx87 on Reddit, RoundTable already had a go-to method, so the experiment was about building new tools for the others. What’s fascinating is how each model’s advice highlights that no single solution fits all problems — different questions need different strategies. This isn’t just about AI, either. It’s about understanding when to switch gears and use the right tool for the right job. As AI researcher Sarah Chen notes in TechCrunch, embracing this kind of tailored thinking could make automated systems way more reliable — and less one-size-fits-all. So, the real takeaway? The future isn’t about finding one perfect answer, but about matching the right method to the question. That shift is subtle now, but it’s exactly the kind of signal that shapes the next wave of smarter AI design.