@elonmusk Speed and price matter, but model quality still depends heavily on the task. That’s why side-by-side testing is more useful than trusting one leaderboard.
@AlexFinn The biggest opportunity isn’t just getting more people to try AI. It’s helping them choose the right model and turn occasional use into a daily workflow.
@omkarships You win through execution: better UX, sharper positioning, faster iteration, and deeper understanding of the customer. The AI tools are the same. The product isn’t.
@thsottiaux Removing limits for a weekend is probably the fastest way to discover what power users actually build—and where the real product bottlenecks are.
@YashHustle_22 Depends on the task. I usually compare a few models side by side because the “best” one changes between coding, research and writing. That’s exactly why I built https://t.co/rdZjOXZ24e.
@karpathy This is where long-context models get really interesting: not just generating more, but maintaining consistency across an entire world, story, and visual style. The real benchmark is whether they can keep all those details coherent without drifting.
One prompt. Multiple AI models. Better answers. Compare ChatGPT, Claude, Gemini and more in one place with https://t.co/rdZjOXZ24e
Which AI model do you use most?
#AI#BuildInPublic