As for good game dev prompts, here's one from a user that made a pretty fun game:
Make asteroids with 2 computers playing against each other on one screen. There should be asteroids flying and 2 ships being controlled by 2 computers. Pay attention to thoroughly implementing the logic to make the ships avoid asteroids at all costs. Absolutely no user input should be necessary, no click to start, no click to restart. The game starts automatically on load and automatically restarts when either computer is dead. The ships should survive as long as possible. The ships should fly around, avoid asteroids as a priority, but also shoot asteroids and each other. Make ships and asteroids positions random each time. Asteroids should split when shot. The goal is to create a robust algorithm for ships so they can survive as long as possible. The game should be playable at 500x500 screen resolution.
Exactly - we think the ai design tools are in the equivalent of the 'uncanny valley' territory that a lot of the diffusion models were stuck in just 1-2 months ago; most average diffusion models are still in this local optimum, but the best of the best seem to have escaped it.
yes! to the second point, someone in our show HN proposed encouraging human designers to compete in submissions as well - we tried implementing this and found that, at least right now, LLMs are still so bad at design that asking a human to beat them is trivial - our plan right now is to focus more on this once it becomes more of challenges and therefore hopefully more interesting/entertaining
Yes — great point. We originally waited for all model responses and randomized the vote order, but that made it a very bad user experience -- some models, especially open-source ones, took over 4 minutes to respond, leading to a high voter drop-off rate.
To preserve the voter experience without introducing bias, our current approach waits for the slowest model within each binary comparison — so even if one model is faster, we don’t display until both are ready. You're right that this does introduce some bias for the two smallest models, and we'd love to hear suggestions for how to make this better!
As for the 5th request: we actually kick off one reserve model alongside the four randomly selected for the tournament. This backup isn’t shown unless one of the four fails — it’s not the fastest or lowest-latency model, just a randomly selected fallback to keep the system robust without skewing results.