We're Tutor Intelligence, a robotics company building generally capable robot workers for American industry. We've been thinking about what technical evaluation should look like in a world where AI agents can 1-shot our hardest hour-long coding interviews, and this is one of our first experiments.
The challenge: command 5 robots in a 60x40 warehouse to fulfill 1000 orders. Your score is the number of timesteps to complete everything. Robots can move, pick items from pallets, dock to pallets (so they move together), and fulfill orders at the edge of the warehouse. Simple rules, but the optimization problem has surprising depth (it's NP-hard in about 10 different ways) with lots of room for strategy and creativity.
This is actually a simplified version of a real problem we work on. Warehouse coordination is one of those domains where the gap between a naive solution and a good one is enormous, and there are many valid approaches.
We built a web visualizer so you can see your solution play out, and a leaderboard if you want to submit. AI agent use is encouraged (probably necessary). So far only my cofounder and I have submitted, so we genuinely have no idea how good solutions can get.
Sharing this early because we'd love feedback on the problem design. And yes, we're hiring (that's why we made it): 70 people, Series A, based in Boston, founded out of MIT. But mostly just curious if others find this problem as interesting as we do.
- It would be good to put what you are planning to learn from this interview process. - Looks like submission is only a text file. Why not ask for chat transcript? - Also, would be useful to let people know what happens after submission/selection.