simulation

You cannot unit-test a stochastic two-agent pipeline with a golden output. You evaluate it the way you stress a distributed system: thousands of simulated runs, controlled fault injection, and a judge calibrated against humans.

The customer wants the agent to practice before it can write to production. Design the task world, reset semantics, tool boundary and verifier, then explain when its scores justify training or release.

You have a coin that lands heads with some unknown probability p. Build a fair 50/50 flip from it without knowing p. The von Neumann trick is two lines; the part that scores is explaining why the bias cancels and how many flips it costs.

A grid where some cells start infected, and each step every infected cell infects its orthogonal neighbors. How many steps until everything is infected, or -1 if some cell is unreachable? This is rotting oranges in disguise, and the multi-source BFS framing is what they want to hear.