A small model beat a Red Alert mission for less than half a cent.
One infantryman. Two percent of the map visible. No enemy in sight. Fourteen model decisions later, Red Alert’s own mission logic declared victory.
The player is Jev 1.13, a small structured decision model from TypeSafe. It does not write prose. It reads a block of state, answers typed questions with calibrated probabilities, and returns a choice. The game is the original Red Alert, and the mission is the first on the Soviet side: Lesson in Blood.
At frame zero Jev controls a single Soviet rifleman. It can see no enemies, and almost the entire map is still hidden. The harness offers ten legal choices. Jev chooses to move five cells east, with moving two cells west as the close alternative.
Five hundred frames later that choice has opened the map. Four hundred and ninety-four cells have been explored, the first French position is in view, and three Yak attack aircraft have arrived.
Three layers do three different jobs, and keeping them apart is the whole design.
Jev does not have to rediscover the mouse, and it is not told which option is correct.
Units die. Groups disagree. Some decisions are close calls.
At frame 3,000 the Yaks choose a French building, while the surviving riflemen choose to move south towards the Yaks rather than attack an enemy nearby.
By frame 4,500 Jev has concentrated everything on a single French building: the Yaks, nine riflemen and four grenadiers. At frame 5,000 the building is gone from view and only one visible enemy remains. Every available group is sent after it.
Over the next five hundred frames another hundred and eighty-two cells come into view, and with them a fresh set of French units and buildings. Jev suddenly has large decisions to make again.
At frame 6,000 another reveal exposes two French pillboxes. The simulation keeps moving, and Jev keeps choosing from the legal actions in front of it rather than working through a list of targets.
At frame 6,500, with close to ninety percent of the map revealed, the Yaks choose a French Jeep from thirty-seven options. The grenadiers choose a French rifleman from another thirty-seven, with the Jeep as their close alternative.
No fifteenth decision was needed. Red Alert kept running.
Orders resolve, units move, the fighting continues. Then the game’s own mission logic fires, and the mission is won at frame 6,760.
Every decision, straight from the run’s record: what each group chose, and how many options it was choosing between.
Yes, with an important qualification. This is not Jev learning a strategy game from raw pixels. The harness gives it structured, player-visible state and generic scaffolding for making a decision.
The line that matters is that the harness makes each decision legible without knowing which option is strategically right. The run’s messier choices, and especially the fondness for barrels, are what exercising a real choice looks like.
Between those fourteen calls the game does what games already do well: movement, combat, visibility, reinforcements, orders that go stale, scripted events. Asking a model to reproduce any of that would waste inference on problems the game has already solved.