RL agents explored billions of game states overnight while the studio slept
Their last major title launched with a game-breaking bug that went viral on Reddit within 2 hours. The emergency patch took 3 days. Steam reviews tanked from 'Very Positive' to 'Mixed.' The QA director estimated the bug cost them $8M in refunds and lost sales. The CEO's exact words: 'Never again.'
A massive open-world game with billions of possible state combinations. Their QA team of 200 testers couldn't cover more than 0.001% of possible scenarios before launch. They'd tried hiring more testers — but at $25-35/hr, the budget for 200 additional QA staff was $10M/year. And even with 400 testers, coverage would still be a rounding error.
We deployed reinforcement learning agents that play through millions of game sessions autonomously, systematically exploring states that human testers never reach. Computer vision models detect visual glitches, physics bugs, and rendering anomalies in real time. A player telemetry pipeline processes billions of events post-launch. Our overnight QA team reviews AI-flagged bugs and writes reproduction cases so the studio has prioritized bug reports every morning.
The AI found a memory leak that only triggered after 47 hours of continuous play in a specific biome. No human tester would have found that. It would have been a day-30 disaster.— QA Director
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