SPADE enables agents to self-play and generate increasingly difficult training environments
teortaxesTex · x · 2026-08-21
SPADE proposes a framework where agents self-play to generate and continuously improve their own training environments. One model acts as both the Environment Designer and the Reasoning Agent, creating executable agentic environments that scale in difficulty as the agent improves, paving the way for recursive self-improvement.
Related event: SPADE: Single-Model Self-Play Writes Its Own Training Environments(13 posts)→
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