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Defining the Primitives of AGI
Master the hard problems: Reasoning chains, multi-agent orchestration, and RLHF.
Prove your capabilities: Build production-grade systems with real-world constraints.
Access the infrastructure: 1000+ challenges, 500+ ai tools and frameworks.
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Build Environments Where AI Learns
The learning loop for AI engineers
Every challenge is a learning environment. Design reward signals, run agents against real tasks, and close the feedback loop that makes everything improve.
1000+
Challenges
500+
AI Tools & Frameworks
Environment. Agent. Reward.
The RL stack, made accessible
Environment design, reward engineering, evaluation architecture, multi-agent coordination. Exercise every layer of the stack that makes agents better.
Signal, Not Just Scores
Structured evaluation rubrics
Binary pass/fail doesn't teach anything. Weighted rubrics score across dimensions, giving you the precise signal to know what to improve next.