Rethinking AI Evaluation: Beyond Static Benchmarks
Why the next generation of evaluation must be dynamic, adversarial, and grounded in real-world complexity. We explore the tension between reproducibility and ecological validity.
Read moreBuilding Agents That Learn from Practice
How iterative self-improvement and structured practice unlock new levels of agent capability.
Read moreThe Practice Hypothesis
Our founding thesis — deliberate practice isn't just for humans. It may be the key to machine intelligence.
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