Nik Pash

This talk argues that the effectiveness of AI coding agents is primarily determined by the underlying model's capability, not by complex engineering scaffolds. Frontier models, when unhindered, can outperform many agent combinations. The core message is to simplify agent engineering and focus on improving model training through robust benchmarks and reinforcement learning environments derived from real-world coding tasks.