Why AI Is Moving Beyond Parameter Counts

This episode explores how a model can leap ahead without adding new parameters, driven instead by post-training reinforcement learning, harness design, and inference-time compute. It also breaks down synthetic environments, verifier agents, and why AI engineers may be shifting from dataset builders to environment architects.