Grock's capability to handle a massive inference budget with low latency is crucial for powering agentized models that require repeated inference to execute complex real-world tasks efficiently. This shift in computing emphasizes the importance of inference over training time compute budgets. Grock's performance presents a promising proof of concept for scaling up and enabling various agentized applications, although the extent of its success is yet to be determined.