TechCrunch AI’s coverage of Boris Cherny’s talk underscores a broader trend in AI: the push toward continuous, autonomous workflows. While agentic loops promise efficiency, they also introduce risks. For instance, the unending nature of these loops could lead to escalating compute costs, as AI agents perpetually refine code without clear stopping points.
Moreover, the lack of deterministic logic in these loops raises questions about control and accountability. As AI models grow more sophisticated, the industry must grapple with whether such systems are truly advancing productivity or merely creating new layers of complexity. The challenge will be balancing innovation with practicality, ensuring that agentic loops deliver tangible value without spiraling out of control.