Amr Ahmed

Senior Staff Research Scientist at Google whose work focuses on large-scale machine learning, data and web mining, user modeling, personalization, social networks, content analysis, information retrieval, and natural language processing.

Agentic AI Is Turning Model Quality Into a Systems Problem

At AI Engineer Singapore’s second day, speakers from Google DeepMind, Cloudflare, Arize, OpenClaw, Adaption and other teams made a shared engineering case: as AI systems become more agentic, model quality is no longer separable from the systems around the model. Richard Ngo framed the risk as long-horizon, situationally aware agents whose goals cannot be inspected, while practitioners argued that production AI now depends on continuous evaluation, traces, deterministic execution boundaries, routing, memory, fine-tuning and test-time search. The source’s central claim is that useful and safe agentic AI is becoming a systems problem, not just a model-selection problem.

AI EngineerMay 17, 202626 min read