AI Workflow Store: Google Researchers Argue On-the-Fly Agent Loops Short-Circuit Software Engineering Rigor

arXiv·medium signal

Researchers from Google and Columbia University argue the dominant agent paradigm of synthesizing plans and executing within seconds bypasses iterative design, testing, adversarial evaluation, and staged deployment that make systems reliable. They propose an AI Workflow Store of hardened, reusable workflows that agents invoke with far greater reliability than improvised tool chains, amortizing the cost of rigorous engineering across a broad user community. Identifies a fundamental flexibility-robustness tension in current agent architectures.