Agentic Workflows
Overview
Agentic workflows study how language-model agents plan and carry out multi-step tasks by calling tools, coordinating specialized agents, and maintaining state or artifacts. Systems range from fixed graphs and typed protocols with deterministic checks to dynamically planned workflows that use reusable skills, human approval, and execution feedback. Work includes scientific and enterprise automation, workflow generation and evaluation, and serving methods such as model routing, caching, scheduling, and parallel execution. A central challenge is balancing flexible autonomy and efficiency with dependable, auditable behavior, since successful outputs can conceal unsafe shortcuts, semantic errors, privacy leaks, or failures that compound across steps.
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