Agentic Workflows

Agentic workflows are multi-step processes where an AI system plans, executes, and iterates on tasks with minimal human intervention between steps. Unlike a single prompt-response exchange, an agentic workflow might involve the AI researching a topic, drafting a document, reviewing it against criteria, revising, and publishing—each step informed by the results of the previous one. The appeal is obvious: you describe the outcome and the system figures out the steps. The risk is equally obvious: errors compound across steps, and the system may confidently execute a plan that was wrong from step two. Production agentic workflows in 2025 tend to be narrowly scoped with clear checkpoints—processing invoices, triaging support tickets, generating reports from structured data. The fully autonomous AI employee that handles ambiguous, high-stakes work without oversight remains aspirational. Building reliable agentic workflows is less about model capability and more about designing the right guardrails, evaluation criteria, and fallback paths.