Building AI Agents for Workflow Automation on Vercel

"AI agent automation" gets used to describe everything from a single scripted prompt to a fully autonomous system that makes decisions and takes actions on its own. When I say it, I mean something specific: a process that used to require a person reading, deciding, and typing into three different systems now runs on its own, reliably, with a human only in the loop where it actually matters.

On Vercel, that usually means a Next.js app with Functions doing the orchestration, a queue or scheduled job triggering runs, and an LLM handling the parts of the workflow that require judgment rather than a fixed rule. The platform work is often the easy part — the real work is scoping which parts of a workflow are safe to hand to a model and which aren't.

This is the first in a series digging into how I build these systems for clients, from architecture down to the reliability details that separate a working demo from something a business can depend on.