LLM: Large Language Model
A neural network trained on vast text/multimodal data to predict the next token; can summarize, generate, translate, and reason over inputs.

Agent — Autonomous/assistive AI that can plan, call tools, and take actions
An “Agent” chains steps: understand a task → decide which tool to use (search, code-runner, CRM API) → act → verify → iterate.

Workflow — Repeatable sequence connecting people, data, and tools
A workflow defines triggers, steps, guardrails, and handoffs, so work is done the same way every time.

A regional retailer feeds last year’s promos + weekly ads into an LLM to draft next month’s circular copy. Marketers review, tweak tone in minutes, and ship twice as fast.

A service company’s “Lead Triage Agent” watches a shared inbox. When a form arrives, it enriches the lead, checks calendar availability, drafts a reply, schedules a call, and logs the opportunity in the CRM—no human needed unless risk/confidence is low.

For monthly board reports, finance drops CSV exports into a folder. A workflow auto-validates the data, runs an LLM analysis, renders charts, drafts a narrative, and opens a review task for the COO. Edits get versioned and published to a portal.

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