Same email. Two ways to ask for help
Dan Scott
Founder, MDJ Studios
A first look; no experience needed:
In short: This article is about agentic AI. Agentic AI can take many different shapes and can be implemented in a variety of ways, each with varying levels of complexity. This piece aims to make the idea accessible to complete beginners by breaking it down through one simple example: an inbox helper.
Imagine getting an important email at work; one of your suppliers asks to move a delivery date. You could paste that email into an AI chatbot and ask what it means and what to write back, or instead, ask AI to "watch" your inbox and only notify you when a real decision is needed.
Those two paths feel similar until you notice who starts the work, what remembers the job, and where you still have to show up. That gap is the simplest way I know to tell chat AI from agentic AI.
I built a side-by-side walkthrough for this. The metaphor below is the same one that demo uses.
The coworker at the desk, and the assistant with a job
Think of a chatbot as a smart coworker at their desk. When you walk over, they help. When you leave, they wait. They're "fluent" with whatever you put in front of them, but don't expect them to keep an eye out for things needing your attention when conditions change.
An agent is more like an assistant you hired for one job. For example, you might have them watch your email, sort it, or notify you when they need your approval on something critical.
You don't restart the conversation every time a new message shows up.
Here's the punch line. If a person still has to start it every time, it is a chat. If something can "run in the background" in a continuous loop, make decisions, and use tools to action on those decisions, we call that an agent.
Here's a side by side comparison
| Asking a chatbot | An AI Agent with tools | |
|---|---|---|
| Who starts it | You, every time | In incoming email; you don't need to open it first |
| Memory | No. Close the window and the job is done | Yes. A saved job can run while you're away |
| What it can touch | Only what you paste. It talks. You do the rest | Open the inbox, file mail, write a draft |
| Where you fit | Almost every step | The decision: should this be sent? |
| Next email | Start over | Already monitoring |
Chat is a conversation you keep opening. An agentic workflow is a job you set up once, then steer with judgment.
Three emails from a fictional class inbox
Picture a training inbox with a few ordinary messages. Nothing fancy. Just enough to see the pattern.
1. Delivery change
Priya from Northwind asks to move a delivery date.
Chat path: You notice the mail. You paste it into the chatbot. You ask AI to summarize it and determine the ask, you also ask it to draft a reply for you. Then, you send it, and archive/file the message. Every step waits on you.
Agent path: The agent uses a tool to monitor your inbox, which triggers an action whenever a new message is received. It reads the email and then determines if a reply is needed; it drafts a reply. Using another tool, it messages you, asking you to review and approve the draft before it sends. After you approve, it sends the message, archives/files the message and keeps watching.
It's the same email, but the difference lies in which steps are AI-owned versus human-owned.
2. Junk newsletter
A newsletter you don't want.
Chat path: You still have to open it, decide it's junk, and trash it. If you want help, you paste it into the chatbot and ask whether it's worth keeping. Then you take the action yourself. The chatbot only helps if you bring it over.
Agent path: The agent is already monitoring the inbox. When the newsletter arrives, it classifies it as junk against rules you set earlier, uses a tool to trash it, and does not ping you. Not every message needs a knock on the door.
It's the same newsletter, but the difference lies in which steps are AI-owned versus human-owned.
3. FYI pallet note
A short note that something landed. No decision needed.
Chat path: If you ask, the chatbot can summarize the note. Then it waits until you walk over again. Filing it, labeling it, and closing the loop still sits with you.
Agent path: The agent reads the note, determines no reply is needed, uses a tool to archive/file it, and stays quiet. Your attention stays free for the messages that need a human call.
It's the same FYI, but the difference lies in which steps are AI-owned versus human-owned.
Why this matters for tech professionals
I've been teaching since 2017 and have trained 1000+ professionals. The question I hear most isn't "which model is smartest." It's "when do I still do the work, and when can a system carry the loop?"
Chat AI is great when you want a fluent answer on demand. You start it, you steer every turn, and you finish the work yourself. Agentic workflows matter when there is a trigger, memory that lasts past one window, tools that can take action, and a clear place for your judgment. That's the shift: from talking to a smart coworker at their desk to hiring an assistant that can run a job in the background and only pull you in when approval is critical.
If you're leveling up in the agentic AI era, start with one boring inbox job. Decide what should wake the agent. Decide what needs a yes from you. Decide what can stay quiet. Then build the workflow around those calls, knowing agentic AI can take many shapes and many levels of complexity. This inbox example is just one accessible way in.
That's agentic work in practice. Not a slogan. A loop you can leave running.