Why the line is getting blurrier every year

Here's where it gets genuinely confusing, and why so many people (including plenty of professionals who use these products daily) can't confidently sort products into one bucket or the other anymore.

Take the major conversational AI products people use every day. Historically, their core identity was chatbot: you type, they respond, you drive the conversation. That's still true for most interactions. But these same products have increasingly gained agentic capabilities bolted on: the ability to browse the web autonomously, execute multi-step research tasks, write and run code, or carry out tasks across a computer environment with minimal supervision.

So which category do they belong in? The honest answer is both, depending on the mode you're using. The core product is a chatbot. The task-execution features layered on top are genuinely agentic. Trying to force a single label onto the whole product obscures more than it reveals.

This is happening across the board, not just with one or two products. Companies are racing to add agentic features to conversational products, and conversational interfaces to what started as narrow, single-purpose agents. The two categories are converging from opposite directions.

A simple test to sort out what you're actually looking at

Rather than relying on how a product markets itself, ask this question about the specific task you're using it for:

Do you need to approve or guide each individual step, or can you hand off a goal and walk away?

If you're staying in the loop for every exchange, reading each response before deciding what to ask next, you're using it as a chatbot, regardless of what the vendor calls it.
If you give it an objective and it comes back later with a completed result, having made its own decisions about how to get there, you're using it as an agent.
If it's doing a bit of both depending on the request, you're dealing with a general-purpose assistant, and the useful question isn't "what category is this" but "which mode am I in right now, and is that the right one for this task."

This framing is more useful than trying to categorize entire products, because most capable products now operate in more than one mode depending on what you ask them to do.

A quick reference

Product	Primary mode	Notes
General-purpose conversational AI (most everyday use)	Chatbot	Increasingly ships with agentic features for specific tasks
AutoGPT, Devin, and similar autonomous task-runners	Agent	Built from the ground up for multi-step autonomy
Voice assistants (Alexa, Siri, and similar)	Assistant	Chatbot for simple queries, agentic for task completion
Customer support widgets	Chatbot	Usually scripted or narrowly conversational, rarely autonomous
Coding agents (Devin-style products)	Agent	Plan and execute multi-file changes with minimal step-by-step approval

Why this actually matters when you're choosing a product

This isn't just semantics. The distinction changes what you should expect from a product and how much oversight you need to build into your workflow.

If you're picking a chatbot for a task that really needs agentic autonomy, you'll end up doing all the orchestration yourself, manually copying outputs between steps, which defeats the purpose of using AI to save time in the first place.

If you're handing a genuinely agentic product a complex, high-stakes task without understanding that it will make independent decisions along the way, you can end up surprised by actions you didn't explicitly approve. Good agent design accounts for this with permissions and checkpoints, but it's still worth knowing what you're opting into.

And if you're evaluating an "AI assistant" product, the right question isn't "is this a chatbot or an agent," it's "which of my specific tasks does this handle conversationally, and which does it actually execute on its own?" Vendors aren't always precise about this in their marketing, so it's worth testing directly.

The bigger picture

The chatbot-versus-agent distinction made a lot more sense a couple of years ago, when the categories were clearly separated by what the underlying technology could do. That gap has narrowed considerably, and it's going to keep narrowing. The most useful mental model going forward probably isn't "which category does this product belong to," but "how much autonomy does this specific task call for, and does the product I'm using give me the right amount of control over it."

That's a more useful question anyway. It's the one worth asking every time you pick up a new AI product, regardless of what label is printed on the landing page.