What Is an AI Agent?
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What exactly is an AI agent and why is the term so controversial?
Today, we're discussing one of the busiest and most confusing terms in AI right now, agents. Are they just fancy wrappers around LLMs, full blown autonomous workers, or something in between? A16Z info partners Guido Appenzeller, Matt Bornstein, and Yoko Lee break down the technical definitions, pricing models, use cases, and why the term agent means so many different things to different people. If you're building, buying, or just curious about what agents are and aren't, this episode is for you. Let's get into it. As a reminder, the content here is for informational purposes only, should not be taken as legal business, tax, or investment advice, or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A sixteen Z fund.
Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast. For more details, including a link to our investments, please see A16Z.com forward slash disclosures.
So I think there's some things which are probably Kind of easy to say, which is A, there's a good amount of disagreement. What is an agent? We've heard a lot of different definitions of it, on the both on the technical side as well, I'd say on the marketing and sales side in some cases, because there's some sales models associated with it. So let's start with with the technical side. I think there's sort of a continuum here. You know, the simplest thing that I've heard being called an agent is business. Just a clever prompt on top of some kind of knowledge base or some kind of context that has this sort of chat type interface. So from a user's perspective, this looks like an human agent would look like, right?
So for example, I ask it, hey, I have a technical problem with my product XYZ, it looks at the knowledge base and comes back with a canned response.
But there it doesn't have to be a knowledge base, right?
It doesn't even have to be a model interface. I see, got it. Okay. So maybe it's just a train model, it's all the model weights, the knowledge. So it's even simpler. So an agent could just be an LLM. Right. But the chat interface or something like that, by some definition. I think on the other end of the spectrum, there's some people who basically say for something to be a real agent, it has to be something fairly close to AGI, right? It needs to persist over long periods of time, it needs to be able to learn, it needs to have a knowledge base, it needs to work independently on problems. If you take then the most extensive definition.
How do the speakers define the technical spectrum of AI agents—from simple wrappers to near‑AGI systems?
Is it fair to say that doesn't work yet?
I think so, it doesn't work yet, although
Will it ever work?
That's a philosophical question.
All right. Fair. Very fair, very fair. So if we take that continuum in between, is there at least a way to to chop that up into a couple of categories of sort of d maybe degrees of agentic behavior.
And different types of agent. There's some artsy agent that help artists to come up with new bezier curves. Yeah.
Yeah.
There's coding agent, which we like to talk about as the agent of use, yeah. Yeah, which we use. There's agent that's just a wrapper on top of L L Ms.
That's right. Yeah. I m I may be the the contrarian in this group. All right. Look, I kind of think agent is just a word for AI applications, right? Anything that uses AI kind of can be an agent now. Before before we started this talk, I actually went online just to refresh myself about some of the more interesting AI agent perspectives out there. I found a really cool talk from Karpathi that he gave a couple of years ago about agents, which I can describe a little bit. But the really funny part was on the YouTube recommended videos to watch next, it's like AI agents are going to revolutionize your lifestyle and the rise of super intelligent AI, you know, it's just kind of like marketing. And so I actually do think that's what's going on in a lot of ways.
The cleanest definition I've seen of an agent is just something that does complex planning. and something that interacts with outside systems.
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Chapters
8 chapters
1
What exactly is an AI agent and why is the term so controversial?
0:03–2:28
2
How do the speakers define the technical spectrum of AI agents—from simple wrappers to near‑AGI systems?
2:28–5:16
3
What are the main categories of agents (coding, artistic, wrapper, autonomous) and how are they used today?
5:16–7:50
4
How should AI agents be priced—per seat, per token, per task, or by value delivered?
7:50–12:43
5
What does a typical AI‑agent architecture look like and which components can be externalized?
12:43–18:31
6
How do data silos, platform restrictions, and privacy concerns affect the deployment of agents?
18:31–24:04
7
Which emerging capabilities (multimodality, web‑browsing, tool integration) will make agents truly game‑changing?
24:04–30:04
8
What milestones must be hit in the next two years for agents to become a mainstream innovation?
30:04–36:09
Speakers
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