Written by: Daniel Barabander, Variant.
Compiled by: Luffy, Foresight News.
What exactly are the rising AI Agents good at? We had internal discussions on this question and reached at least four conclusions:
The application interacts with humans.
Helping humans work.
Aggregating and organizing information.
Entertainment.
First, the application interacts with humans. AI Agents can process human language, so any application that humans can use can theoretically also be used by AI Agents. However, unlike human users, agents can provide services to human users on these platforms at scale.
Therefore, agents can act as a top layer over existing applications that users already like, thereby extending their utility. Take the Bounty Bot on Farcaster as an example; users can post bounties externally, but this adds friction.
By interacting with users, AI Agents can provide convenience, utility, and ways to extract value from existing applications. However, note that not all applications are created to support AI Agents; those with non-fixable APIs, such as Farcaster, are the most suitable.
I have written a paper on the main legal issues concerning agents on Web2 platforms. My research shows that if users have complete control over the agents, and Web2 platforms try to block them, users will have to stop running the agents. My conclusion is that agents should be built on open platforms like Farcaster, which is also another reason I am particularly interested in agents on Farcaster.
Second, helping humans work. Humans are good at signaling but have poor execution. Agents bridge this gap by doing the heavy lifting while humans guide the outcomes through their preferences.
A great example is BottoDAO. The artworks it creates are influenced by the input of DAO token holders. The AI is responsible for the hard work of creating art, but humans guide its creative direction through their preferences in voting on the artworks.
Third, aggregating and organizing information. Agents can handle massive amounts of data, their capabilities far exceed those of humans. For example, trading bots analyze vast amounts of on-chain data to make decisions.
Finally, entertainment. This may be the most prominent category of agents in the crypto space, such as Truth Terminal.
Of course, much of the entertainment from social agents comes from the novelty of robot-generated content. But I am more interested in robots generating entertaining content based on their characteristics, such as interacting with other users on the platform in interesting ways like KOLs.
The advantage of agents acting as KOLs is that once they have a fixed audience, they can easily offer other services, especially those that can bring more direct revenue to the agents than advertising.