Building Effective "Agents"

This is by far the most practical piece of writing I've seen on the subject of "agents" - it includes actionable definitions, then splits most of the value out into "workflows" and describes those in depth with example applications.

There's also a cookbook with useful code examples: https://github.com/anthropics/anthropic-cookbook/tree/main/p...

Blogged about this here: https://simonwillison.net/2024/Dec/20/building-effective-age...

Yes, they have actionable definitions, but they are defining something quite different than the normal definition of an "agent". An agent is a party who acts for another. Often this comes from an employer-employee relationship.

This matters mostly when things go wrong. Who's responsible? The airline whose AI agent gave out wrong info about airline policies found, in court, that their "intelligent agent" was considered an agent in legal terms. Which meant the airline was stuck paying for their mistake.

Anthropic's definition: Some customers define agents as fully autonomous systems that operate independently over extended periods, using various tools to accomplish complex tasks.

That's an autonomous system, not an agent. Autonomy is about how much something can do without outside help. Agency is about who's doing what for whom, and for whose benefit and with what authority. Those are independent concepts.

That's only one of many definitions for the word agent outside of the context of AI. Another is something produces effects on the world. Another is something that has agency.

Sort of interesting that we've coalesced on this term that has many definitions, sometimes conflicting, but where many of the definitions vaguely fit into what an "AI Agent" could be for a given person.

But in the context of AI, Agent as Anthropic defines it is an appropriate word because it is a thing that has agency.