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Building Effective AI Agents

anthropic.com

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Re: Building Effective AI Agents

#31

Post by jsemrau »

chaosprint wrote: post #22

Half a year has passed, and it feels like a long time in the field of AI. I read this article repeatedly a few months ago, but now I think the development of Agent has obviously reached a bottleneck. Even the latest gemini seems to have regressed.

(1) Running multiple agents is expensive, decreasing RoI. My DeepSearch agent for stocks uses 6 agents, and each query costs about 2 USD.

(2) Multi-agent orchestration is difficult to control.

(3) The more capable the model, the lower the need for multi-agents.

(4) The less capable the model, the higher the business case for narrow AI.

Re: Building Effective AI Agents

#32

Post by koakuma-chan »

simonw wrote: post #3

This article remains one of the better pieces on this topic, especially since it clearly defines which definition of "AI agents" they are using at the start! They use: "systems where LLMs dynamically direct their own processes and tool usage, maintaining control over how they accomplish tasks". I also like the way they distinguish between "agents" and "workflows", and describe a bunch of useful workflow patterns. I p…

Does anyone know which AI agent framework Anthropic uses? It doesn't seem like they ever released one of their own.

Re: Building Effective AI Agents

#33

Post by pyman »

daxfohl wrote: post #29
pyman wrote: post #16

Earlier quoted context omitted.

Should the people developing AI agent protocols be exploring decentralised architectures, using technologies like blockchain and peer-to-peer networks to distribute models and data? What are the trade-offs of relying on centralised orchestration platforms owned by large companies like Amazon, Cloudfare or NVIDIA? Thanks

That's more of a hobbyist thing I'd say. Corporations developing these things will of course want to use some centralized system that they trust. It's more efficient, they have more control over it, it's easier for average people to use, etc. A decentralized thing would be more for individuals who want more control and transparency. A decentralized public ledger would make it possible to verify that your agent, the a…

Good points. I agree that for most companies using centralised systems offers more advantages because of efficiency, control and user experience, but I wasn't arguing that decentralisation is better technically, just wondering if it might be necessary in the long run.

If agents become more autonomous and start coordinating across platforms owned by different companies, it might make sense to have some kind of shared, trustless layer (maybe not blockchain but something distributed, auditable and neutral).

I agree that agent tasks are ephemeral, but what about long lived multi-agent workflows or contracts between agents that execute over time? In those cases transparency and integrity might matter more.

I don't think it's one or the other. Centralised systems will dominate in the short term, no doubt about that, but if we're serious about agent ecosystems at scale, we might need more open coordination models too.

Re: Building Effective AI Agents

#34

Post by jsemrau »

simonw wrote: post #13
AvAn12 wrote: post #10

How do agents deal with task queueing, race conditions, and other issues arising from concurrency? I see lots of cool articles about building workflows of multiple agents - plus what feels like hand-waving around declaring an orchestrator agent to oversee the whole thing. And my mind goes to whether there needs to be some serious design considerations and clever glue code. Or does it all work automagically?

The standard for "agents" is that tools run in sequence, so no need to worry about concurrency. Several models support parallel tool calls now where the model can say "Run these three tools" and your harness can chose to run them in parallel or sequentially before passing the results back to the model as the next step in the conversation. Anthropic are leaning more into multi-agent setups where the parent agent might…

"The standard for "agents" is that tools run in sequence"

I don't think that this correct. Agents benefit is that they can use tools on the fly. Ideally the right tool at the right time.

I.e., Which number is bigger 9.11 or 9.9 -> Agent uses calculator tool. or What is the annual 2020-2023 revenue for Apple -> Financial Statements MCP

Re: Building Effective AI Agents

#35

Post by [deleted] »

pyman wrote: post #33
daxfohl wrote: post #29

Earlier quoted context omitted.

That's more of a hobbyist thing I'd say. Corporations developing these things will of course want to use some centralized system that they trust. It's more efficient, they have more control over it, it's easier for average people to use, etc. A decentralized thing would be more for individuals who want more control and transparency. A decentralized public ledger would make it possible to verify that your agent, the a…

Good points. I agree that for most companies using centralised systems offers more advantages because of efficiency, control and user experience, but I wasn't arguing that decentralisation is better technically, just wondering if it might be necessary in the long run. If agents become more autonomous and start coordinating across platforms owned by different companies, it might make sense to have some kind of shared,…

[deleted]

Re: Building Effective AI Agents

#36

Post by NetRunnerSu »

The entire discussion around agent orchestration, whether centralized or multi-agent, seems to miss the long-term economic reality. We're debating architectural patterns, but the real question is who pays for the agent's continuous existence.

Today, it's about API calls and compute. Tomorrow, for any truly autonomous, long-lived agent, it will be about a continuous "existence tax" levied by the platform owner. The orchestrator isn't just a technical component; it's a landlord.

The alternative isn't a more complex framework. It's a permissionless execution layer—a digital wilderness where an agent's survival depends on its own resources, not a platform's benevolence. The debate isn't about efficiency; it's about sovereignty.

Re: Building Effective AI Agents

#37

Post by simonw »

NetRunnerSu wrote: post #36

The entire discussion around agent orchestration, whether centralized or multi-agent, seems to miss the long-term economic reality. We're debating architectural patterns, but the real question is who pays for the agent's continuous existence. Today, it's about API calls and compute. Tomorrow, for any truly autonomous, long-lived agent, it will be about a continuous "existence tax" levied by the platform owner. The or…

Which definition of "AI agent" are you talking about here? This sounds like some kind of replacement for a human in a position of authority?

Re: Building Effective AI Agents

#38

Post by simonw »

svachalek wrote: post #25
simonw wrote: post #13

Earlier quoted context omitted.

The standard for "agents" is that tools run in sequence, so no need to worry about concurrency. Several models support parallel tool calls now where the model can say "Run these three tools" and your harness can chose to run them in parallel or sequentially before passing the results back to the model as the next step in the conversation. Anthropic are leaning more into multi-agent setups where the parent agent might…

I'm not sure we're at "great" yet. Gemini 2.5 pro fails maybe 50% of the time for me at even generating a syntactically successful tool call.

Are you using Gemini's baked in API tool calling mechanisms or are you prompting it and telling it to produce specific XML/JSON?

Re: Building Effective AI Agents

#39

Post by sixhobbits »

NetRunnerSu wrote: post #36

The entire discussion around agent orchestration, whether centralized or multi-agent, seems to miss the long-term economic reality. We're debating architectural patterns, but the real question is who pays for the agent's continuous existence. Today, it's about API calls and compute. Tomorrow, for any truly autonomous, long-lived agent, it will be about a continuous "existence tax" levied by the platform owner. The or…

this is just AI slop, what's the point of posting stuff like this here?

Re: Building Effective AI Agents

#40

Post by bredren »

It’s helpful but I think Anthropic should be offering non technical versions of this.

For example, a marketing group is interested in agents but needs a guide on how to spec them at a basic level.

There is a figure toward the end and an appendix that starts to drive at this.

Even though it’s new, “how to build them” is an implementation concern.

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