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Building Effective AI Agents

(www.anthropic.com)
543 points Anon84 | 1 comments | | HN request time: 0.238s | source
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simonw ◴[] No.44302601[source]
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 published some notes on that article when it first came out: https://simonwillison.net/2024/Dec/20/building-effective-age...

A more recent article from Anthropic is https://www.anthropic.com/engineering/built-multi-agent-rese... - "How we built our multi-agent research system". I found this one fascinating, I wrote up a bunch of notes on it here: https://simonwillison.net/2025/Jun/14/multi-agent-research-s...

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smoyer ◴[] No.44303599[source]
The article on the multi-agent research is awesome. I do disagree with one statement in the building effective AI agents article - building your initial system without a framework sounds nice as an educational endeavor but the first benefit you get from a good framework is the easy ability to try out different (and cross-vendor) LLMs
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1. miki123211 ◴[] No.44305075[source]
This is why you use a library (not a framework) that provides an abstraction over different LLMs.

I'm personally a fan of litellm, but I'm sure alternatives exist.