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469 points samuelstros | 1 comments | | HN request time: 0.214s | source
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ahmedhawas123 ◴[] No.44999186[source]
Thanks for sharing this. At a time where this is a rush towards multi-agent systems, this is helpful to see how an LLM-first organization is going after it. Lots of the design aspects here are things I experiment with day to day so it's good to see others use it as well

A few takeaways for me from this (1) Long prompts are good - and don't forget basic things like explaining in the prompt what the tool is, how to help the user, etc (2) Tool calling is basic af; you need more context (when to use, when not to use, etc) (3) Using messages as the state of the memory for the system is OK; i've thought about fancy ways (e.g., persisting dataframes, parsing variables between steps, etc, but seems like as context windows grow, messages should be ok)

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nuwandavek ◴[] No.44999771[source]
(author of the blogpost here) Yeah, you can extract a LOT of performance from the basics and don't have to do any complicated setup for ~99% of use cases. Keep the loop simple, have clear tools (it is ok if tools overlap in function). Clarity and simplicity >>> everything else.
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samuelstros ◴[] No.45000170[source]
does a framework like vercel's ai sdk help, or is handling the loop + tool calling so straightforward that a framework is overcomplicating things?

for context, i want to build a claude code like agent in a WYSIWYG markdown app. that's how i stumbled on your blog post :)

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1. nuwandavek ◴[] No.45001760[source]
There may be other reasons to use ai sdk, but I'd highly recommend starting with a simple loop + port most relevant tools from Claude Code before using any framework.

Nice, do share a link, would love to check out your agent!