nuwandavek (u/nuwandavek)

nuwandavek commented on What makes Claude Code so damn good minusx.ai/blog/decoding-c... · Posted by u/samuelstros

nojs · 12 days ago

I’ve noticed that custom subagents in CC often perform noticeably worse than the main agent, even when told to use Opus and despite extreme prompt tuning. This seems to concur with the “keep it flat” logic here. But why should this be the case?

nuwandavek · 12 days ago

(blogpost author here) I've noticed this too. My top guess for any such thing would be that this type of sub-agent routing is outside the training distribution. Its possible that this gets better overnight with a model update. The second reason is that sub-agents make it very hard to debug - was the issue with the router prompt or the agent prompt? Flat tools and loop make this a non-issue without loss of any real capability.

nuwandavek commented on What makes Claude Code so damn good minusx.ai/blog/decoding-c... · Posted by u/samuelstros

samuelstros · 13 days ago

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 :)

nuwandavek · 12 days ago

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!

nuwandavek commented on What makes Claude Code so damn good minusx.ai/blog/decoding-c... · Posted by u/samuelstros

kristianp · 12 days ago

Just fyi, at the end of the article there is a link to minusx.com which has an expired certificate.

This server could not prove that it is minusx.com; its security certificate expired 553 days ago

nuwandavek · 12 days ago

Oops, fixed it, thanks!

nuwandavek commented on What makes Claude Code so damn good minusx.ai/blog/decoding-c... · Posted by u/samuelstros

brokegrammer · 12 days ago

I don't get it. The title says "What makes Claude Code so damn good", which implies that they will show how Claude Code is better than other tools, or just better in general. But they go about repeating the Claude Code documentation using different wording.

Am I missing something here? Or is this just Anthropic shilling?

nuwandavek · 12 days ago

(blogpost author here) Haha, that's totally fair. I've read a whole bunch of posts comparing CC to other tools, or with a dump of the the architecture. This post was mainly for people who've used CC extensively, know for a fact that it is better and wonder how to ship such an experience in their own apps.

nuwandavek commented on What makes Claude Code so damn good minusx.ai/blog/decoding-c... · Posted by u/samuelstros

radleta · 13 days ago

I’d be curious to know what MCPs you’ve found useful with CC. Thoughts?

nuwandavek · 13 days ago

(blogpost author here) I actually found none of them useful. I think MCP is an incomplete idea. Tools and the system prompt cannot be so cleanly separated (at least not yet). Just slapping on tools hurts performance more than it helps.

I've now gone back to just using vanilla CC with a really really rich claude.md file.

nuwandavek commented on What makes Claude Code so damn good minusx.ai/blog/decoding-c... · Posted by u/samuelstros

nuwandavek · 13 days ago

(blogpost author here) You're right! I did make the distinction in an earlier draft, but decided to use "RAG" interchangeably with vector search, as it is popularly known today in code-gen systems. I'd probably go back to the previous version too.

But I do think there is a qualitative different between getting candidates and adding them to context before generating (retrieval augmented generation) vs the LLM searching for context till it is satisfied.

nuwandavek commented on What makes Claude Code so damn good minusx.ai/blog/decoding-c... · Posted by u/samuelstros

ahmedhawas123 · 13 days ago

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)

nuwandavek · 13 days ago

(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.