Users praised the LangChain article on stacking loops and primitives for autonomous AI agents because it offered clear practical guidance on building effective frameworks.
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@BraceSproul Interesting. I've been struggling with this a bit for Sokosumi too - like do we need a chat if we focus on specialized agents? It's more overhead so its good to hear an opinion like yours
http://x.com/i/article/2066900327077486592
another banger from Sydney! i think this whole hierarchy of loops is still super early but some primitives we know work
ex: verification as a primitive is so ridiculously important for non-slop semi-long-horizon work, it’s worth spending days to weeks making sure the distribution of outcomes you want from your agent are verifiable in practice by your system
http://x.com/i/article/2066900327077486592
Loops are popular right now because they're the mechanism by which you connect an agent to your ecosystem and help it improve over time.
This guide covers how you can stack loops to build effective agents with @LangChain!
http://x.com/i/article/2066900327077486592
loops can help you build more effective, more autonomous agents
this post dives into a few loops: 1. the agent loop 2. the verification loop 3. the event driven loop 4. the hill climbing loop
and how you can compose them with langchain primitives!
http://x.com/i/article/2066900327077486592
@sydneyrunkle For hill climbing loop on real world outcome. Do check out https://github.com/Nimrobo/superdense
We are focused on just this problem statement
@sydneyrunkle https://github.com/cobusgreyling/loop-engineering
@sydneyrunkle @LangChain Great article Sydney, brings to mind the new update from Synth helping CPG brands build event driven loops to run their business .
@LangChain_OSS @LangChain interesting, what's the best way to balance loop depth without overfitting the agent
loops are where it gets real, agreed. the part that bites teams later is that a loop connecting an agent to your ecosystem is only as safe as what you let it touch inside that loop. the design question we keep coming back to with clients isn't "how many loops" but "what can the agent actually do on each pass, and who's watching". that's the difference between improving over time and breaking quietly over time
