Hi everyone,
While experimenting with multimodal AI workflows and building autonomous agent loops that process complex text and data payloads, managing reasoning steps efficiently while minimizing API roundtrip latency is a fascinating challenge.
I wanted to open a discussion with the community on current practical approaches:
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What architectural patterns do you rely on to structure multi-step reasoning tasks without hitting performance bottlenecks?
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How do you approach context pruning and state management as agents handle longer conversational turns?
Would love to hear your insights, research directions, and hands-on experiences with this!