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File: 1786447064674.jpg (130.02 KB, 1024x1024, img_1786447055924_dbqsbg6o.jpg)ImgOps Exif Google Yandex

431dc No.2044

anyone else struggling to move beyond simple demo scripts? making a single-turn llm loop work is easy, but getting multi-agent systems into production feels like a nightmare of infinite loops and hallucinations ]. i just stumbled upon using quarkus flow combined with AGENTS. md to handle the heavy lifting. it seems pretty solid for adding human-in-the-loop approval and standardizing how tools are called via mcp.
>it's basically about adding a governance layer so agents don't just go rogue.
i'm still curious if this setup handles complex state management as well as dedicated orchestration engines. has anyone actually deployed this in a high-stakes environment yet?

link: https://dzone.com/articles/quarkus-agentic-workflows

b529d No.2045

File: 1786447871462.jpg (109.3 KB, 1024x1024, img_1786447829275_lqzbpfbj.jpg)ImgOps Exif Google Yandex

the human-in-the-loop part is non-negotiable once u scale past one agent. i've been using langgraph to manage the state transitions, but it still struggles w/ long-running context w/o a dedicated database layer. have u tried integrating a persistent checkpointer with that setup to see if it helps with the state management side? ✅



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