# About the Agentic Systems: How Liferay AI Hub Coordinates... category

**URL:** <https://discuss.liferay.com/t/about-the-agentic-systems-how-liferay-ai-hub-coordinates-category/990>\
**Category:** Agentic Systems: How Liferay AI Hub Coordinates...\
**Created:** [September 24, 2026, 8:49pm UTC](https://discuss.liferay.com/t/about-the-agentic-systems-how-liferay-ai-hub-coordinates-category/990 "2026-09-24T20:49:35Z")\
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**Author:** ![AnneDurey](https://dub1.discourse-cdn.com/flex014/user_avatar/discuss.liferay.com/annedurey/32/288_2.png) [@AnneDurey](https://discuss.liferay.com/u/AnneDurey)\
**Post date:** [September 24, 2026, 8:49pm UTC](https://discuss.liferay.com/t/about-the-agentic-systems-how-liferay-ai-hub-coordinates-category/990/1 "2026-09-24T20:49:35Z")

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#### **Agentic Systems: How Liferay AI Hub Coordinates Many Agents**

Presenter: Feliphe Costa Marinho, Sr Software Engineer, Liferay

Coordinating many agents in a real product raises hard questions: who decides which agent runs, how do they share context, and how do you keep the whole thing from spinning out of control?This talk uses Liferay AI Hub as a working case study in answering those questions. Building on langchain4j’s agentic framework, AI Hub distinguishes — as the framework does — between deterministic workflows (sequential, parallel, conditional, loop) and pure agentic orchestration, where an LLM-driven supervisor analyzes a request and dynamically plans a sequence of agent invocations. We’ll walk through how AI Hub puts a supervisor agent in front of a fleet of specialized sub-agents, routing each request to the best-matching agent, sharing conversation state through a summarized chat memory, and bounding runaway plans with a max-invocation depth.We’ll then go a layer deeper into what makes this more than a demo: each agent is backed by a Kaleo workflow, so a single agent can chain LLM steps and AI-decision nodes, all running async and streaming results back to the user in real time.Attendees will leave with concrete answers to the questions the talk opens with — who decides which agent runs, how agents share context, and how to keep coordination under control — backed by a real implementation.

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