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AgenticX
by DemonDamon
Framework for composing and deploying agentic multi-agent workflows
Python
Updated Jul 13, 2026
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Overview
Implements a flexible Python framework for building and deploying agentic (multi-agent) AI applications. Provides an extensible architecture for composing agentic RAG, Dynamic Task Routing Pattern, and delegated task flows so teams can model specialist agents and Supervisor Pattern orchestration patterns. Distinctive features include modular agent stages, workflow primitives for delegation, and hooks for integrating evaluation and logging.
Key Benefits
As agents delegate work to other agents, visibility into who did what and whether results are reliable becomes vital for trust. AgenticX makes agent delegation and workflow explicit, enabling reproducible interaction traces and easier insertion of evaluation or reputation checks. This matters because you cannot evaluate or trust multi-agent systems if coordination and handoffs are opaque. Evaluation-Driven Development (EDDOps)
Ideal For
Teams prototyping multi-agent applications and workflows that need explicit delegation, tracing, and integration points for evaluation. Agent Registry Pattern
Real-World Examples
- Modeling delegated workflows where specialist agents handle subtasks
- Instrumenting agent interactions for post-hoc evaluation or reputation scoring
- Integrating RAG pipelines into multi-agent task flows with traceable handoffs
Works With
langchainopenai
Topics
agentic-aiagentic-workflowmulti-agent-system
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Keywords
multi-agent trustagent-to-agent evaluationagentic-workflowagent-delegation