Distributed AI Assistant

What you'll build

Vertical stack context: DOSFIUniversity (research) → DOSFI Academy (this course) → MeshNativeExchange (publishing & monetizing). Students progress from Learning → Building → Publishing → Monetizing. This module provides a comprehensive exploration of the Distributed AI Assistant within the Mesh-Native ecosystem, focusing on multi-node inference pipelines, advanced routing policies, and Workflow schema orchestration. It delves into the deployment and management of complex AI workflows across distributed nodes, emphasizing subsystem responsibilities, data flow, and deterministic behavior in high-assurance environments. This course provides an architectural framework for implementing Distributed AI Assistants within the Mesh-Native ecosystem. Participants will master the orchestration of DIU (Distributed Intelligence Unit) clusters, define complex Workflow patterns, and configure Routing Policies that leverage the Vital Transport Layer. The curriculum focuses on the deterministic execution of inference pipelines across heterogeneous nodes, ensuring privacy-compliant data transit through the MNE and robust state management via the MeshInfer workflow engine.

Skills you'll practice

• Design and deploy DIU orchestration layers for multi-node inference.
• Implement granular Routing Policies to optimize latency and cost in the Transport Layer.
• Configure MeshInfer state machines for complex Workflow persistence.
• Execute secure, privacy-tier-aware data settlement via the MNE.
• Validate multi-node consistency in distributed state synchronization.

Before you start

• Proficiency in Mesh-Native core primitives and identity fabric.
• Experience with YAML-based bundle schema configuration.
• Working knowledge of the Vital Transport Layer diagnostic tools.

Lab steps3 steps

1. 1
   DIU Orchestration and Pipeline Topology
2. 2
   Routing Policies and Transport Layer Optimization
3. 3
   State Synchronization via MeshInfer