Multi-agent systems decompose complex workflows into cooperating specialized components. These articles cover orchestration patterns, state management, deployment strategies, and the architectural trade-offs involved in coordinating multiple autonomous agents within a single platform. Topics include supervisor-worker topologies, parallel dispatch with errgroup, and production deployment on Cloud Run.
8 posts tagged with multi-agent. ← All posts
Wrapping Go agents in A2A, MCP, and AG-UI transports, then a full client/server app that ties the whole series together.
Wrap Go agents in A2A, MCP, and AG-UI transports, then run the end-to-end client/server capstone where a host agent uses remote specialists as tools.
The prebuilt orchestration builders in agent-framework-go — Sequential, Concurrent, Group Chat — plus wrapping a whole workflow as one agent.
The Sequential, Concurrent, and Group Chat orchestration builders in agent-framework-go, plus wrapping a whole workflow as one nestable agent.
Turning agents into a service you can run and expose, then a full DocQA app that ties the whole series together.
Host MAF agents with DevUI, A2A, MCP, and AG-UI, then build DocQA — a grounded, cited multi-agent app that ties the whole Python series together.
Five prebuilt multi-agent shapes — Sequential, Concurrent, Group Chat, Handoff, Magentic — and when each beats hand-wiring a graph.
Sequential, Concurrent, Group Chat, Handoff, Magentic — the five prebuilt MAF orchestrations in Python and when each beats hand-wiring a graph.
Microsoft published a 12-chapter reference architecture for multi-agent systems and a separate framework — the Microsoft Agent Framework — to build them. Here is what the 102 Python files actually contain and how they map to the chapters.
This lesson teaches the simplest form of multi-agent delegation: wrapping one agent as a tool another agent can call.
Wrap a specialist WeatherAgent with agenttool.New into a tool.Tool and hand it to a French TravelAgent — one model orchestrating another with no workflow engine.
Google's GKE AI infrastructure docs list ~40 integrations. Here's a field map of which ones actually matter when the workload is a HIPAA-aware multi-agent medical AI, and where the gaps sit.
Five interfaces hold the whole platform together. The 30-line orchestrator closure that makes the rest of the architecture testable, auditable, and safe to evolve.
All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.