#MAF

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· Engineering

Five MAF orchestration shapes — adding Group Chat and Magentic

The first ten posts treated MAF as having four orchestration patterns. The official docs say five. Here are the two I missed — Group Chat and Magentic — with the API surface, when to pick each, and the test path that catches them at build time.

· Engineering

Refactor: from rolled-our-own to MAF-native

I built memory, communication, security, governance, and evals from scratch first. Then I deleted most of it and used the official MAF packages. Here

· Engineering

Ollama as the default LLM for enterprise-shaped systems

PROVIDER=ollama, granite4.1:3b, zero API keys, no Azure account. How to make a multi-agent project that demonstrates enterprise patterns run end-to-end on a laptop in 90 seconds.

· Engineering

Governance with the Agent Governance Toolkit

OWASP Agentic Top 10 coverage with YAML policy files, two API surfaces (one-line wrapper and programmatic evaluator), and a metric bridge that shows policy denials in Grafana.

· Engineering

A2A: when the workflow IS the broker

The reference architecture distinguishes request-based and message-driven agent communication. For in-process orchestration, MAF

· Engineering

Memory done right with MAF

AgentSession is short-term memory. MemoryContextProvider + MemoryFileStore is long-term memory. Mem0 is long-term memory when you want it hosted. Here

· Engineering

Four orchestration patterns in MAF — and when to pick each

Sequential, Concurrent, Handoff, and Custom WorkflowBuilder. Four shapes the Microsoft Agent Framework ships out of the box. Each one is the right answer to a different question.

· Engineering

The 12-chapter reference architecture, in 102 Python files

Microsoft published a 12-chapter reference architecture for multi-agent systems and a separate framework (MAF) to build them. I implemented one on top of the other and learned what each chapter actually demands in code.