Multi-turn evals from first principles
Single-turn evals check one decision. Multi-turn evals check the whole trajectory. Here
#Python
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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
Agent registry as a project-local convention
The Microsoft Agent Framework deliberately does not ship an agent registry. Here
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.
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.
Optimus — a Gemini-powered BigQuery anti-pattern detector that paid for itself in a week
We built a small Go + Python service that parses a project's INFORMATION_SCHEMA, asks Gemini to classify each top-spending query against a catalog of anti-patterns, and recommends a rewrite. It is not a magic box; it is a pipeline that cuts the human review time per query from 20 minutes to 90 seconds.