Deep DiveAI Engineering
MAF v1 — Concurrent Orchestration (Python + .NET)
Fan one input out to an expert panel, aggregate the responses, and keep wall-clock time bounded by the slowest branch cleanly.
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Journal
Solutions Architect specializing in Azure, AI, and enterprise cloud-native development. Writing about architecture, AI agents, and building things that scale.
Deep DiveAI Engineering
MAF v1 — Sequential Orchestration (Python + .NET)
Use SequentialBuilder or BuildSequential to pass one conversation through Writer, Reviewer, and Finalizer agents without hand-built adapters.
Deep DiveAI & LLM
MCP: What It Is and Why It Changes How You Build AI Tools
MCP solves the N×M integration problem between AI models and tools. What it is, how it works, and why it matters before your next AI feature.
Deep DiveAI Engineering
MAF v1 — MCP Tools (Python + .NET)
Stand up a Python MCP server and consume it from Python and .NET MAF agents, including discovery and AITool wiring from one server.
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Deep DiveAI Engineering
MAF v1 — Workflow Events and Builder (Python + .NET)
Two kinds of workflow events — lifecycle and custom. Subscribe to the stream in Python and .NET, filter by type, and wire a live progress indicator.
Deep DiveAI Engineering
MAF v1 — Workflow Executors and Edges (Python + .NET)
Model deterministic workflows with executors as nodes, edges as routes, and a Pregel-style scheduler in Python and .NET.
Deep DiveAI Engineering
MAF v1 — Context Providers (Python + .NET)
Add per-request context with focused providers, compose them before each LLM call, and plug in TextSearchProvider for simple RAG.
Deep DiveAI Engineering
MAF v1 — Middleware and the Agent Pipeline (Python + .NET)
Use middleware to wrap agent runs, intercept tool calls, and redact PII before the LLM sees it in both Python and .NET safely.
Deep DiveAI Engineering
MAF v1 — Observability with OpenTelemetry (Python + .NET)
Wire OpenTelemetry spans for agent runs with GenAI attributes, using console export for dev and OTLP for production tracing.
Deep DiveAI Engineering
Building a Multi-Agent E-Commerce Platform: The Complete Guide
A 12-part hands-on series on building production-ready multi-agent AI systems with Microsoft Agent Framework, A2A protocol, and a real e-commerce platform you can run locally.
Deep DiveAI Engineering
AI Agents: Concepts and Your First Implementation
What AI agents actually are, how they differ from chatbots, and a hands-on walkthrough to build your first working agent with Microsoft Agent Framework in under 30 minutes.
Deep DiveAI Engineering
Prompt Engineering for AI Agents -- Grounding, Roles, and YAML Configuration
How to write agent prompts that prevent hallucination, adapt to user roles, and stay maintainable -- with YAML-based configuration you can version-control.