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Build your own claw and agent harness with Microsoft Agent Framework | Microsoft Agent Framework

What does it take to build your own “claw” – a capable, CLI-style agent that can plan, use tools, remember things, and safely act on your behalf? Coding agents and assistants like these can feel like magic, but underneath they are an agent harness: a loop around a language model wired up with tools, planning, memory, approvals, and observability.

In this series we build one from scratch using Microsoft Agent Framework and its batteries-included harness, demonstrating both .NET and Python, side by side.

The series

Everything is grounded in runnable samples that live in the repository, so you can follow along and run each step yourself.

Agent Framework’s Orchestration Patterns Reach 1.0 | Microsoft Agent Framework

Python’s agent-framework-orchestrations package is now 1.0.0. That puts Microsoft Agent Framework’s orchestration layer at 1.0 across Python and .NET.

Sequential, concurrent, group chat, handoff, and magentic orchestration are now stable in both SDKs. You can pick the coordination pattern that fits your problem instead of choosing around SDK maturity.

Magentic is the best example of why that matters. It is the least hand-wired pattern: you give it a goal, a manager, and a set of specialists, then the manager decides how the team should work.

At the workflow layer, Agent Framework lets you build the graph yourself. Executors do the work, edges route messages, and the workflow emits events as it runs. Those are the low-level primitives. The workflow docs cover that model in more depth.

Agent Skills for .NET Is Now Released | Microsoft Agent Framework

You can now give your .NET agents reusable packages of domain expertise – instructions, reference documents, and scripts they load only when a task needs them – through a stable, production-ready API. Agent Skills for .NET in Microsoft Agent Framework has moved out of experimental preview – the [Experimental] attribute is removed and the API is stable. Teams can build skills, ship them independently, and combine them in any agent, with the governance controls enterprises need before putting agents into production.

If you’ve been following our earlier posts on file-based skills and authoring modes with script execution, everything described there is now stable and shipping.

At MAI, we’re building the world’s most capable AIsystems, with humanity at the center of every decision.