Microsoft's agent-building story now has a single center of gravity. Agent Framework 1.0 shipped on April 3, 2026, and with it Semantic Kernel moved into maintenance mode, following AutoGen, which entered that state in October 2025 1. Microsoft calls the release production-ready, with stable APIs and long-term support for both .NET and Python 2. For security teams, a stable 1.0 label marks the moment to start a structured review. It is not a reason to stop asking questions.
What actually shipped
Microsoft describes Agent Framework as an open-source SDK and runtime for building AI agents and multi-agent workflows. It is meant for developers who want to go beyond simple assistants and build orchestrated systems that call tools, work across multiple models and run longer workflows 2. The project was introduced in October 2025. It combines foundations from Semantic Kernel with orchestration concepts from AutoGen 2.
The framework also includes native support for the Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication 1. Those two features matter most from a risk perspective. MCP makes it easier to plug agents into external tools and data sources. A2A lets agents exchange work with other agents. Both expand what an agent can reach and who can influence it.
Microsoft also highlighted several features that are still in preview: DevUI, hosted agent integration, and deeper tooling and observability support 2. These sit outside the stable 1.0 core 2. The practical consequence is that teams cannot assume every capability carries the same stability guarantees.
A messy family tree
The 1.0 release follows a lineage that can confuse anyone auditing an existing deployment. After Microsoft put AutoGen into maintenance mode, the project split three ways [1]:
- The original AutoGen continues as a community-managed codebase that receives fixes only.
- AutoGen's original creators forked it into AG2, which is under active development.
- Microsoft put its own investment into the new unified framework.
The legacy AutoGen line now gets bug and security fixes but no new features. Its last major Python release was v0.7.5 1. The review advice is direct: treat legacy AutoGen as something you patch, not something you build new capability on, and plan a migration 1.
The two accounts frame this transition differently. Visual Studio Magazine presents Agent Framework as an evolution that builds on Semantic Kernel and AutoGen rather than discarding their ideas 2. The drel.ai review puts the emphasis on replacement: the predecessors are frozen, and the new framework is where development continues 1. Both are accurate. For risk owners, though, the replacement framing is the more useful one. A framework that only receives fixes will fall further behind as agent attack techniques change.
Why the model should be treated as untrusted
The core security point follows from what the framework enables. Once an agent can call tools through MCP and hand tasks to other agents over A2A, the model's output stops being just text shown to a user. It becomes instructions that trigger actions. A model can be steered by poisoned documents, malicious tool responses or a compromised peer agent. Its decisions should therefore get the same skepticism as input from any external, unauthenticated caller.
In practice, that suggests several review questions:
- Tool scope. What can each tool actually do, and with whose credentials?
- Approval. Do high-impact actions need confirmation outside the model's control?
- Agent trust. Are A2A peers authenticated and trusted only as far as their role requires?
- Untrusted content. Do MCP servers that return external content get treated as untrusted data sources?
The framework's support for multiple models and long-running workflows 2 increases the stakes. Longer workflows give an injected instruction more steps in which to cause harm. Multi-model setups add more providers whose behavior has to be understood.
Stable core, moving edges
The split between a stable core and preview features 2 deserves attention in any production rollout. Observability tooling is one of the preview areas 2, and observability is exactly what a security team needs to reconstruct what an agent did and why. Organizations relying on preview components should expect change and should test before treating them as audit-grade logging.
The bottom line
Agent Framework 1.0 resolves an ambiguity that had hung over Microsoft's agent tooling since late 2025. There is now one supported path forward 12. That clarity helps. Teams still on AutoGen or Semantic Kernel have a defined migration target, and teams starting fresh have stable APIs to build on.
The native MCP and A2A support 1 still means a 1.0 deployment can reach more systems than its predecessors typically did. The sensible approach is to adopt the framework while building on the assumption that the model at its center can be manipulated. Permissions, approvals and logging should be designed around that assumption, not around trust in the model's judgment.
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