Microsoft is pushing the boundaries of agentic AI development with its latest advancements in Semantic Kernel and AutoGen. The tech giant is positioning Semantic Kernel as its preferred tool for building large-scale agentic AI applications, with the Agent Framework and AutoGen integration set to revolutionize the way enterprises approach AI development.

At the heart of Microsoft's AI application development strategy is Semantic Kernel, an open-source set of tools for managing and orchestrating AI prompts. Since its launch, Semantic Kernel has grown into a framework for building and managing agentic AI, with the Agent Framework being a key feature. The Agent Framework is designed to help build applications around agent-like patterns, offering a way to add autonomy to applications and deliver goal-oriented applications.

The Agent Framework is available as an extension to the base Semantic Kernel and is delivered as a set of .NET libraries. It helps manage human/agent interactions and provides access to OpenAI's Assistant API. The framework is intended to be controlled via conversation, but it's easy enough to build and run agents that respond to system events rather than direct human actions. This allows developers to focus on using agents to manage tasks.

Semantic Kernel's agent features are designed to extend the concepts and tools used to build RAG-powered AI workflows. The platform manages context and state, as well as handling calls to AI endpoints via Azure AI Foundry and similar services. Agents can use existing or new plug-ins, as well as call functions, making it easy to work with external applications and dynamically generate workflows around both humans and software.

Microsoft is also integrating AutoGen into Semantic Kernel, which builds on its Process Framework. AutoGen is designed to manage long-running business processes and works with distributed application frameworks such as Dapr and Orleans. The integration will help deliver better support for multi-agent operations in Semantic Kernel, with AutoGen supporting both .NET and Python.

AutoGen simplifies the process of building agents, with a no-code GUI and support for a variety of different LLMs such as OpenAI, Azure OpenAI, Ollama, and Google Gemini. The platform provides a declarative agent development environment, with a JSON description of the various elements that go into making an agent. This makes it easy to build and customize agents without requiring extensive coding knowledge.

AutoGen Studio is a local web application that provides a place to construct teams of agents and extensions, with the aim of constructing a multi-agent application without needing to write any additional code. The platform builds on top of AutoGen's AgentChat service and allows developers to drag components onto the canvas, add termination conditions, and configure agents with models and extensions.

The integration of Semantic Kernel and AutoGen marks a significant shift in the way enterprises approach AI development. By providing a no-code agent development environment, Microsoft is democratizing access to AI development and enabling businesses to automate complex workflows and processes. As the technology continues to evolve, it will be interesting to watch how it takes advantage of the skills and knowledge that exist across organizations, beyond IT and development teams.

With Semantic Kernel and AutoGen, Microsoft is poised to revolutionize the enterprise AI landscape. As the company continues to advance its AI development tools, it's clear that the future of AI development is bright, and the possibilities are endless.