Definition
Semantic Kernel is an open-source software development kit from Microsoft for building, orchestrating, and deploying AI agents and multi-agent systems. It is model-agnostic, meaning it can route requests to different language model providers behind a common interface, and it offers official support across C#, Python, and Java. The SDK sits in the middle of an application, tying together prompts, functions, memory, and agents into a structured, testable whole.
Plugins and functions
A defining concept is the plugin: a collection of functions the kernel can call. These may be native code functions or AI-driven semantic functions defined largely by a prompt. By describing capabilities this way, Semantic Kernel lets a model plan and invoke the right function for a task, while developers keep the deterministic and the probabilistic parts of their system clearly separated. Built-in memory and vector-store integration support retrieval and longer-running context.
Ecosystem direction
Microsoft has signalled that Semantic Kernel and AutoGen are converging into a unified Microsoft Agent Framework for new enterprise projects. Builders evaluating Semantic Kernel should factor in that roadmap. D-Central notes this neutrally, without recommending it over other options; the appropriate choice depends on the language, platform, and governance requirements of the project.
For adjacent tooling, see D-Central's entries on AutoGen and the ReAct pattern that informs how such agents reason and act.
In Simple Terms
Semantic Kernel is an open-source software development kit from Microsoft for building, orchestrating, and deploying AI agents and multi-agent systems. It is model-agnostic, meaning it…