Agent frameworks
microsoft/semantic-kernel
Semantic Kernel is Microsoft’s SDK for integrating models, plugins and agent patterns into conventional applications. It is less a standalone agent product than a set of software components that let established code call AI capabilities through defined interfaces.
THE PRACTICAL EXPLANATION
Semantic Kernel is Microsoft’s SDK for integrating models, plugins and agent patterns into conventional applications. It is less a standalone agent product than a set of software components that let established code call AI capabilities through defined interfaces.
WHERE TO USE IT
Use it inside Microsoft-stack applications, particularly when C#, Azure services and existing enterprise architecture matter. It can support assistants, planners, plugins and multi-agent patterns without abandoning normal application engineering.
WHO MAY USE IT
.NET, Python or Java teams that want AI functionality to live inside an engineered service rather than a separate no-code platform.
HOW TO USE IT
Treat plugins as application APIs with schemas, permissions and tests. Begin with direct function selection before adding planning or multiple agents. Keep model configuration externalised and test the same workflow against expected refusals and tool failures.
GETTING THE BEST RESULTS
WHY IT MAY BE USEFUL
SDK for adding models, plugins, orchestration and agent patterns to applications.
Best considered for: Microsoft-stack teams working in C#, Python or Java.
READ BEFORE YOU ADOPT IT
Its breadth can add complexity if a smaller SDK would solve the job.
Confirm the current licence, maintenance status, dependency risk, data path, model access, tool permissions and human approval points at the source. A public repository is inspectable raw material—not proof that a system is secure, supported or suitable for your production environment.