Semantic Kernel
Microsoft's open-source SDK for integrating LLMs with programming languages. It provides a framework for orchestrating AI capabilities with conventional code.
Why It Matters
Semantic Kernel makes it easy to add AI capabilities to existing enterprise applications, bridging the gap between LLM experiments and production software.
Example
A .NET application using Semantic Kernel to connect to Azure OpenAI, manage prompt templates, chain LLM calls with database queries, and maintain conversation memory.
Think of it like...
Like a universal adapter that lets your existing software talk to AI models — plugging AI capabilities into your current tech stack without rebuilding everything.
Related Terms
LangChain
A popular open-source framework for building applications powered by language models. It provides tools for prompt management, chains, agents, memory, and integration with external tools and data sources.
Orchestration
The coordination and management of multiple AI components, tools, and services to accomplish complex workflows. Orchestration handles routing, sequencing, error handling, and resource allocation.
API
Application Programming Interface — a set of rules and protocols that allow different software applications to communicate with each other. In AI, APIs let developers integrate AI capabilities into their applications.
Tool Use
The ability of an AI model to interact with external tools, APIs, and systems to accomplish tasks beyond text generation. Tools extend the model's capabilities to include search, calculation, code execution, and more.