Semantic Kernel
Semantic Kernel is an AI orchestration framework. It helps developers connect prompts, tools, memory, and workflows into AI applications.
Simple idea: Semantic Kernel helps organize AI app logic.
Why It Matters
AI products are not only prompts. They usually need:
- Prompts.
- Tool calls.
- Memory.
- Connectors.
- Workflows.
- Function calling.
- Logging.
- Guardrails.
Semantic Kernel gives structure for building those systems.
Core Concepts
| Concept | Meaning |
|---|---|
| Kernel | Main orchestration object |
| Plugin | Group of functions the AI can use |
| Function | A tool or prompt-based skill |
| Planner | Helps decide steps for a goal |
| Memory | Stores and retrieves context |
| Connector | Connects to models or services |
When To Use
Use a framework like Semantic Kernel when:
- The app has multiple tools.
- Workflows need repeatable steps.
- You need structured prompts.
- You are building enterprise AI systems.
- You want clearer separation between AI logic and business logic.
When Not To Use
Avoid adding a framework too early if:
- The feature is a simple one-shot prompt.
- The workflow is still experimental.
- A small service with direct model calls is easier.
CookieYes Ideas
- Compliance assistant workflow.
- Cookie classification workflow.
- Regulatory monitoring workflow.
- AI governance review workflow.
Mozilor Ideas
- Accessibility remediation workflow.
- WooCommerce agent workflow.
- Support triage workflow.
- Documentation assistant workflow.