Generative AI (Gen AI)
Gen AI creates new content based on prompts.
Examples:
Writing emails
Generating code
Creating images
Summarizing documents
Answering questions
Popular Gen AI tools:
ChatGPT
Google Gemini
Claude
GitHub Copilot
Example
Prompt:
Create a C# Employee CRUD API.
Gen AI:
Generates the code.
Stops after providing the answer.
Agentic AI
Agentic AI goes beyond generating content. It can plan, decide, and execute tasks.
Workflow
User Goal:
Build and deploy an Employee Management System.
Agentic AI may:
Analyze requirements.
Generate database schema.
Create backend APIs.
Create frontend UI.
Run tests.
Fix errors.
Deploy to cloud.
Monitor results.
This is an AI "agent" working toward a goal.
Components of Agentic AI
Large Language Model (LLM)
Memory
Planning
Reasoning
Tool Usage
API Access
Decision Making
Real-World Example
Gen AI
You ask:
Write SQL query to find top 10 employees.
AI returns the query.
Done.
Agentic AI
You ask:
Analyze employee performance and send a report.
AI:
Connects to database
Runs queries
Creates charts
Generates report
Emails management
All automatically.
Architecture Comparison
Gen AI
User
↓
Prompt
↓
LLM
↓
Response
Agentic AI
User Goal
↓
Agent
↓
Planning
↓
Tools/APIs
↓
Reasoning
↓
Execution
↓
Result
Examples of Agentic AI Frameworks
LangChain
LangGraph
CrewAI
AutoGen
OpenAI Agents Platform
Gen AI vs Agentic AI
Many people use these terms interchangeably, but they are different.
| Feature | Generative AI (Gen AI) | Agentic AI |
|---|---|---|
| Purpose | Generates content | Takes actions to achieve goals |
| Output | Text, code, images, videos | Decisions, actions, workflows |
| User Role | User gives prompt and gets response | User gives goal and AI performs multiple steps |
| Memory | Usually limited conversation memory | Can maintain context and state |
| Tool Usage | May or may not use tools | Actively uses tools, APIs, databases |
| Autonomy | Low | High |
| Example | ChatGPT generating code | AI creating code, testing it, fixing bugs, and deploying it |
Example
Simple Rule
Best AI Integration Tools in Visual Studio 2022 (2026 Guide)
Artificial Intelligence is changing software development rapidly. Today, most software engineers use AI tools inside Visual Studio to write code faster, debug applications, generate APIs, and improve productivity.
If you are using Microsoft Visual Studio 2022, here are the best AI integration tools you should install in 2026.
1. GitHub Copilot – Best AI Coding Assistant
GitHub
GitHub Copilot is currently the most popular AI coding assistant for developers.
Features
- AI code completion
- Full function generation
- AI chat support
- Bug fixing suggestions
- Unit test generation
- Supports C#, ASP.NET, Python, JavaScript, Java, and more
Best For
- Professional developers
- Students
- Enterprise teams
- Full stack development
Official Website
How to Integrate GitHub Copilot in Visual Studio 2022
Step 1: Open Visual Studio 2022
Launch Visual Studio.
Step 2: Open Extensions Manager
Go to:
Extensions → Manage Extensions
Step 3: Search “GitHub Copilot”
Click:
- Download
- Install
Restart Visual Studio.
Step 4: Sign In
Login using your GitHub account.
Step 5: Start Using AI
Now start typing code.
Example:
// create login api in asp.net core
Copilot will automatically generate code suggestions.
2. Visual Studio IntelliCode – Best Free AI Tool
Microsoft
Visual Studio IntelliCode is Microsoft’s built-in AI assistant.
Features
- Smart IntelliSense
- AI-based recommendations
- Learns coding patterns
- Optimized for C# and .NET
Why Use It
- Free
- Lightweight
- Built directly for Visual Studio
Official Website
How to Enable IntelliCode
Usually IntelliCode comes preinstalled.
If not:
Step 1
Open:
Extensions → Manage Extensions
Step 2
Search:
IntelliCode
Install and restart Visual Studio.
Step 3
Enable IntelliCode
Go to:
Tools → Options → IntelliCode
Enable all recommendations.
🥉 3. GitHub Copilot Chat
🥉 3. GitHub Copilot Chat
GitHub Copilot Chat Documentation
Features
- Ask questions about your project
- Explain exceptions and errors
- Generate SQL queries
- Create APIs
- Generate test cases
- Documentation generation
Example:
Create ASP.NET Core Web API CRUD for Employee with Entity Framework Core
Copilot Chat can understand project context and assist throughout the development lifecycle.
4. Codeium – Best Free Alternative to Copilot
Codeium
Codeium is one of the best free AI coding assistants.
Features
- Unlimited AI autocomplete
- AI chat
- Code explanation
- Fast suggestions
Best For
- Students
- Beginners
- Freelancers
Official Website
How to Integrate Codeium
Step 1
Open Visual Studio.
Step 2
Go to:
Extensions → Manage Extensions
Step 3
Search:
Codeium
Install extension.
Step 4
Restart Visual Studio.
Step 5
Sign in to Codeium.
AI coding assistant is ready.
4. CodeRush AI (AiGen)
Features
- AI-assisted refactoring
- Code generation
- Bug fixing
- Test generation
- Solution-wide updates
Best AI Setup for Visual Studio 2022
| Requirement | Recommended Tool |
|---|---|
| Best Overall | GitHub Copilot |
| Best Free Tool | Codeium |
| Best for .NET | IntelliCode |
| Best for Security | Tabnine |
| Best for AWS | Amazon Q |
Recommended Combination
Best Paid Setup
- GitHub Copilot + IntelliCode
Best Free Setup
- Codeium + IntelliCode
Final Thoughts
AI tools are becoming essential for software engineers in 2026. Companies now expect developers to use AI for:
- Faster coding
- Debugging
- API generation
- Refactoring
- Documentation
- Testing
If you are learning software development, start using AI tools early to improve productivity and stay industry-ready.
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