AI in Visual Studio: Choose an Assistant for Your Project
Visual Studio and Visual Studio Code are separate editors with different AI assistant options. Here is how to compare what is available in each and keep your project context when your team changes assistants.
Updated 5 min read
Visual Studio and Visual Studio Code are two separate editors from Microsoft. Visual Studio is the full-featured IDE used mainly for .NET, C++ and enterprise Windows development. Visual Studio Code is the lightweight, cross-platform editor that most web and open-source developers use. AI assistant options differ between them, and it is worth knowing which you are running before you search for extensions.
Tools like fenbs keep your project context outside any one editor so the work record does not change when your team switches from one AI assistant to another.
Visual Studio versus Visual Studio Code
The two editors share a name but not a codebase. Visual Studio is a full IDE with built-in project management, a debugger, a designer surface and deep integration with MSBuild and NuGet. Visual Studio Code is a text editor extended by plugins, with no built-in project system.
AI assistants available for Visual Studio Code, such as Cursor or the GitHub Copilot extension, are not always available for the full Visual Studio. Check the extension marketplace for your specific editor version before assuming an assistant is available.
AI assistants available in Visual Studio
GitHub Copilot is the primary AI assistant for Visual Studio. It provides inline completions, a chat panel and, in recent versions, multi-file editing through the Copilot cloud agent. Microsoft has also added Copilot features directly into Visual Studio's own UI, including code explanations and fix suggestions in the error list.
Other third-party extensions exist, but GitHub Copilot has the deepest integration with the full Visual Studio IDE as of late 2026. Check GitHub's documentation for a current setup guide specific to Visual Studio.
Comparing AI assistant options
| Assistant | Available in | Strengths | Check before using |
|---|---|---|---|
| GitHub Copilot | Visual Studio and VS Code. | Deep Microsoft integration, inline completions, multi-file edits, project instructions in .github/copilot-instructions.md. | Which plan includes the cloud agent and multi-file editing; check GitHub's docs for current plan details. |
| Cursor | VS Code-based editor (separate download). | Full repo indexing, agent mode, AGENTS.md project instructions, large context window. | Not available as a plugin for full Visual Studio; it is its own editor. |
| Claude Code | Terminal and VS Code extension. | Reads AGENTS.md natively, long context, strong reasoning on complex code. | Terminal-first; VS Code extension is a companion, not a full inline editor. |
| IntelliCode | Visual Studio and VS Code. | Completion suggestions trained on public code patterns; no external API required. | Not a chat assistant; limited to completion suggestions. |
| fenbs | Not an IDE. Connected AIs read the shared work record over MCP. | Keeps requirements, decisions and context outside any IDE so they travel with the project. | Needs an AI assistant that supports MCP; see the Integrations page for supported tools. |
Prices, plan names and feature availability change. Check the vendor's current documentation rather than relying on any comparison article, including this one.
Keep context when your team changes assistants
If your team switches from GitHub Copilot to Cursor, or from Visual Studio to VS Code, the project requirements and decisions should not have to be re-explained. Store them in fenbs. Any connected AI reads the same project context over MCP, regardless of which editor your team uses. Create a free account and add your project now.
Create a free accountFree for one person · No credit card · Works with Claude, ChatGPT, Cursor and more
Project instructions in Visual Studio
GitHub Copilot reads a .github/copilot-instructions.md file at the repository root. This file can contain standing rules for the assistant: preferred libraries, naming conventions and what a reviewer needs to see. Keep it concise. A short, specific file is read and applied more reliably than a long one.
Decisions your team has made about the project are worth recording in both the Copilot instructions file and in fenbs Decisions and rules. The instructions file applies inside that editor; the fenbs record is readable by any connected AI on any editor.
What changes when you use agent mode
Agent mode lets the assistant take a task description and make changes across multiple files, run builds and propose a complete diff for review. It is useful for well-scoped tasks but requires more careful review than inline completions, because the assistant can touch files you did not expect.
Before running agent mode, write a clear task in one sentence. After it runs, check the diff against that sentence. If it changed files outside the scope you described, ask it to revert those changes before you commit. The task description you used is worth saving in fenbs so the next session can see what was asked and what was changed.
Preserving context when the team changes assistants
Each AI assistant stores its memory inside its own app or subscription. When a team member leaves, changes tools, or switches from Visual Studio to VS Code, that stored context stays behind. Requirements and decisions that live only in a chat panel are not available to the next assistant or the next person.
Keep the decisions that matter in a shared place. What is an AI brain explains why storing context outside a single AI app is more reliable than relying on any assistant's built-in memory.
How to do this with fenbs
- Create a free account and add your project.
- Write the key decisions your team has already made: preferred libraries, patterns that are not negotiable, and what the project is trying to do.
- Connect GitHub Copilot or another supported AI assistant over MCP from Integrations.
- Ask the assistant to read the project context at the start of each session before it proposes changes.
- When a team member switches tools or joins, ask their AI assistant to read the same context rather than walking them through the project by hand.