AI for Desktop: Choose an Assistant for Your Computer

Desktop AI assistants fall into several categories: chat apps you open in a window, screen-aware agents that can see and interact with your computer, and IDE or editor integrations that work inside development tools. The right choice depends on what you need the assistant to access and how much automation is appropriate for your workflow.

Switching between desktop tools — from a chat assistant to a coding tool to a productivity app — usually means starting each session without a record of what you were doing. A tool like fenbs keeps task context, decisions and Where we left off notes outside any one app, so a supported connected assistant can pick up where you left off, regardless of which desktop tool you use next.

What kinds of desktop AI assistant are there?

The category of "AI for desktop" covers very different things. Understanding which kind you need helps you evaluate the options accurately.

• Chat desktop apps: standalone windows for ChatGPT, Claude or Gemini — the same models as the browser versions, packaged as a native app with keyboard shortcuts and system integration.
• Screen-aware agents: assistants that can see your screen and take actions — clicking, typing, reading app content — typically using a computer use or operator API.
• IDE and editor integrations: GitHub Copilot, Cursor, VS Code with Copilot or Claude Code running alongside your code editor.
• OS-level assistants: Microsoft Copilot is integrated into Windows 11 and Windows 10 (via updates); Apple Intelligence is integrated into macOS and iOS.
• Productivity app integrations: AI features built into Notion, Google Docs, Microsoft Office and similar tools.

How do the main desktop AI options compare?

This is a fast-moving area. Check each vendor's download page for current OS support and minimum system requirements before installing.

What permissions do desktop AI assistants need?

Desktop AI apps vary widely in what they ask to access. A chat app with file upload only accesses files you explicitly drag in. A screen-aware agent that can control your computer needs accessibility permissions and, depending on the OS, screen recording permissions.

Before granting permissions, consider what the app will be able to see and do. Accessibility permissions on macOS and Windows give an application the ability to read on-screen content and simulate input across all apps. That is a significant trust decision, separate from the AI model's privacy policy.

• Read your files: only files you share or a folder you grant access to.
• Screen reading: seeing what is currently visible on your display.
• Screen recording: capturing screenshots or video of your screen, possibly for analysis.
• Accessibility access: reading content in other apps and simulating keyboard and mouse input.
• Network access: sending your prompts and screen content to a remote server for processing.

For work involving confidential documents, check your employer's approved tool list before granting any of these permissions to a new desktop app.

What does a screen-aware AI agent actually do?

Screen-aware agents can read what is visible on your screen and take actions in response to your instructions. You might say "summarize what is in that spreadsheet" and the agent reads the screen rather than requiring a file upload. More capable versions can click, type and navigate applications on your behalf.

This is useful for automating repetitive point-and-click tasks, filling in forms or navigating tools that do not have an API. The risk is that a misunderstood instruction can take real actions — clicking a button, submitting a form, deleting a file — without a confirmation step. For agentic automation that involves approvals, the AI agent approval workflow guide covers how to set up checkpoints.

How do desktop AI apps handle context between sessions?

Most desktop AI chat apps start a new session each time you open the app, with prior conversations stored but not automatically loaded. Chat history is useful for looking back but is not the same as a structured project record the assistant reads before acting.

Claude has Projects (available via claude.ai and the desktop app) that store a shared system prompt and files for a group of conversations. ChatGPT has a memory feature that saves preferences and facts across chats. These help with preferences and repeated tasks but are not designed to carry structured task status and project decisions across tools.

How to do this with fenbs

1. Create a free account and add your current project with its tasks and decisions.
2. Check Integrations for supported desktop assistants. Connect via MCP using the browser-based OAuth sign-in — no tokens to paste.
3. Ask the connected assistant to read your project context at the start of each session. It will read Rules first, then Where we left off, In progress tasks and what is Waiting on you.
4. When you switch desktop tools — say, from Claude desktop for writing to VS Code with Copilot for coding — the project context is the same. The tool changes; the record does not.
5. Before ending a session, ask the assistant to save progress. Record the current state of each task it touched and where the project stands.

When a simpler setup is enough

If you use one desktop AI tool for all your tasks and the work is self-contained — each session is its own problem — a shared project record adds overhead for little benefit. fenbs earns its place when you move between tools, work on ongoing projects, have a team or need decisions and lessons to carry forward.