How much time will I actually save with Fazm?

Most users report saving 45-90 minutes per day on repetitive tasks. The biggest time savings come from email management (drafting replies, sorting, archiving), form filling (expense reports, CRM updates, applications), research (comparing products, gathering data from multiple sites), and social media (cross-posting, scheduling, replying). For example, booking a flight that normally takes 10 minutes of clicking through airline sites takes a single voice command with Fazm. Filing an expense report that requires opening a PDF, extracting numbers, and entering them into a spreadsheet becomes one spoken sentence. The more repetitive and multi-step your daily work is, the more time you get back.

What exactly can Fazm control?

Fazm controls everything you can do manually on your Mac. That includes mouse movements and clicks, keyboard typing, browser navigation and form filling, app switching, file management in Finder, and system-level actions. It uses direct browser DOM control for web interactions - meaning it reads and manipulates the actual page structure rather than taking screenshots and guessing where to click. For native macOS apps, Fazm uses accessibility APIs to interact with buttons, menus, text fields, and other UI elements. This works across any application: Chrome, Safari, VS Code, Slack, Figma, Terminal, Mail, Calendar, and more.

How is Fazm different from ChatGPT or Claude?

Chatbots like ChatGPT and Claude give you answers in a conversation window. Fazm takes action directly on your computer. When you say 'reply to Sarah's email,' Fazm opens your email app, finds Sarah's message, writes a contextual reply, and sends it. A chatbot would tell you what to write, but you still have to do all the clicking and typing yourself. Fazm moves your mouse, types on your keyboard, clicks buttons, and navigates between apps. It is a computer agent, not a chat assistant.

How does the memory layer work?

Fazm builds a personal knowledge graph by extracting information from your files, browsing history, conversations, and daily activity. Over time, it learns your contacts (names, emails, relationships), accounts and credentials, preferences (formatting, tone, scheduling habits), and frequently used workflows. In your first week, you might say 'Reply to Sarah's email, she's my cofounder, her email is sarah@acme.com.' By week four, you just say 'Reply to Sarah' because Fazm already knows who she is. By week eight, Fazm can draft the reply before you even ask. All of this data stays locally on your Mac - your knowledge graph never leaves your machine or gets sent to any cloud service.

Is Fazm safe? Can it mess up my computer?

Safety is built into every layer of Fazm. You watch every action in real-time on your screen - Fazm moves your mouse and types visibly, so there is nothing hidden. You can stop any action at any point by pressing a keyboard shortcut. Fazm also shows you what it plans to do before executing destructive actions like deleting files or sending emails, giving you a chance to confirm or cancel. Because Fazm is open source, the code is fully auditable on GitHub. There is no hidden behavior, no background processes making changes you cannot see, and no actions that bypass your screen.

What platforms does Fazm support?

Fazm currently supports macOS, running natively on both Apple Silicon (M1, M2, M3, M4) and Intel Macs. It is built with Swift and uses macOS-specific frameworks like ScreenCaptureKit for screen analysis and Accessibility APIs for app control, which is why macOS is the primary platform. Windows and Linux support are on the roadmap but do not have release dates yet. You can also control your Mac remotely from your phone using Fazm Remote, which gives you voice access to your desktop while you are away from your computer.

How does Fazm voice input work?

One keyboard shortcut activates push-to-talk. Hold the key, speak naturally about what you need done, and release. Fazm transcribes your speech locally using on-device models, so there is no network latency for the voice recognition step. You do not need wake words like 'Hey Siri' or 'OK Google' - just press and talk. You can also type commands into the floating toolbar if you prefer text input. Fazm understands natural language, so you do not need to memorize specific commands. Say 'book me a flight to Tokyo next Thursday' or 'find the cheapest AirPods on Amazon' and Fazm figures out the steps.

Is my data sent to the cloud?

Fazm processes screen analysis and memory entirely on your machine. The personal knowledge graph, file indexing, and screen capture all run locally. The only data that leaves your Mac is the intent - a text description of what you want to accomplish, which is sent to the AI model (Claude or GPT) for action planning. Your actual screen content, file contents, browsing history, and personal knowledge graph never leave your computer. Fazm is also open source, so you can verify exactly what data is transmitted by reading the code on GitHub. For users who need complete air-gapped operation, local model support is planned.

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Building Native macOS Apps with Claude Is a Different Beast Than Web Dev

Fazm Team·March 17, 2026·3 min read

macosswiftclaudenative-developmentappkit

Building Native macOS Apps with Claude Is a Different Beast Than Web Dev

If you have used Claude to build a React app, you know it is remarkably good. Drop in a description, get working code. But try building a native macOS app in Swift and the experience changes completely.

The reason is simple - training data. There are millions of React tutorials, Stack Overflow answers, and open source repos. For AppKit? Maybe a few thousand relevant posts, many of them outdated. SwiftUI is better but still has gaps, especially for macOS-specific features that differ from iOS.

Where Claude Hallucinates

The most common failure mode is Claude inventing APIs that do not exist. It will confidently write NSWindow.setFloatingBehavior(.alwaysOnTop) - a method that sounds right but has never existed. The real approach involves setting window.level to .floating and configuring the collection behavior.

Accessibility APIs are even worse. Claude will suggest AXUIElementCopyAttributeValue calls with attribute names that are close to real ones but slightly wrong. kAXTitleAttribute exists, but Claude sometimes uses kAXLabelAttribute (which does not) or mixes up the attribute constants with their string values.

What Actually Works

The fix is a detailed CLAUDE.md file. Not a generic one - a file that contains actual working code snippets for the patterns your app uses.

Include things like:

How your app creates and manages windows
Working accessibility API call patterns with correct attribute names
SwiftUI view patterns that compile on macOS (not iOS)
Which APIs require specific entitlements or permissions

When Claude has concrete examples of working code in context, it extends those patterns correctly. Without them, it falls back to interpolating from its training data - and for native macOS, that training data has too many gaps.

The Investment Pays Off

Building the CLAUDE.md takes time upfront. But once it covers your core patterns, Claude can extend them reliably. The second accessibility API wrapper takes 30 seconds. The twentieth SwiftUI view follows the same structure automatically. The key is giving Claude ground truth rather than letting it guess.

Fazm is an open source macOS AI agent. Open source on GitHub.

Building Native macOS Apps with Claude Is a Different Beast Than Web Dev

Building Native macOS Apps with Claude Is a Different Beast Than Web Dev

Where Claude Hallucinates

What Actually Works

The Investment Pays Off

Related

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