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.

The Ideal Hardware Setup for Running Parallel Claude Code Agents

Fazm Team·March 17, 2026·3 min read

claude-code hardware tmux parallel-agents m3-max productivity

The Ideal Hardware Setup for Running Parallel Claude Code Agents

Running a single Claude Code agent is fine on most machines. Running five of them in parallel, each working on a different part of your codebase, requires real hardware. Here is what actually works.

The Hardware: M3 Max + 64GB RAM

The M3 Max MacBook Pro with 64GB of unified memory is the sweet spot for parallel agent workflows. Each Claude Code session consumes a meaningful amount of memory - the language server, file indexing, git operations, and the terminal itself all add up. With five sessions running simultaneously, you need headroom.

The M3 Max matters because the CPU cores handle parallel compilation across multiple agents without thermal throttling. When three agents trigger builds at the same time, you do not want them queuing behind each other.

The Workflow: tmux Sessions

Each Claude Code agent runs in its own tmux session, isolated and named:

tmux new -s agent-auth-refactor
tmux new -s agent-api-migration
tmux new -s agent-test-suite
tmux new -s agent-docs-update
tmux new -s agent-perf-optimization

This gives you clean separation. You can detach from any session, check on another agent's progress, and switch back without losing context. No more five terminal tabs all named "zsh" where you cannot tell which agent is doing what.

Why This Setup Works

The key insight is that parallel agents are only useful when they work on genuinely independent parts of the codebase. If two agents touch the same files, you get merge conflicts and wasted tokens. The tmux setup makes this boundary visible - each session name describes what that agent owns.

With this hardware and workflow, a day of development work compresses into a few hours. Five agents working in parallel is not five times faster, but it is close to three times faster once you account for coordination overhead.

Practical Tips

Use tmux ls to get a quick status overview
Name sessions by task, not by number
Keep a git worktree per agent to avoid file conflicts
Monitor memory usage with htop - if you are above 55GB, reduce to four agents

The bottleneck is never the hardware once you have an M3 Max with 64GB. It is always the coordination between agents and making sure they stay in their lanes.

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

The Ideal Hardware Setup for Running Parallel Claude Code Agents

The Ideal Hardware Setup for Running Parallel Claude Code Agents

The Hardware: M3 Max + 64GB RAM

The Workflow: tmux Sessions

Why This Setup Works

Practical Tips

More on This Topic

Related Posts

Five Months In: Why Parallel Claude Code Beats Nested Subagents

Learn AI Workflows or Find an AI-Safe Career? Why Going All-In Is the Bet

Managing 5+ Parallel Claude Code Agents Without Losing Track