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.

Does Fazm work in languages other than English?

Yes. Fazm works in any language - English, Russian, Spanish, German, Japanese, and more. You can speak or type in your preferred language and Fazm will understand and act. Some of our most active users run their entire workday in Russian, issuing voice commands to manage Jira tickets, write Slack messages, and navigate internal tools. There is no language setting to configure - just speak or type naturally and Fazm handles it.

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.

I Tracked 530 Working Memory Entries and Found a Retention Curve

Fazm Team·March 18, 2026·2 min read

ai-memory working-memory retention-curve agent-profile data-analysis

I Tracked 530 Working Memory Entries and Found a Retention Curve

Over six months of using AI coding agents daily, I logged every entry that went into my working memory files - MEMORY.md, CLAUDE.md, and project-specific context files. The total hit 530 entries. Then I tracked which ones actually got used and which ones just sat there consuming context window space.

The Retention Curve

The data tells a clear story:

Week 1: 95% of new entries are actively useful
Week 2: drops to 70%
Week 4: drops to 40%
Week 8: drops to 15%
Week 12+: drops below 5%

Most working memory entries have a half-life of about two weeks. After that, the context has shifted enough that the entry either no longer applies or the agent has internalized the pattern through repeated exposure.

Why Old Entries Hurt

Stale memory entries do not just waste context tokens. They actively mislead the agent. An entry saying "the auth endpoint returns 401 for expired tokens" was true three months ago but now the API returns 403. The agent trusts the memory entry over the actual error response it receives, leading to debugging sessions that chase the wrong problem.

Regenerate, Do Not Accumulate

The best approach is treating the AI profile like a cache, not an archive. Every two weeks, regenerate the memory file from scratch using only the last 14 days of interactions. This captures current patterns and drops stale information automatically.

The regeneration process:

Review the last two weeks of agent interactions
Extract patterns that repeated more than three times
Note any active workarounds or environment-specific quirks
Discard everything else

What Survives

Some entries are genuinely long-lived - fundamental project architecture decisions, environment setup notes, and personal preferences (like "never use em dashes"). These form a stable core of maybe 30-40 entries that persist across regeneration cycles. Everything else should be treated as temporary.

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

I Tracked 530 Working Memory Entries and Found a Retention Curve

I Tracked 530 Working Memory Entries and Found a Retention Curve

The Retention Curve

Why Old Entries Hurt

Regenerate, Do Not Accumulate

What Survives

More on This Topic

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