Naseem is a native AI agent for macOS, built entirely in Swift. It can work with your files, run terminal commands and Python, drive native Mac apps, automate and test apps in the iOS Simulator, use MCP and Skills, delegate to sub-agents, and work remotely through Telegram. Bring your own model or run locally with Ollama/MLX. Every consequential action requires your approval first, and autonomous mode is strictly opt-in. No Electron. No Node. It does real work on your Mac — with you in control.
Hi Product Hunt 👋
I built Naseem because I wanted an AI agent that doesn’t just live in a chat window — I wanted one that actually lives on my Mac and can do work there.
So I built it natively in Swift. No Electron, embedded browser, or Node runtime.
Naseem can work with files, use the terminal and Python, control native Mac apps, drive the iOS Simulator, use MCP servers and reusable Skills, delegate to sub-agents, and even be reached remotely through Telegram.
One of my favorite tests was giving it an empty Xcode project and asking it to build a small Minecraft-style iOS game. It wrote the code, hit build errors, fixed them, rebuilt, launched the Simulator, interacted with the game, and tested what it had made.
That’s the direction I want to take Naseem:
LLM + Agent Harness + Your Mac
You choose the model — cloud APIs, Ollama, or local MLX — while Naseem provides the tools and environment that let the model actually act.
Naseem Free is free forever, and every install includes a 30-day Pro trial with no card required.
This is still the beginning, and feedback is one of the main reasons I’m launching it here. I’d especially love to know: what real task would you hand to an agent that lives on your Mac?
— Ayman Hamed
About Naseem on Product Hunt
“A native AI agent that does real work on your Mac”
Naseem launched on Product Hunt on September 1st, 2026 and earned 76 upvotes and 1 comments, placing #21 on the daily leaderboard. Naseem is a native AI agent for macOS, built entirely in Swift. It can work with your files, run terminal commands and Python, drive native Mac apps, automate and test apps in the iOS Simulator, use MCP and Skills, delegate to sub-agents, and work remotely through Telegram. Bring your own model or run locally with Ollama/MLX. Every consequential action requires your approval first, and autonomous mode is strictly opt-in. No Electron. No Node. It does real work on your Mac — with you in control.
On the analytics side, Naseem competes within Mac, Developer Tools and Artificial Intelligence — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Naseem performed against the three products that launched closest to it on the same day.
Who hunted Naseem?
Naseem was hunted by Ayman Hamed. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Ayman Hamed