“Tailscale was made for this”

→ NVIDIA DGX Spark: great hardware, early days for the ecosystem

This Simon Willison’s post is mainly about NVIDIA’s DGX Spark, which has just started shipping, but what really caught my attention was the part where he mentioned Tailscale, and the subheading is “Tailscale was made for this”:

Having a machine like this on my local network is neat, but what’s even neater is being able to access it from anywhere else in the world, from both my phone and my laptop.

Tailscale is perfect for this. I installed it on the Spark (using the Ubuntu instructions here), signed in with my SSO account (via Google)… and the Spark showed up in the “Network Devices” panel on my laptop and phone instantly.

I can SSH in from my laptop or using the Termius iPhone app on my phone. I’ve also been running tools like Open WebUI which give me a mobile-friendly web interface for interacting with LLMs on the Spark.

That is what I’ve been talking about with my friends. Although I don’t have a powerful Mac mini or a shiny DGX Spark, the way I use Tailscale is approximately what Simon Willison described in his post.

When I take a break between bouldering sessions, believe it or not, I sometimes use the Termius app on my iPhone to SSH into my Mac at home, check Claude Code’s work, or assign it new tasks via tmux running in Ghostty on my Mac.¹ Or when I come across noteworthy startup fundraising news on the go, I can use my iPhone to pull the same trick: ask an LLM to do the news clipping for me via Simon Willison’s LLM CLI running on my Mac at home. (Hopefully I will write about my LLM news clipping workflow soon. 2025-11-20 Update: I wrote a post about it.)

Sometimes how I use Tailscale has nothing to do with AI. For instance, I host Linkding, an open source bookmark web app, on my Raspberry Pi, and I want to use it on my iPhone without exposing it on the internet. In this case, I can use Tailscale Serve to securely access it through my tailnet as if I were on the same local network.

Another use case is about safely using untrusted Wi-Fi. I use one of my Raspberry Pis as a Tailscale exit node, so when I’m at a coffee shop with untrusted Wi-Fi, I can turn on Tailscale on my MacBook Air and securely route all my traffic through the exit node—Tailscale encrypts every packet between my MacBook Air and my Raspberry Pi using WireGuard,² so even on an untrusted Wi-Fi, no one can snoop on my connection. In fact, I created a Keyboard Maestro automation that connects my MacBook Air to the Tailscale exit node whenever it joins a Wi-Fi network that’s not on my allowlist.

As a user, I appreciate how easy Tailscale is to set up, even though I’m only using a fraction of its capabilities. As an observer who is interested in the tech startup scene, I’ll definitely keep a close eye on how Tailscale grows as a business.