Last week in Hangzhou, I switched to my home computer and couldn’t find that morning’s AI conversation

I got stuck on the third step: I wanted the AI to continue working on the old code, but the session history seemed locked inside another machine. I used to bridge the gap with screenshots and copy-paste, and the files became messier and messier. Later I realized the problem wasn’t making the AI smarter—it was reconnecting to the “worksite” first.

I didn’t understand it right away either. Atuin Threads looks like an ordinary terminal tool. After installing it, I didn’t even know where to find the sessions, and I messed up my first sync. It took an afternoon to understand that it manages AI coding assistant sessions—not email, cloud storage, or chat history from every app. There’s no urgency to try it; screenshots can keep work moving for now.

What Atuin Threads is, and who’s using it

In short, it’s a cross-computer session index for AI coding assistants: questions asked and code changed on Computer A can be found and continued on Computer B. It leans toward independent developers and small software teams, not universal sync for every office app.

I know a freelance developer named Xiaolin who builds custom tools for clients. He works from a shared office in Nanshan, Shenzhen. At home in the evening, he lets the AI assistant on his local computer continue tests that hadn’t finished during the day. The next day, he uses Atuin Threads to reopen the previous day’s session instead of explaining the project background again. He says the most useful part isn’t how much the tool “remembers,” but avoiding one round of repeated context.

This kind of tool only suits people comfortable working in a computer terminal. If you mainly use a web-based AI, a desktop chat window, or don’t understand the command line at all, it may cause more trouble than the problem itself.

Replicating it today: budget, time, barrier, and first step

I spent 0 yuan in cash. Installing it and getting it working took about 40 minutes, including 20 minutes checking the setup instructions. The technical barrier isn’t high, but I needed to know what a “terminal” was and where my AI coding assistant stores sessions. I got this wrong too, assuming closing the app automatically saved the history.

The first step isn’t configuring every computer at once. It’s opening Atuin Threads’ installation guide, clicking the system button beside “Install,” and setting it up on one machine. After installation, I’d confirm that it can read one existing AI session, then sign in and sync on the second computer. My advice is to connect only two main devices first, rather than linking home, office, and backups all at once. Not everyone needs this tool, and it isn’t suitable for syncing passwords, private client files, or sensitive code.

Choose by your stage—don’t copy my mistakes

If I’m just starting out: I wouldn’t change my workflow yet. I’d keep one computer for regular projects and remember where one session lives. Once switching machines becomes frequent, I’d spend 40 minutes trying Atuin Threads.

If I already have 1–2 clients: I’d create a “work brief” covering the project goal, files already changed, and the next step, then enable cross-device sessions. That gives the AI context and makes it easier to check whether the work has drifted. For client materials, I’d remove sensitive details first.

If I’m scaling: I’d treat Atuin Threads as part of the development workbench, but not as access management or a backup solution. I’d define who can sync what and which repositories must stay out of session history, then enable devices one at a time.

My answer is plain: first, I’d confirm that “switching machines and losing context” really happens often. If it happens once a week, the time and hassle aren’t worth it. If I’m restating the same project every day, it’s worth adding to my toolkit. If I try it, I’d connect just two computers, finish one real task, and then decide whether to keep it.