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Latent Space · 3 min · Oct 22, 2026

Snapshotting can make massive test parallelism practical

  • Shawn Wang (swyx)Host · Co-founder, AI Engineer

    Wrote “The Rise of the AI Engineer” and founded Smol AI, maker of AI News.

  • Alessio FanelliHost · Founder, Kernel Labs

    Partner at Decibel, backing technical founders who build developer tools.

About this segment

Bernhardsson argues that agents could run tests in separate, short-lived sandboxes if setup can be snapshotted and cloned. Cutting startup overhead could make highly parallel testing worthwhile.

From “Why AI Compute Comes in Rectangles — Erik Bernhardsson, Modal”, Oct 22, 2026. Watch the full episode

“having the ability to like spin up a sandbox in, you know, 100 millisecond, run a few commands, and then like shut it down and like snapshot it.”
Erik Bernhardssonat 44:09 · Latent Space44:09

Takeaways

  1. Short-lived sandboxes could make compute more efficient.
  2. Snapshotting avoids repeating slow test setup in every shard.
  3. Lower overhead could let teams run each test in parallel.

In this episode

Full episode
  1. 15:24Renting GPUs avoids some risks but creates long-term exposure5:57
  2. 28:18Neoclouds scale by pre-selling GPU capacity3:40
  3. 43:26Snapshotting can make massive test parallelism practical3:26

  4. 5 more moments in the full episode
Up next · The Knowledge ProjectA venture reset is coming, so founders should hoard runway3:51

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

  1. 43:32

    use case for snapshotting? Like, what would that give us that we don't get right now? I think the big thing for me is like, today, a lot of sandbox workloads are kind of like lift and shift like people think a lot about sandboxes almost like you know i have my dev box now i'm going to shove it in the cloud i'm going to have an agent control it maybe i'll run the harness inside the sandbox i don't know if like long term that's like the right way to think about you know on like compute for I think a much better model would be you're going to have this like very long running agents, which almost like to me are like kind of durable execution workflows, like they're going to run, you know, 24 seven, you know, every once in a while, they're going to run commands and, you know, having the ability to like spin up a sandbox in, you know, 100 millisecond, run a few commands, and then like shut it down and like snapshot it.

  2. 44:24

    I think the faster you can get that like you know wake up you know go to sleep cycle the more you can sort of create sandboxes that only run for like a very brief period and that will make compute much more efficient and it will also enable you to do some really cool things you know like forking and moving things around and you know having like imagine you know like clawed code instead of you know having sort of a very linear flow like sequential flow like kind of branching and running hundreds of agents at the same time.

  3. 44:54

    I think a lot about CI is another illustrative example. For most of the history of CI, talk about GitHub actions and things like that, you've had a very sequential flow. You slowly install a bunch of stuff, then you run the test suite, and then generate some reports or whatever. And it's like you can break it up into shards, but it's kind of annoying. What I would love to do is take your entire test suite and just run every single test in its own sandbox, right?

  4. 45:19

    like and just paralyze the shit out of that around like a thousand sandboxes why can't that be done i mean the problem is like there's too much there's too much overhead around like you know starting and stopping sandboxes so i think the more like you you create like you know frictionless like starting and stopping the more you can enter a world where like you can do this like extremely bursty like large scale like run as much as you want in parallel so you know i'm an infra geek Like I said, like I get very excited about these things.

  5. 45:49

    You know, once we figure out all these primitives and the right building blocks, I think it's going to unlock a lot of really cool stuff that, you know, we previously could not do with software. Why hasn't that already been built? I would assume even previously people would want to parallelize as much of their CI as possible. You can't, but the overhead, it's like Amdahl's law or whatever, right? Like the overhead of parallelization right now is very high because like right now, like in GitHub Actions, for instance, like we parallelize in the modal test suite, But what that basically means is now if you take your test suite and you split it up in two, now each of those shards both need to do all the installs and the test setup.

  6. 46:27

    And that takes a long time. It can take minutes. But let's say you can do the test setup once, and then you snapshot the container, and now you clone it, and now you can run the test suites independently. I think a lot of the benefits cannot be, you can't materialize those benefits until you get the friction and the overhead down, the transaction cost.