Well, I know what I'm doing next weekend.. I was already gonna pick up an esp32-s3 for another project, now I need two...

Personally I like Drone more than Buildkite. It's as close to a perfect CI system as I've seen; just complex enough to do everything I need, with a design so stripped-down it can't be simpler. I occasionally check on WoodpeckerCI to see if it's reached parity with Drone. Now that AI coding is a thing, hopefully that'll happen soon

You can use `ln` atomicity for a simple, portable(ish) locking system: https://gist.github.com/pwillis-els/b01b22f1b967a228c31db3cf...

War is peace. Freedom is slavery. Ignorance is strength.

> I'm not [yet?] running multiple agents, and currently don't really want to

This is the main reason to use AI agents, though: multitasking. If I'm working on some Terraform changes and I fire off an agent loop, I know it's going to take a while for it to produce something working. In the meantime I'm waiting for it to come back and pretend it's finished (really I'll have to fix it), so I start another agent on something else. I flip back and forth between the finished runs as they notify me. At the end of the day I have 5 things finished rather than two.

The "agent" doesn't have to be anything special either. Anything you can run in a VM or container (vscode w/copilot chat, any cli tool, etc) so you can enable YOLO mode.

  If your business relies on compute, and you run that compute in the cloud, you are putting a lot of trust in your cloud provider. Cloud companies generally make onboarding very easy, and offboarding very difficult. If you are not vigilant you will sleepwalk into a situation of high cloud costs and no way out. If you want to control your own destiny, you must run your own compute.

This is not a valid reason for running your own datacenter, or running your own server.

  Self-reliance is great, but there are other benefits to running your own compute. It inspires good engineering. Maintaining a data center is much more about solving real-world challenges. The cloud requires expertise in company-specific APIs and billing systems. A data center requires knowledge of Watts, bits, and FLOPs. I know which one I rather think about.

This is not a valid reason for running your own datacenter, or running your own server.

  Avoiding the cloud for ML also creates better incentives for engineers. Engineers generally want to improve things. In ML many problems go away by just using more compute. In the cloud that means improvements are just a budget increase away. This locks you into inefficient and expensive solutions. Instead, when all you have available is your current compute, the quickest improvements are usually speeding up your code, or fixing fundamental issues.

This is not a valid reason for owning a datacenter, or running your own server.

  Finally there’s cost, owning a data center can be far cheaper than renting in the cloud. Especially if your compute or storage needs are fairly consistent, which tends to be true if you are in the business of training or running models. In comma’s case I estimate we’ve spent ~5M on our data center, and we would have spent 25M+ had we done the same things in the cloud.

This is one of only two valid reasons for owning a datacenter, and one of several valid reasons for running your own server.

The only two valid reasons to build/operate a datacenter: 1) what you're doing is so costly that building your own factory is the only profitable way for your business to produce its widgets, 2) you can't find a datacenter with the location or capacity you need and there is no other way to serve your business needs.

There's many valid reasons to run your own servers (colo), although most people will not run into them in a business setting.