uberduper

I get about 20 minutes of work from my 5h limit with the $20 plan. It wouldn't bother me as much if codex would continue after the token bucket refills instead of waiting for me to show up and tell it to continue. I don't jump to the $100 plan because I would be in the exact same situation.

Gimme an rtx spark in the new framework 13 pro.

My take from working at a Big Corp is that individuals using coding agents can increase velocity substantially and produce good quality work, assuming they are proficient with the tools. But it falls apart quickly when you have a team trying to work together.

imo we either need to centralize the agent and and submit plan, spec, reference doc MRs rather than submitting code changes. Or develop SCM systems/workflows that incorporate plan/spec/reference/prompt metadata with code so intent can be factored into merges.

Nix isn't involved in my container images. I just take the dependencies and env vars from the flake and generate a dockerfile.

Guess I need to try out dockerTools. That looks really convenient. Thanks!

I do the same. Codex manages a per project flake.nix and uses `nix develop` for all testing. nix-direnv for my own convenience. I generally have it generate dockerfiles or other deployment assets at some point.

Codex is way better at nix than I am.

The distinction is scale. "AI Datacenters" are a new level of scale with new levels of power consumption and heat generation. Sure you could run regular compute and w/e in them but it's not practical to build these mega sites for regular compute. GPU Compute / AI workloads require network/interconnect bandwidth and latencies where distance matters so you're forced to solve problems you wouldn't otherwise have to. Those problems are mostly solved with money.

No. Agendas like, "I need to push my ideas for promotion credits."

I'm building the same stuff I've always built. Just faster and with less dependence on others. Not having to argue with devs that have their own agendas has been my biggest benefit from coding agents.

TBF this was the case prior to the firmware change. It wasn't a bait and switch. It just wasn't obvious to someone buying a printer they thought worked with open source slicers.

Did you install the network connector Orca slicer prompted you to download? It's a closed source blob that runs on your PC which I'm presuming you haven't air-gapped as well.

`initcall_blacklist` is a thing.

amd gpus compete but they lack the interconnect. NVLink performance is a huge deal for training.

There's a few dimensions you can look at for gpu load. Probably the easiest indirect metric to watch for gpu load is power usage.

But if you really care about this, you should actually profile your application. nsight systems makes this pretty simple to do. Dunno how many actually care about having a TUI.

I previously worked at a managed database as a service company. On more than one occasion during my time there, a junior engineer deleted a customers database and at least one time one of our most senior dbas made it unrecoverable. Never got such straight forward confessions out of them.

I did some work on an agent that was supposed to demonstrate a learning pipeline. I figured having it fix broken linux servers with some contrived failures would make for a good example if it getting stuck, having to get some assistance to progress, and then having a better capability for handling that class of failure in the future.

I couldn't come up with a single failure mode the agent with a gpt5.x model behind it couldn't one shot. I created socket overruns.. dangling file descriptors.. badly configured systemd units.. busted route tables.. "failed" volume mounts..

Had to start creating failures of internal services the models couldn't have been trained on and it was still hard to have scenarios it couldn't one shot.

Do people really want codex to have control over their computer and apps?

I'm still paranoid about keeping things securely sandboxed.

Well they're liquid cooled, so there's some extra handling required. Then there's the sky high failure rate.

A dozen people couldn't handle the number of daily nvidia compute tray RMAs one of these datacenters produces.

Appreciate you making my point for me.

I don't know anything about this particular site, but I presume it's one of the new mega gpu sites.

I'm seeing many people in the comments with an early 2000's era concept of datacenters. The scale of these new sites is mind boggling. Take your idea of a typical datacenter building. Make it 4x bigger. Then put 4 of them together into a cluster. Then imagine 10 of those clusters at the site.

There's going to be continued support from local electricians, low voltage wiring vendors, various facilities service companies, HVAC, and now plumbers.. lots of plumbers. So many leaks. A site like this is going to have probably a few hundred full time people on site all the time in addition to the contracted folks.

Local shops will absolutely be contracted to work on the project. A datacenter project like this can't find enough qualified electricians.

Many jobs during construction. A site like this is a substantial multi-year construction effort.

Long term permanent jobs.. not so much.

CDDL is more permissive than gpl. It's not a violation of cddl to intermingle with code under a different license. GPL is the issue and it's the individual contributors to linux that _could_ sue.

There's no zfs grenade. It's CDDL, feel free to use it wherever you want. Oracle can't come after you for violating the gpl even if somehow using zfs on linux violates the gpl.

Recent freecad is pretty decent. My main complaint these days is the performance of the geometry engine.

AWS loop a long while back wanted me to design a playlist system so my dumbass brain snapped to m3u files or w/e people were using back then and designed a system to host/share playlist files. The teenager (ok probably in their 20s) interviewing me seemed more and more confused as we went on but he never tried to redirect me to what he really intended.

If you actually want to use vxlan ids to isolate l2 domains, like if you want multiple hypervisors separated by public networks to run groups of VMs on distinct l2 domains, then vxlan over WG seems like the way to go.

What are your discovery mechanisms? I don't know what exists for automatic peer management with wg. If you're doing bgp evpn for vxlan endpoint discovery then I'd think WG over vxlan would be the easier to manage option.

This leads to authors having to re-explain their thinking in detail, covering points that they’d omitted for brevity or because they are obvious to those with a good understanding of the problem.

There's nothing wrong with this. Being able to explain your thinking in detail to someone that doesn't necessarily understand the problem is a pretty good exercise to make sure you yourself fully understand the problem _and your thinking._ Of course, this can't turn in to a lecture on basic things people should know or have looked up before commenting.