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Another option, if you already have terminal open, is to drag the file/folder from Finder into your terminal window. The path will be pasted there.

Yep. Many different options available. Seems to me most complaining about finder haven’t actually bothered to give it the benefit of the learning-curve they’ve given to other file managers. Explorer is so far behind Finder it’s ridiculous, yet people somehow think it is better? C’mon.

What are you talking about? Like I've said I've been using finder for 15 years and most of these things people are talking have absolutely no discoverability.

Like is the mac UI really supposed to be "Get frustrated, google it, and read how to do these things and special keyboard shortcuts/drag-and-drop/etc"?

To be clear I think macs are by far the superior product on the hardware front, but nobody should be discovering new UI tricks after 3 years, let alone a decade.


Probably a routing issue. Shot in the dark would be that one of these routers is NATing traffic, and the other router doesn’t have a route to that NAT’d range.


Other shot in the dark, misconfigured bridging or similar where ARP isn’t getting forwarded and rewritten quite right


Or look for something mangling SRV records, Minecraft seems to use those more regularly than everything else.


It’s interesting to observe and build LLM-driven solutions in Networking.

The biggest challenges that most of us networking people have are around velocity (how fast we can build and scale networks) and how effectively we can operate them (avoid defects, fix them fast when something breaks).

LLMs are great in both areas. AI helps with deployment challenges by speeding up tooling development and the creation of workflows on orchestration platforms. A manual process step today, say - reserving an IP address in an IP DB — is automated the next day instead of on a backlog for years. This post is an example of that (config-gen/config-deploy).

Operations use-cases are more interesting, IMO, and address the “too many signals” problems that we face. Network substrate telemetry, overlay telemetry, service host metrics, service metrics, customer metrics, recent change data, prior alarms - the list goes on. Being a network operator is not for the faint of heart and is under-mentioned on high stress job lists. AI makes AMAZINGLY good network operations triage agents, since they are able to immediately process so many signals.

Exciting times!


>LLMs are great in both areas.

Nuance. LLMs are just going to report that they cant SSH to an endpoint, after delivering your vibeconfig, and throw it back to you to resolve connectivity. Your velocity with LLMs will stall at break fix every time.

>AI makes AMAZINGLY good network operations triage agents, since they are able to immediately process so many signals.

I have seen a lot of tokens spent on solutions that could have just been grafana.


I'm a network engineer at a F500 and am no stranger to automation. We use a lot of Ansible and Terraform to manage both on-prem and AWS network infrastructure. Lots of Juniper and Cloudflare products, and we use NetCM, Netbox, Prometheus, and Grafana. But we've been playing with agents since late 2024, and our team has come a long way since then.

It was already easy enough and straightforward to deploy a network because we had built so many CLI tools to handle what we needed, but it still required a bit of a human touch to validate outputs and feed those to different tools. Thanks to skills with helper scripts, we're pretty close to one click deployments these days. So much of our maintenances or operations can even be handled from our phones. We can just tell an agent that there's a new version, or AMI, and we can reliably trust them to safely update the fleet from end to end without causing service disruptions. When customers need updates made, agents draft the PRs and I just review, and they deploy after I approve.

I would argue that most of what makes this possible though isn't LLMs themselves, but having invested in robust network design, consistent standards (snowflake setups or configs will cause you problems), proper observability, and detailed docs/runbooks. While I have my doubts that someone will ever be able to vibe code that knowledge and experience, you can certainly use agents to amplify an already strong engineering foundation.


>While I have my doubts that someone will ever be able to vibe code that knowledge and experience, you can certainly use agents to amplify an already strong engineering foundation.

Yep, I dont see any disagreement with you at all.


It seems odd that such a tiny proportion would run `discoverable=yes`. Any idea why that is? It makes me question the numbers.


My home lab has grown over the years, now consisting of a physical Proxmox cluster, and a handful of servers (RaspPi and micro hosts). A couple years back I got tired of failures related to host-level Docker issues, so I got a NAS and started using NAS storage for everything I could.

I also re-investigated containerization - weighing Docker Swarm vs K3s - and settled on Docker Swarm.

I’ve hated it ever since. Swarm is a PITA to use and has all kinds of failure modes that are different than regular old Docker Compose.

I’ve considered migrating again - either to Kubernetes, or just back to plain Docker - but haven’t done it. Maybe I should look at Uncloud?


Same, one of my very first gaming experiences. Nothing but great nostalgia!


Huge nostalgia wave seeing some of these. Many of them are hard for me to pinpoint but unmistakably familiar.

My first website was a geocities site back in ~1999, which was dedicated to StarCraft. I wish I could find it now; I remember it being really aesthetically pleasing - it would be funny to see how it held up.


“At the primary moment of disruption, we saw YemenNet (aka TeleYemen) lose transit from BICS (AS6774) and Global Cloud Xchange (AS15412) at 22:32 UTC and revert to satellite service from BusinessCom (AS197206)”

It’s never good when your primary ISP’s only connection out to the world is via satellite


Also curious about this



Amazon Prime’s price hikes have a predictable cadence: * 2014: $79 to $99

* 2018: $99 to $119

* 2022: $119 to $139

We should expect a price hike from $139 to $159 in 2026, assuming the trend continues.


Meanwhile, Google Fiber has been the same price for 15 years. At least according to the billboard outside my window.


It works out for them because bandwidth gets cheaper over time but inflation eats away at that. $70 today is like $50 back in 2010 when GFiber first launched.


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