I think I've had more success recently with telling it to look at an old project I have in another folder on the system that does the thing I need to do. I've been using that technique to try and build a little self replicating worm to see it work in its own world. I keep jokingly telling people that we should just let a group on the 'good' side, whatever that might be, exploit and patch and move on. Inspired by Linux.Wifatch https://en.wikipedia.org/wiki/Linux.Wifatch

Defense as we see it today seems fundamentally broken. The answer is to fight it with more AI? That doesn't seem right. Can software reliably self evolve and keep patching itself? What certification is going to protect you from an intruder with their legion of minions, none of them, you don't have perfect visibility to your systems, your systems emit too many signals to ingest 100% of actions, so does software need to get fundamentally simpler?

Today has me wondering how many datacenters exist out there just for organized crime? Are the big kingpins of the world going all in AI as well?

Lots of questions popping into my head today, I'm trying to think how you would slow or stop this and I can't help but think we just need everyone to go outside and touch some grass and remember we're all stuck on the same rock.

I'll be sending architecture diagrams to my agent, I draw those much faster than I talk. I hope there's a good way to get alerted for agent waiting for your turn. Hmm I wonder if the Claude Code app will install on my Boox. I've been finding it fun to run Claude on weird things, if it runs linux there's a good chance. My favorite install was into my Steamdeck to debug some button sensitivity issues.

I've written three different solutions for platforms that solve this standard protocol layer. What has worked for us was deciding to standardize on the Kubernetes API for our services back in 2017, and then from then on, all our providers have provided either a k8s API to interact with resources, or provide a Cluster API for provisioning. For example we have two datacenter VM providers that implement the k8s API and we've been able to swap the providers with no user refactoring, it's a good solution in hindsight with how many people have k8s in their stack.

For the second big feature you're thinking of, we never really go a good solution to this problem, a lot of our workloads are long lived and not necessarily spot instance-able, but it's a very fun routing problem. Most of our need to be in multiple clouds is that we want to heavily separate our customer facing services, and keeping it away from internal workloads that support those customer APIs.

Is this public work? I'd love to take a look. This is my bread and butter.

I'm just a dev, but I appreciate the insights from other professionals.

They were an accessibility nightmare, but you use what you got. I tried so hard as a kid to understand flash, but had to settle on MS Frontpage to publish my first RPG page.

What's old is new again.

I can see how there's a big leap there, but I agree somewhat. If they are aware these are happening and can detect it as it is happening why are they not stopping them? What do you do there? It'll be cat and mouse for a while. Thinking of reasons they wouldn't try and stop it is just a lot of speculation in my brain.

It's probably a way harder problem than I think it is, but they are aware of them now, so I assume they are going to get more aggressive about it.

Let's say then that they can't detect them near real time or even a bit after, maybe they do have a big observabilty gap that no one has solved adequately.

The speed which they add features I've needed for governance is pretty close to the speed I 'manually' write those for my company. To me personally we are all just going fast and breaking everything and not having enough time to set up safe environments. I'm sure it's in the backlog.

It was the first newsletter I actually subscribed to back in the day! Sad to hear about his passing, his appearances on podcasts introduced me to the more business side of tech where I was just a hobbyist teen at the time.

RIP

I used to spend hours debugging video card issues and other modifications I've liked to make over the years and being able to describe my ideal system admin setup I could get onto what I actually wanted to do.

Heh, thinking about it now, I broke a MBR on a Windows install as a kid and if I would have had these tools I would have been able to fix it immediately, but back then it took me using enough Linux booted off live cds to learn debugging techniques to fix the MBR. And debugging is one of my best skills.

I have a linguistics background and a lot of my philosophizing lately has been on whether or not the emergent abilities of the LLMs is deep down a similar mechanism that creates our consciousness.

For a little bit I was working on having linguistics based evals for a kaggle competition. My challenge was whether or not I could mask things well enough to not trigger its internal state of certain phenomena, and that sent me down a rabbit hole that I'm still exploring.

This story resonated with a lot of questions that can come out of figuring a good solid answer to the what is consciousness question. The one I triggered for me is: Is our perception of time just a slow thread in the giant GPU we are running the universe on? Or more generally, what is time? That's a fun YouTube rabbit hole if you ever need one.

Another thing I have in the general sdlc process is having it add enough logging to verify features are turned on, configured as we expected, and that becomes enough feedback for most of my features.

I've been mostly focusing on being able to replicate this across stacks greater than 3 projects so far (with the eventual goal of having an agent be able to orchestrate our complete infra stack, and this being a large component of a DR plan to rebuild).

None of this is really new for us, I'm just the most knowledgeable in my group in how the different products across teams glue together so I've been creating these rube goldbergs as a prototype, and then having it iterate on codifying the parts that don't need a constant LLM. We were blessed to have an engineer a decade ago build out tooling for local container automation that matches 95% of the deployed infra stack. That last 5% sucks when you fall into it, but that's always been a truth. I've added and expanded the tool over the years with making it act more like the deployed environment networking wise, but a lot of things don't end up working well in docker containers on M series macs when most of our complicated virtualization in our private cloud can't run on them yet...