Yeah. “Breaking confinement” = confines broken.

Interesting problem… how do you store energy when it comes in the form of small heat differentials? That sounds like one hell of an interesting battery.

Maybe if there was also a natural source of cold, as well as a natural source of heat. The problem might then be to store the hot/cold inside a material until they can be mixed. Then mixing in such a way that allows energy extraction?

Except you wouldn’t mix them directly. You’d instead let them try to mix thermally, while forcing the heat to travel through something that allows energy extraction.

Exchange still occurs globally and amongst the upper class.

Fair enough. You guys can basically collude to control the labor supply, if your niche is small enough. All the more power to you; I wish more of the labor force had guns like that.

It would be awesome if you could localize the results. Knowing that Microsoft is one of the worst offenders helps me very little, because I live in bumfuck nowhere. However, I bet I’d find some useful stuff at https://bumfucknowhere.didtheyghostyou.com/

This is awesome but it can never have an impact on hiring practices. Making this information public can change behaviors, given the data can’t be cooked.

Why can they spend money now, but make it so on paper it’s as if they spent it next quarter?

This probably won’t fix anything, but hopefully stops it from contributing to the issue further down the line

…meme

Damn, I never thought about how AI is making it so that even the professionals are unprofessional now… because AI enables the posers to get the job, and then they keep using AI to keep the job.

How can you maintain a workforce of specializations under these conditions?

Honestly, I’ve had a rather interesting experience with AI. I was very adverse to LLM usage at first. Later I sort of figured out that I was more adverse to the energy around AI than I am AI itself.

I knew the models sucked at large tasks. Trying to get an edge on the matter though, I started asking myself, how can I get the model to perform better? I figured I could pass over the AI hate stage and get right into the AI professional stage… at least a head start.

So I began experimenting with local LLMs, LLM harnesses, and various governance tools like jai. I decided against Claude Code and Cortex because they’re provider specific — instead using OpenCode so that I can use whichever model I desire. Then I began building out a SKILL.md repository for tightly scoped tasks like change-review, security-analysis, refactor, architecture-review, grill-me, feature-design, …

I’m still thinking through some of the project needs. I want something that lets an agent work, while treating the agent as a kind of helpful adversary. You should be able to configure workloads that designate models, context, available tooling, skills, permissions, session length, inference level, acceptance criteria, and human-review stages. It would also allow for session switching, model switching, agent deliverable handoff to another agent, … not to mention, your VCS should know and respond appropriately if an agent ever pushes code. Don’t trust it by default.

These workloads should be version controllable, benchmarked, …

Anyway, a lot of that is speculative. Just where I’m at now, controlling context and skills manually, I’m already seeing much better results.

And no, I don’t have the AI do everything. I just find smarter ways to decompose “everything” into much smaller tasks that are easier to review and scrutinize.

But also, I push for local model usage in my organization. I don’t want my success to mean success for the AI companies. Fuck the AI companies.

I told my boss this:

• Right now the AI race has a lot of similarities to the dotcom bubble. The subject is packed with risky loans based on huge debts. Those huge debts are expecting to be paid as AI becomes profitable, but AI companies are largely loosing money.
• All those loans and infrastructure create the burden of sunk costs leading to a desperate need to succeed.
• The people feeling that desperation are the same people who own the largest marketing, news, and social media networks in the world.
• As a result, there’s a lot of hype around AI. A lot of “kool-aid,” and everyone wants you to drink it. If you drink the kool-aid, that means you’re also bought into the problem. You also need it to succeed, thus making their problem into your problem.

I explained to him that mature, professional use of AI is going to wind up following a similar path to data engineering. It’ll start with bullshit standards, “prompt engineers” and the like, but eventually SE disciplines are going to define who makes best use of AI. You’re going to have niche use cases for daemon AIs, local LLMs, and remote models. You’ll have stronger frameworks around session management, context management, agent permissions, …

It’s not going to be like this forever, “dump all your shit into our web upload and let the AI figure everything out in one go.” It’s going to become more fragmented, bounded, dare I say deterministic… orchestratable.

Then I told my boss, it would be better if he could frame his excitement around these future use cases… so we can skip the kool-aid stage and get right into the good stuff.

He agreed, until about a week passed. Then it was AI hype again.

Yeah. I’m currently in a situation where we picked up a new hire and she keeps dropping these problems on me. Whenever she runs into something she doesn’t understand, I get a Teams message:

Hi partofthevvvvvvvooooiiiicccceeeeee

It’s happening again 🤦‍♀️

The numbers don’t look right in SLT and the numbers matched yesterday, I don’t know…

They were fine yesterday, then they were all wrong all by themselves. Like magic.

Can you call real quick?

By this point, I’m already fucking irritated and I haven’t even responded yet.

• What do you mean by SLT? What the fuck is that, a dashboard?
• What are you comparing the numbers against to know they’re wrong?
• Did you create a minimal reproducible example in SQL, to demonstrate the issue?
• Did you halfsplit the problem by checking the Bronze tier data for the discrepancy?
• Did you open a ticket?
• And no, no I can’t fucking call. Please type the problem you’re actually having so that I can help you without spending three hours on the phone.

… she proceeds to create the ticket. MRE is a bunch of pseudocode referencing nonexistent tables with footnotes like, “this is the kind of tests we should check.” Oh, but you couldn’t be bothered to write the fucking test?

At a certain point, the ticket just falls into chaos:

• Her: The other team is comparing against their own dashboard, that’s how they know there’s a problem.
• Me: Please get the configuration options necessary to reproduce the calculations in their dashboard.
• Her: Here’s a list of the values they’re using to filter users.
• Me: That list counts 36. Your prior screenshot said the filter has 17 selections.
• Her: Jose said that’s the list of team members. The dashboard filters to team members.
• Me: Okay. I asked for the dashboard filters, not the team members.
• Her: Jose says they’re both the team members.
• Me: …

So after explaining (10x) that, to troubleshoot the dashboards discrepancy, we actually need the filter values from the dashboard… we end up on a 3 hour call, because none of this is fucking landing.

So here I am doing other people’s jobs while I’m already busy enough from my own. I get so burnt out sometimes.

Discipline is part of the recipe for brilliance. So often, I find myself hearing of people’s problems and I realize that the problem is a manifestation of your poor discipline. It’s not necessarily that you did something wrong, misconstrued requirements or misconfigured procedures, no… it’s that you didn’t actually try to read the error message, look at the docs, catalog your technical debt, make a phased rollout plan, decide on what tests you’ll need, write a well bounded scope, … no. These “brilliant” people are fully capable of doing this, they just aren’t disciplined enough

You just stuck your balls to the wall and said “boss, I think it’s cold outside.” How about you go open the fucking door and check?

/s… I got a little carried away there.

IIRC, lime or something like that can be used as a carbon scrubber, but it’s not something that you’d want to do constantly and everywhere. Looked this up some time back.

Oh I’ve got some limes.

Soda lime.

Oh, well I can go get some of that.

Soda lime is a mixture of sodium hydroxide (NaOH) and calcium oxide (CaO).

Oh, so it’s not lime soda. It’s soda lime. Alright then… I’ve got some salt and milk.

best to ventilate to the outside and then run the exchanged air through a counterflow heat exchanger to preserve indoor temperature as much as possible.

Wait, I’m not supposed to drink it?