Fear and Loathing in the Gas Town

The $47 Tuesday

I woke up with a forty-seven-dollar cloud bill. For a Tuesday. A single, unremarkable Tuesday. One agent. One night. Scale that to a squad running all week and the number gets a fifth digit. Nobody signed a purchase order.

The model had been running overnight – a stochastic parrot with a credit card and no supervision, like handing a flamethrower to a golden retriever and calling it a fire department – and somewhere between 2 AM and sunrise, it decided to refactor a module that didn't need refactoring. Three times. Then it wrote tests for the refactored code. Then it refactored the tests.

Nobody asked it to. Nobody was watching.

Nobody was in command.

Welcome to 2026. Pull up a chair. The hangover is spectacular.

The Binge

Remember when resources were cheap?

I do. It feels like remembering a different civilization.

You'd spin up an instance, glance at the pricing tier, pick the next size up because, honestly, what's the difference? Fifteen cents an hour, thirty cents, who's counting. The email client weighs a gigabyte? Fine. Two? Sure. Five? Why not. Memory is cheap. Compute is inexpensive. Electricity is someone else's problem.

We stopped counting clock cycles. We stopped counting bytes. We stopped counting anything at all. More. Fatter. Hungrier. The mantra of an industry drunk on Moore’s law and someone else's power bill.

It was a good binge. I'll give us that. We built extraordinary things while wasted on cheap resources. Cloud platforms. Real-time collaboration. Models that pass a bar exam.

But here's the thing about binges.

They end.

The Morning After

If this were a patient, the chart would read: technically alive, spiritually bankrupt, insurance expired 2024.

History does this thing where it spirals. We went from counting every byte on a punch card to wasting terabytes on Electron apps wrapped around a text field, and now - full circle - we're counting again.

Except the units changed. We're not counting bytes anymore. We're counting kilowatts. Tokens. The humans who actually understand what the hell is happening.

One data center now drinks power like a small city. So that a model - trained on our data, public and not-so-public - can generate as much AI-slop as inhumanly possible. Slop it's a code generated by default, reviewed by nobody, deployed on faith. Code that will itself consume the resources we no longer have. Which will require more compute to manage. Which will eat more power. Which will...

You see where this goes.

The snake found its tail. The snake is eating well.

His Majesty, Context

Here's the pitch from the hype barkers – the conference-circuit prophets who couldn't deploy a todo app without three wrappers and a prayer: "Don't worry about code quality. Just feed it back into the model. The model will sort it out."

No. The model will not sort it out. Especially if it's anything more complex than that notorious todo app.

The model is the problem wearing a solution's uniform.

Because into the equation walks His Majesty: Context. The invisible constraint nobody warned you about.

We now fight not only for cycles and memory, but for something far stranger – the attention span of a stochastic parrot with a 200K token window and the long-term memory of a goldfish. Context windows. Hallucination rates. Prompt hygiene. Output entropy.

We traded one set of engineering constraints for another. Except this set is weirder, harder to measure, and nobody wrote the textbook yet because the textbook would be outdated before the ink dried.

And this - this - is where good engineers enter the picture. The ones who can hold all of it in their head at once. Resources, context, hallucination risk, output quality, cost per token, cost per mistake. The ones who think about it on the shore, before the current pulls them into the sewer and they're screaming for mama.

They are in short supply. See the table above. Last row.

The Dream

Pause. Breathe. Ask yourself honestly.

Wouldn't you kill for a virtual army of engineers? Your own squad. Ones that do exactly what you need, exactly how you need it. Clean code. Reliable deploys. Fast iterations. Economical with resources. Maintainable at 3 AM six months later.

No arguments. No "I'll refactor this later." No "works on my machine." No vanishing for two weeks into a rabbit hole that produces a framework nobody asked for.

Every engineer alive is a secret architect. In our souls, we're all grander than the Wachowskis, with a cathedral-grade vision of how the system should work. The perfect codebase. The perfect pipeline. The perfect abstraction.

But.

The Meat Problem

Reality is meat.

You're a piece of meat surrounded by other pieces of meat, each with their own priorities, their own bad Tuesday, their own interpretation of "done." If something matters to you – it might not matter to them. Not out of malice. Out of meat.

That's why the industry hunts for mythical senior engineers. The ones who – alone, or maybe with one partner if the stars align and neither quits in six months – will carry an entire department. Whole companies run on the shoulders of two people who happen to care about the same things at the same time.

How many times have you told yourself: this project – this one – I'll do right. Start to finish. My way. Everything will be clean. Everything will work. Everything will be–

A blocker. Someone's sick, ship it fast. "We'll rewrite later." "Fine, leave it."

Frankenstein. Again. You wanted the best. You got the usual.

This is not a failure of technology. This is optimism mistaken for a plan.

You can't build the cathedral from meat. You need builders with a statute, not a mood.

Chaos

Chaos chaos chaos.

I've been writing software for longer than I care to admit. I've watched patterns come and go. Waterfall, agile, microservices, monoliths again, serverless, server–more, AI–first, AI–who–cares. Each time, the promise: this will bring order.

Each time: new chaos with a fancier name.

Somewhere in a co–working space, a man in a Patagonia vest is writing a blog post about how this time it's different. It is always different. It is never better.

But.

The Turn

Here's where I lean forward and drop my voice.

There is something different about this particular moment. Not because the technology is better – it's always "better." What's different is the pressure. The resource table above isn't a warning. It's a fact. We cannot keep generating slop and hoping the next model will clean it up. We cannot keep throwing hardware at software problems when the hardware isn't there.

The constraints are back. And constraints – real ones, the kind that don't go away when you throw money – are where engineering actually happens.

From chaos, order.

Not the accidental kind. Not "it'll sort itself out eventually." The deliberate kind. The kind where someone surveys the field from the hilltop, counts the sheep, and says: enough. You're soldiers now. Here are your rules of engagement.

I'm building something. Five components. A name. A philosophy that doesn't fit in a tweet but fits perfectly in a statute.

The sheep have a codex. The system has an eye.

But before anything else - before rules, before architecture, before the first soldier receives its orders – you need to see. Every token. Every decision. Every cost. Every failure.

You cannot command what you cannot see.

Next dispatch: The Eye.

About the author

Building the system. Writing the field manual.

Shepard