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Daily one-pagers about AI, leadership, technology, and being human.

johnmaconline

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October 1, 2026 2 minute read

The Death of the Software Laborer (The Resurrection)

AIHumanTechnology

We generally don’t need thousands of people with shovels anymore.

But that doesn’t mean we don’t need those thousands of people. We just scaled them up and across the stack of work. Now need them to

  • operate the machines
  • survey and lay out the work
  • install pipe, conduit, drainage, rebar, forms, and concrete
  • weld, wire, assemble, and finish
  • maintain and repair equipment
  • inspect quality and safety
  • coordinate crews, materials, and sequencing
  • handle the awkward, irregular work machines are bad at
  • make decisions when reality doesn’t match the plan

The excavator doesn’t decide where it should dig a hole. Nor does it decide what you should put in the hole. Nor why it’s digging a hole. It just digs.

We do need far fewer people per unit of output, but we can produce so much more output. For a job that required 100 people with shovels, today you might need 10 split across the various roles.

And then you can do 10 more jobs at the same time.

AI is the excavator.

We generally don’t need thousands of people typing code into their code editors for a particular project. But that doesn’t mean we don’t need those software engineers. We need our engineers to decide what to build, how it should work, how the pieces fit together, whether it is correct, and what to do when it isn’t.

We don’t need software engineers to write the code.

But boy, do we still need software engineers.

September 30, 2026 2 minute read

The Death of the Software Laborer (The Funeral)

AIHumanTechnology

Each day from 1817 to 1825, across northern New York, 9000 men showed up with their shovels and lunch pails to dig the Erie Canal.

The 363-mile canal crossed New York State from the Hudson River to Lake Erie, spanning 40 feet wide and 4 feet deep with 83 locks. Thousands of laborers with picks, shovels, wheelbarrows, horses, and carts moved the dirt a little bit at a time.

Dug by hand. Men with shovels.

Some were better and faster than others, and that mattered for any specific work crew, but at the project level, a laborer was a laborer.

Need to move more dirt a little faster?

Hire more people with shovels.

But now we have excavators, dump trucks, and tunnel boring machines. What took 8 years could be done in about 18 months today with a few operators and a healthy fuel budget. And those operators bring their lunch pails right into the cabs with them.

Nobody hires a guy with a shovel anymore.

From the beginning of the software industry until today, the same has been true for writing code. Men and women showed up each day with their keyboards and lunch pails to type the code into the machine.

Like the big, strong guy on your work crew, some coders were much better than others, and that mattered for your specific project. But at a large scale, a coder was a coder.

But now we have AI. AI is the excavator, dump truck, and tunnel boring machine.

What took four programmers two weeks to code, test, and fix can now be done before lunch with a few agents and a healthy token budget. Now those coders can eat their lunch while the agents are building the things.

Start the soft music. Put the montage together. Stand the lectern up at the front of the room.

The programmer’s career is in the casket.

September 29, 2026 1 minute read

Robots on the Fasion Runway

AITechnologyThe250

Formless AI is here to stay.

But what about AI-powerd robots?

Sure, we’re worried about Skynet, but Elon’s got Optimus cooking and you can choose from a whole bevy of humanoid personal assistants at the Robostore (the G1 is 17% off right now!). They’re coming.

For some reason we’re building robots that either look robots, or look like women. OK, I guess you don’t have to think too hard about that.

But Vogue pushed the genre forward by sending them down the runway. I guess it didn’t go over well.

The robots are coming, but it’s too soon for the fashion runway.

September 28, 2026 1 minute read

Luddites

AIHumanTechnology

People generally don’t identify as luddites.

We don’t want to be the old guy. We don’t want to be our out-of-touch parents, the crotchety neighbor, or the coworker at the end of his career just trying to ride it out.

Yet, here we are.

AI is an accelerator. It also appears to be accelerating the pool of luddites.

Let’s keep talking. Let’s keep debating. Let’s keep pushing and pulling.

But let’s not stop building.

September 27, 2026 1 minute read

More BS College Ranking Shenanigans

HumanThe250

US News & World Report flipped the script, and it screwed Princeton.

This year’s rankings put MIT at the top. I’m sure the person in charge of this at Princeton is seething because USNWR pushed a methodology change.

This year’s rankings introduced a criterion comparing graduates’ earnings by major four years after college with those who studied the same major nationwide. The measure includes only federal financial aid recipients, part of an effort to minimize the impact preexisting wealth and family connections could have on post-college earnings. It replaces a metric that measured graduates’ federal loan debt.

How dare they.

We should all be very upset.

Oh, right. None of this matters. No rankings list that is fundamentally for-profit, provides its criteria publicly with a wink, and simply asks the institutions to “self-report” on that criteria should matter one iota to you.

Not one neuron operation in your brain should be spent on this list.

Don’t worry, Princeton, you can self-report the proper data next year.

September 26, 2026 1 minute read

Eyes on the Incentives

AIHumanTechnology

Lots of doomsdaying around AI recently. The accelerationist versus doomer wars are heating up.

Dario from Anthropic has always been a doomer, but now his foil Sam, has joined in. Elon has always kinda been a doomer, but then sometimes he just flips to the accelerationist side.

There’s not a clean political split. The left tends towards doomerism. The right tends towards accelerationism. But it’s way more complicated.

What’s really going on?

It’s incentives. Like always.

It’s possible that Dario and Sam are legit in their public worrying. That their incentives are human-focused. But it’s also possible that Anthropic and OpenAI will benefit from a slowdown. From some regulation (that they help create).

Honestly, I don’t know which it is.

But I know I’ll keep my eye on the incentives.

September 25, 2026 2 minute read

Leading AI

AILeadershipTechnology

The current token budgets are untenable.

Or you could say the rate at which the new models use tokens is untenable.

With the standard ChatGPT business account, I can work for about an hour until my 5-hour budget is totally blown. And that’s not even using the frontier model Astra. That’s with the (now old) Terra at medium context. With Astra, its more like 20 minutes.

Work for an hour, then wait four more until my 5-hour budget resets. Then do it again.

So that’s two hours of work. Three if I spread it out across another 5-hour window.

You can’t take off working like this.

What are your options?

  • More tokens. You can always throw money at the problem.
  • Get better at which model to use for what task. You should do this anyway. It helps, but it only takes you so far.
  • Break jobs into smaller tasks. Context costs tokens. Less context, less tokens.
  • Avoid duplication. Models, especially when you have multiple agents running. If you don’t manage what each is doing, they’re probably each rereading all of the same context.
  • Build efficient, AI-readable memory storage. If you cut down what the model needs to read to understand, you use less tokens. This goes hand-in-hand with the one above.
  • Build deterministic software tools to perform much of the work. Use the AI to generate reusable code, rather than asking it to continually use a model to do the same work over and over. This is software development 101. Write code.
  • Do more yourself. Duh.
  • Ask better questions. Give better instructions.

When you look at this list, it looks a lot like what a good manager does with his/her team.

Once again it comes down to being a good leader.

In some ways (not all ways), leading AI isn’t much different from leading people.

September 24, 2026 2 minute read

Baggage Handling the Code

AITechnologyThe250

Think about the baggage system at an airport.

You hand over your bag and care about two things:

  • It shows up when you do.
  • It isn’t damaged.

Then it disappears behind a wall. Literally.

You might think about it a little bit. A little trepidation. A little mistrust. Probably based on some personal experience. But generally, you don’t care what’s behind that wall. You don’t care about its efficiency. Whether people or machines handled it. You don’t care if it’s a clever design. You don’t care about any of the implementation.

You care that the bag shows up when you do and it’s not damaged.

Code is starting to look the same.

For years, code was expensive. Humans had to design it, write it, debug it, explain it, and maintain it. We crafted it. We showed each other lines, functions, and modules we were proud of. So we treated code as the product, and we cared deeply about it.

AI changes that.

Which is uncomfortable for programmers.

When AI can generate the implementation in minutes, the code itself becomes less scarce. Each line is less important. Each elegantly crafted logic path is less important. Each minimal and efficient function is less important.

What is still important?

Function and correctness.

Did it show up when you did, and did it damage anything?

AI baggage handles the code.

So what will you do?

September 23, 2026 2 minute read

Factory and Craftsman

AIHumanTechnology

What’s the difference between a cabinet made on an assembly line in a factory and one made by the cabinet maker down the street in his shop?

Maybe you’re thinking quality.

It’s not quality.

A good factory can make cabinets with high-quality materials and superbly consistent dimensions and finish. A mediocre cabinet maker can make a lousy cabinet with cheap materials and bad finish.

Maybe you’re thinking personal service or customer care.

It’s not personal service.

A factory with excellent people in customer service, including installation contractors, can provide an outstanding and personalized experience. An uncaring cabinet maker down the street can make you wish you’d hired anybody else.

The difference is where the craft mentality resides.

A factory cabinet has most of the crafting done before manufacturing begins. A person has already decided the dimensions, materials, joints, tolerances, hardware, finish, and assembly sequence. The factory optimizes its manufacturing to reproduce that design consistently, quickly, and cheaply.

A cabinet maker down the street moves much of that crafting into the act of building. He can look at your crooked wall, change a dimension, choose a different joint, compensate for unusual conditions, and make judgments as the work progresses all the way through installation.

Where does AI fit?

AI is the tool, not the factory or the cabinet maker. It’s the CAD package, ruler, and calculator. It’s the supply chain management engine. It’s the design verifier. It’s the “what-if” analyzer. It’s the

Craftsmanship has little dependence on whether the thing came from a factory or from a person whose name you know.

AI doesn’t change that.

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