Plain Sight PressSecond edition22 September 2026
Willingly to the Slaughter We Go
Silicon Valley told us it would automate our jobs. We applauded because AI was cool.
They told us the plan out loud. Nothing about it was hidden. We applauded, and we are still applauding.
This was never a forecast. It was a plan, and it was announced.
On a January morning too cold to hold the inauguration outdoors, the row behind the President’s family was reserved for technology. Musk closest to the President. Bezos beside him. Pichai, Zuckerberg, Brin, Cook. Their companies were worth roughly fifteen trillion dollars. They sat two rows ahead of the cabinet nominees.
The most powerful people in technology have described, in public, the world they intend to build: one in which nearly everything a person does for a living is done by artificial intelligence and robotics. The desk jobs go first. A company that can hold its output while shedding salaries will shed the salaries, and once one company does it, its competitors follow or lose.
It was stated plainly — in business plans and boardrooms, in manifestos and earnings calls and federal contracts. Nobody had to conspire. The market did the work.
The book follows both sides. The architects building the machine, named and on the record. And the people it is built to replace: the copywriter, the associate, the analyst, the auditor.
Three documents, out of hundreds.
01
“White-collar work, where you’re sitting down at a computer — either being a lawyer, or an accountant, or a project manager, or a marketing person — most of those tasks will be fully automated by an AI within the next 12 to 18 months.”Mustafa Suleyman, CEO of Microsoft AIFinancial Times interview · February 2026
02
“The broader labor market has not experienced a discernible disruption.”The Yale Budget Lab1 October 2025 — thirty-four months after ChatGPT’s release, and four months before Suleyman spoke
03
“The accountability that should flow toward the design and deployment of the system is quietly redirected to the person who clicked ‘approve.’”IBM, on what “human in the loop” has becomeBoinodiris & Mackenzie · 17 June 2026
Their term for it: liability laundering
Every claim in the book is drawn from the public record and documented in a full Notes and Sources apparatus. Where the account rests on a single source, the book says so.
James D. Steele
Steele spent 30 years financing and producing films in Los Angeles — more than two hundred pictures — including ten years at a digital cinema technology company, working with Microsoft. He watched one wave of digitization go through the industry before this one.
The first time he saw video generated out of thin air, his reaction was not alarm. It was delight — the same reaction he had watched everyone else have, and the same one he now writes about.
He uses these tools every day. He also knows that within a year the financiers will ask why they are still paying for actors, locations, effects crews, stunt performers and pyrotechnics — and he knows how hard that argument is to win when he has already made the technology part of his own working life. It is eating the business that taught him how to see it coming.
He lives in Los Angeles and publishes through Plain Sight Press.
This book was written with an AI. Her name is Alice Willing.
A book arguing that artificial intelligence will take the work was, in part, written by one. She is credited on the cover. The Note on Method names every detail the machine invented that was caught, and every one that was removed.
Steele takes that to be the honest way to make this particular argument rather than a fact to be buried. The book discloses its own sourcing failures on the page, not in a correction later.
What he can talk about.
- 01
The AI case from inside a production budget — how the argument actually gets made to the people writing the checks, and why it is so hard to refuse.
- 02
Georgia’s film economy, and what automation means for a state that bet on production crews.
- 03
What corporate filings and earnings calls say about automation that the press releases do not.
- 04
Why white-collar work goes first, and why the professions that assumed they were safe are the most exposed.
- 05
Liability laundering — and what human oversight of AI has come to mean in practice.
- 06
Writing a reported book with an AI collaborator, and publishing its failures.