“A significantly smaller team, using the tools we’re building, can do more and do it better.”

– Jack Dorsey, announcing 4,000 layoffs at Block, February 2026

Everyone agrees: AI is coming for the developers. The $200,000-a-year engineers writing CRUD apps and maintaining CI pipelines. The line workers of the knowledge economy. Trim them. Automate them. Celebrate the efficiency gains. Watch the stock pop.

Nobody asks the obvious question.

Why is nobody coming for the CEO?

Meet the A-suite. AI replaces the CEO. The AI Executive Officer (AEO) is the human who operates alongside it. The rest of the C-suite becomes the A-suite (AxOs).

The Math

Median S&P 500 CEO total compensation in 2024 was $17.1 million. That is 85 senior software engineers. One person. One salary. Eighty-five engineers worth of payroll.

But salary is the small number. The real cost of a CEO is what happens when they are wrong.

Jack Dorsey tripled Block’s headcount from roughly 3,900 to over 12,000 between 2019 and 2022. The stock peaked above $275 in 2021 and has since dropped over 75%. He built two separate company structures for Square and Cash App instead of one, a decision he now calls incorrect. He spent $68.1 million on a single company event in September 2025. Five months later, he cut 4,000 people and blamed AI.

None of that is an AI story. All of it is a management story.

The Efficiency Standard That Stops at the Top

Dorsey is not unique. He is just the most recent example of a pattern the industry refuses to examine: the efficiency standard always flows downward.

When a company deploys AI to replace developers, the pitch is simple. These tools can do what humans do, faster and cheaper. How about applying that logic upward?

A CEO sets strategy, allocates capital, communicates with stakeholders, makes high-stakes decisions under uncertainty, projects confidence, and takes credit when things work. Most of that reduces to pattern recognition, modeling, and communication, all of which AI already handles with less ego and fewer pet projects.

The one function that genuinely requires human judgment is choosing between futures you cannot model. That happens a few times a year. The rest is coordination and calendar management. You do not need a $17 million executive for that. You need an AI with good models and a small team of AxOs who can execute.

The Blast Radius Problem

When a developer writes bad code, the blast radius is a feature, maybe a service, maybe an outage that lasts hours. We have spent decades building infrastructure to make individual developer failure survivable. Code review, CI pipelines, staged deploys, automated rollback. The entire modern engineering stack exists to contain the damage of any single human decision.

When a CEO makes a bad decision, no such system exists. The blast radius is the entire company. Years of engineering capacity consumed. Billions in shareholder value destroyed. Thousands of jobs lost. The failure is in command, and there is no rollback mechanism for command.

We build elaborate systems to contain the mistakes of $200,000 engineers. We build nothing to contain the mistakes of $17 million executives.

So let’s build something.

What This Looks Like in Practice

An AI system handles strategy synthesis, capital allocation modeling, performance monitoring, stakeholder reporting, and operational coordination. It processes information continuously, without ego, without pet projects, without the need to justify its own existence through activity.

The A-suite works alongside it. AxOs are the humans who replaced the C-suite. Same caliber of person, different relationship to power. They handle what the AI cannot: relationship judgment, regulatory navigation, crisis decisions that require a human face, and the handful of annual choices where genuine uncertainty demands human intuition.

Total cost: maybe $3 million fully loaded for the A-suite. That is $14 million in annual savings against the median CEO package alone, and significantly more when you account for the C-suite ecosystem it replaces. Replace the decision-maker with a system, and the entire executive layer simplifies with it.

The Self-Protecting System

The people who would need to approve this change are the ones being replaced.

CEOs set strategy. Boards approve CEO compensation. Boards are populated by current and former CEOs. The entire governance structure exists to perpetuate itself, and every stakeholder around it has a reason to play along. Consultants need executive engagement. Analysts need access. The financial press needs CEO narratives to drive clicks.

The AI-replaces-developers story persists because developers do not control the narrative. They do not sit on boards. They do not write shareholder letters. They do not go on CNBC. The people who control the conversation about who gets automated will never volunteer themselves.

The BoringOps Lens

BoringOps exists to ask one question: where is the actual drag on your organization?

Every layer produces friction. Engineers write bad code. Infrastructure drifts. Processes decay. Those problems are real, and they compound. But the decisions that create the most expensive, hardest-to-reverse damage originate at the top: decisions to triple headcount without discipline, to adopt complexity without justification, to build empires instead of systems.

If AI is powerful enough to eliminate 4,000 engineers, why is it not powerful enough to challenge one executive?

boring (adj.): Applying the same efficiency logic to executive compensation that leadership is so eager to apply to everyone else.