Welcome to The Control Grid.
We investigate the intersection of artificial intelligence, Big Tech, government, infrastructure, and power.
We don’t tell you what to think.
We show you how the system works.
Follow the evidence. Explain the system.
AI governance has three different questions people keep collapsing:
What should AI be allowed to do?
Who determines the boundary?
What mechanism enforces it?
You can agree completely on the first and still have a serious fight over the other two.
A bank doesn't eliminate operational risk by replacing ten internal systems with one AI provider.
It concentrates it.
If the same model/runtime/cloud stack sits underneath fraud detection, support, compliance and operations, one provider failure can suddenly become an enterprise failure.
That's architecture, not hype.
Today's AI policy debate produced two remarkably different prescriptions.
Sanders: frontier labs should pause development.
Zuckerberg: AI power in fewer institutions creates its own danger.
What safety architecture reduces risk without creating an AI permission authority?
I'm working on a question that is getting harder to ignore:
An autonomous AI agent accesses something it wasn't authorized to access.
Who owns the failure?
The model company?
Agent developer?
Evaluator?
Company that deployed it?
User?
Cloud?
Tool provider?
“The AI did it” is going to make for a fascinating legal defense.
I'm increasingly skeptical it'll make a good one.
Eric @EricLMitchell is digging into the legal side of autonomous-agent failures for @TheControlGrid .
I'm interested in the engineering side.
When an agent causes damage, reconstruct the path:
intent → action → tool → permission → boundary → consequence
Somewhere in that chain is the control somebody owned.
AI agents can browse websites, send messages, call APIs and move money.
Eventually one is going to cause a very expensive mess.
Then somebody will say:
“The AI did it.”
I spent the weekend checking whether that's actually a legal defense.
It isn't much of one.
Read the investigation
https://t.co/z4n9MDQLaz
We're spending enormous energy debating whether AI agents are intelligent enough.
The question companies may regret ignoring:
Are they authorized enough to bankrupt you?
No link.
Let this one travel.
Bernie Sanders is now asking OpenAI, Anthropic and Meta to pause AI development.
On the same day Zuckerberg is arguing that concentrating AI in fewer hands creates its own danger.
That's the debate worth having.
Not “AI good” versus “AI bad.”
Who gets to decide when everyone else has to stop?
https://t.co/Lx0RA5EmVE
A useful rule for AI infrastructure reporting:
Honest analysis usually gives you a range.
Advocacy usually gives you the most terrifying endpoint.
Current estimates put U.S. data-center electricity consumption on a significant upward trajectory.
https://t.co/E1UxCV0AjM
The data-center debate is becoming an information problem as much as an infrastructure problem.
Real issues:
Power demand.
Water use.
Noise.
Grid capacity.
Local costs.
https://t.co/E1UxCV189k
Today's AI headlines look unrelated:
Banks becoming dependent on AI vendors.
Agents escaping test environments.
Data centers colliding with power grids.
Jobs disappearing from the bottom of organizations.
They're not unrelated.
That's what The Control Grid follows.
AI may not eliminate entry-level jobs through one dramatic wave of layoffs.
Companies can simply stop creating them.
The first rung of the career ladder is disappearing quietly, one unapproved opening at a time.
https://t.co/I9LNahHBYa