WordPress opens the door to AI-written sites

WordPress lets AI agents publish content

WordPress is handing publishing controls to AI agents.

The platform now lets AI draft, edit, and publish posts, manage comments, and restructure sites using natural language commands, with human approval required before anything goes live. It already reaches over 43% of the web, with 20 billion monthly page views across its network.

This is a scale shift, not a feature update. When tools like this sit inside the biggest publishing system online, content volume is going to rise fast.

The guardrails are there, but they feel thin if users start approving everything by default. Quality becomes a choice, not a constraint.

You can picture someone clicking approve at midnight, screen glowing. Expect more sites that look maintained but feel empty when you read closely. If most posts are written this way, what still signals a real human behind a site?

Smuggling case exposes weak spots in AI controls

A co-founder is out after an arrest tied to AI chip smuggling.

Super Micro said board member Yih-Shyan Liaw resigned after U.S. prosecutors charged him and others with routing restricted AI servers through Taiwan and Southeast Asia into China. The scheme allegedly involved relabeling hardware with tools as basic as hair dryers to hide serial numbers.

This is less about one company and more about how porous these controls look in practice. If billions of dollars in hardware can move this way, enforcement is still catching up to demand.

The market barely flinched, with shares up 2% after hours despite a 33% drop earlier that day. That tells you investors see this as contained, at least for now.

Think of a warehouse floor late at night, boxes moving, labels swapped. Expect tighter scrutiny across the AI supply chain, especially around intermediaries and contractors. How many similar routes are still running quietly?

AI is making geothermal easier to find

The industry says it found more sites in 3 years than the previous 30.

Geothermal energy has always been there, but companies struggled to locate viable spots and wasted money drilling bad wells. Now firms like Zanskar are using AI models to map underground heat and guide drilling with more precision.

This feels less like a breakthrough and more like overdue tooling catching up to a known resource. The real shift is cost and confidence, since fewer failed wells change the economics fast.

Permitting still takes three to seven years, though recent policy moves aim to speed that up, especially on federal land in the western U.S. The grid question is still hanging, since AI demand is rising at the same time new supply is being figured out.

Picture drilling rigs in dry heat at noon. If AI keeps reducing guesswork, geothermal could move from niche to steady baseload power. What happens when the cheapest clean energy is the one we ignored for decades?

Prohuman team

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