The AI world is moving fast today — and it's not just about bigger models or flashier demos. We're seeing something more interesting: AI tools becoming genuinely useful for real work, from Hollywood productions to niche theater applications.

AI Video Generation: The Race Heats Up

xAI just shook up the video generation landscape with Grok Imagine. The model debuted at number one on Artificial Analysis rankings for both text and image-to-video outputs. But here's the kicker — it's priced at four dollars and twenty cents per minute, compared to Veo's twelve dollars and Sora's thirty dollars.

That pricing isn't just aggressive — it's potentially market-changing. When you can iterate on video concepts at a quarter of the cost, suddenly creative workflows look very different.

Meanwhile, Google opened Project Genie to the public. This isn't just another video generator — it's a world simulator. Users create explorable environments where characters can walk, fly, or drive through AI-generated spaces. The model remembers what it builds, so returning to areas stays visually consistent.

The catch? Sessions are capped at sixty seconds due to compute costs. Each user gets a dedicated chip while exploring. It's currently limited to Google's AI Ultra subscribers at two hundred fifty dollars per month.

AI Enters Real Production Workflows

Here's where things get interesting. Filmmaker Darren Aronofsky's studio Primordial Soup just released "On This Day… 1776" — a Revolutionary War series created entirely with AI visuals. Each episode drops on the two hundred fiftieth anniversary of the historical event it depicts.

This isn't experimental art-house content. It's running on TIME's YouTube channel with professional voice actors and real production values. AI video is moving from hidden tricks to handling entire visual processes in legitimate studio workflows.

The Practical Programming Revolution

But perhaps the most compelling story comes from an unexpected source. Chris Ashworth, creator of QLab — software that automates lighting and audio for live theater — had his Claude moment recently.

Ashworth has been skeptical of AI for two years. Every time he checked, he found it garbage. But he recently used Claude to build a custom lighting design application for a niche project. Something that would serve maybe three people total.

Here's his insight: "It can take a person who is a bad programmer and make them faster at making bad programs. And it can take a person who is a good programmer and make them faster at making good programs."

The key difference? Understanding and directing the code it produces. Ashworth is terrified by programmers shipping code they haven't looked at. But when you can review, edit, and quality-control AI output, it becomes a powerful force multiplier.

His lighting app took just a few days to build. As a professional programmer, he would never have allocated weeks to serve three users. But with AI assistance, suddenly those niche applications become viable.

Simon Willison echoes this theme in his latest Datasette release. The new alpha includes support for multipart file uploads and improved development workflows using uv — Python's new package manager. These aren't flashy features, but they're the kind of practical improvements that compound over time.

The pattern is clear. AI isn't just about generating content anymore. It's becoming a tool that makes previously uneconomical projects suddenly viable. Whether that's custom theater software for three users or professional video series on historical topics, the economics of creation are shifting in fascinating ways.