Welcome, humans.

Most of you know us for this newsletter. Fewer of you know we also built The Neuron Academy, an AI training site with short, beginner-friendly courses on the stuff you actually do at work: writing better prompts, getting more out of ChatGPT, Claude, and Gemini, and automating repetitive tasks. Each lesson takes about 15 minutes, and you don’t need a technical background.

Before we tell you it’s good, we figured we’d let someone else say it. We opened the Academy early to a select group of Neuron subscribers and asked them to help us build it.

Here’s what Christine E., one of those members, told us:

(Grant and Corey are reading this over each other’s shoulders right now. Neither is humble about it.)

Readers like you, building something for readers like you. Come see what they helped shape at The Neuron Academy.

Here’s what happened in AI today:

…and a whole lot more that you can read about here.

Got a Black Friday or Cyber Monday deal too good to keep to yourself?  We’re rounding up offers for a special Black Friday edition of The Neuron, and your brand could snag a sponsored spot. Reach out for details!

😻 Google's Genie 4 builds AI worlds you can control (with sound)

Imagine asking AI for a snowy mountain, stepping into it, hearing the wind, then saying "add a dragon."

That's what Google DeepMind is chasing with Genie 4, its new AI world model. Instead of a video you watch, you explore a world that changes as you move through it. And this time, it comes with sound.

First, what's a world model? Most AI video tools generate a clip, and you sit back and watch. A world model simulates an environment that responds to your actions. It's the difference between watching someone walk through a forest and playing a game where you pick the path. Turn left, and the scene should change. Walk around a rock, and it should still be there.

Here's what Google says Genie 4 can do:

That last one might matter most. Google says Gemini 3.8 Flash can act as a guide: it watches what happens, decides what should happen next, and instructs Genie to keep the simulation on track.

Picture a robot practicing how to pick up objects in a simulated kitchen. Gemini checks the result after each step and adjusts the plan. That could let AI train on situations it hasn't seen in real life.

Basically, Google wants robots to make their mistakes in a fake kitchen instead of yours.

The uses go beyond gaming. Filmmakers could preview virtual sets before spending a dime on production. Game developers could test levels before building them by hand. Google has even paired Genie 4 with its Gemini robotics research to simulate a humanoid robot playing checkers.

Here's the catch: Genie 4 is still a research preview. Google admits objects, physics, and spatial details can get inconsistent, especially in longer sessions. Access is limited to trusted testers for now, with Google AI Ultra subscribers (via Project Genie) and select Gemini API and AI Studio partners next.

So this isn't a perfect simulator of reality. It's a shift from AI that makes finished media to AI that makes interactive experiences.

What we're watching: whether Genie keeps the same objects, rules, and consequences over longer sessions. A pretty two-minute world is cool. One reliable enough to train a robot for your house is the real breakthrough.

Watch Google's Genie 4 demos

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🎓 AI Skill of the Day: Find out why your project keeps slipping

You know that project that's been "almost done" for three weeks? Everyone's busy, the meetings keep happening, and the deadline keeps moving.

Atlassian's 2026 State of Teams report found that 87% of surveyed knowledge workers said they lacked time or capacity to coordinate while everyone was busy executing. Reviews, signoffs, and handoffs can pile up even when individual tasks move faster. Atlassian's dependency-mapping playbook shows how to trace who is waiting on whom, identify risks, assign owners, and set a review schedule. It includes a worksheet you can use to check the AI-generated map against your team's actual responsibilities.

The real blocker is probably buried across meeting notes, Slack threads, and your project tracker. The trick is to run a few connected AI checks instead of asking one chatbot to diagnose your team.

Here's the workflow:

After your next check-in, run the comparison again. You'll see which blockers disappeared, which remain, and whether your fixes worked.

Congratulations, you've turned "let's circle back" into an actual investigation.

Have a specific skill you want to learn? Request it here.

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📰 Around the Horn

Want absolutely EVERYTHING that happened in AI this week? Click here!

🍪 Treats to Try

*Asterisk = from our partners (only the first one!). Advertise to 700K+ readers here!

UPCOMING EVENT: The Neuron IRL in San Francisco

The Neuron is going IRL on November 18 at 4:30 PM PT! Join us in San Francisco for drinks, bites, special guests, and a live recording of The Neuron podcast. Huge thanks to Slack and Alumni Ventures for making it happen.

It’s free, but space is limited. Save your spot!

📖 Midweek Wisdom

Getting AI to finish a task faster is one thing. Knowing whether it makes you better at your job is another. Today's reads tackle the second part.

Our favorite question from all five: are we measuring AI by how much work it produces, or by how much better that work makes us? Those aren't always the same thing.

New from The Neuron: AI Explained

New episodes air every week on Wednesdays: Spotify | Apple Podcasts | YouTube

A Cat’s Commentary

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