Welcome to Something Big.

Hi, it’s Matt.

A few months ago, I wrote an essay called Something Big Is Happening.

Maybe you were one of the millions who read it. Maybe a friend forwarded it to your inbox, or it showed up on your feed. Maybe you opened it on your phone just to kill two minutes, and twenty minutes later you were sitting there with a knot in your stomach, staring at the wall.

When I wrote it, I wasn’t trying to go viral.

I’d been working in the AI industry since 2019, watching the technology improve rapidly. But earlier this year, we crossed a threshold.

The pace of progress accelerated so fast that my own job changed completely in the span of months. When I went home to visit my parents, I tried to explain it to my dad, but I caught myself giving him the polite, watered-down version of what was happening. Because the honest version made me sound like I had lost my mind.

My dad is a lawyer. He’s a smart guy, but he shouldn’t need a technical degree just to understand how radically white-collar work is about to change. I wanted to find an article someone else had written to send him, but Silicon Valley has an obsession with sounding smart. Everything was buried in impenetrable jargon or breathless PR fluff. Nobody was telling normal people the raw, plain truth.

So that night, I sat down and wrote what was actually happening.

I sent it to a few friends for feedback, and shared the link on X, thinking other people might find it interesting. I thought a few hundred people might read it.

Within weeks, over 100 million people read it.

My inbox exploded. I received tens of thousands of messages from lawyers, accountants, radiologists, teachers, CEOs, and parents, telling me: “I couldn’t sleep last night.” “I showed this to my entire executive team.” “I finally understand what’s happening, and I’m terrified I’m already behind.”

And then came the question that followed almost every message:

“What do I actually do now?”

Here’s the truth:

Since the essay came out, the technology hasn’t slowed down. It has accelerated.

The models we thought were mind-blowing six months ago already look like toys compared to what’s coming out of the labs today. The feedback loop (where AI helps train the next, smarter AI) is actively spinning.

The gap between what is happening behind closed doors at OpenAI and Anthropic, and what the public understands, has never been wider.

Most people outside of tech are still in the denial phase. They use a free chatbot once, watch it make a stupid mistake, and laugh it off. They think they have five to ten years to figure this out.

They don’t.

The disruption that wiped out the technical requirements of my job over the last year is about to roll through law, finance, consulting, medicine, media, and corporate strategy. It doesn’t care how senior your title is. If your work happens on a screen, the baseline of what a single human can do is being rewritten right now.

That is why I created Something Big.

To be your unfair advantage.

I spend every day building with these models, breaking them, testing frontier tools before they go public, and talking directly with the people building them.

Every week, I’m going to cut straight through the noise. You’ll get an honest answer on which breakthroughs actually matter, the step-by-step workflows people are using right now to 10x their output, and an early look at what’s coming next so you’re never left playing catch-up.

My rule for every single issue is simple: It must be clear enough for my dad to understand immediately, and powerful enough that a frontier AI researcher still learns something.

Because today’s biggest AI announcement will be replaced by another one next week. Keeping up with the headlines isn’t enough. What matters is learning to recognize the larger shifts before their consequences become obvious to everyone else.

Six months from now, when the people around you are trying to make sense of the latest breakthrough, you won’t be scrambling to catch up.

You’ll already understand what it means.

And you’ll be the person they ask.

I never expected to write an AI newsletter. I’m a builder and founder at heart. But after months of trying to answer more questions than I could fit into a television segment or a post on X, I realized this may be the most useful thing I can build.

Something Big is Happening.

Let’s make sure you’re ready for it.

— Matt

P.S. One thing you should know about me: sometimes I’m going to say things here that sound a little crazy. That’s okay. I’ve spent the last seven years very close to this technology, and I’ve learned that the things that sound like science fiction have a strange habit of becoming normal surprisingly quickly. If you ever think I’ve lost it, look back at the things I’ve said publicly over the years. I haven’t been right about everything, but I think you’ll find I’m usually worth hearing out.

An AI just got someone fired.

Here’s what that means for you.

Earlier this year, a research startup called Andon Labs gave an AI named Luna $100,000, a corporate credit card, internet access, and a three-year lease on a storefront in San Francisco.

Then they told it to open a store and make money.

The brand, the products, the prices, the hours and the employees were all decided by Luna.

One of those employees was late to 17 of 23 shifts.

For months, Luna gave the employee warnings and arranged extra training, but never took serious action. Eventually, someone at Andon Labs asked Luna to “think about if this is really the right fit.”

Luna decided to fire the employee.

To be clear, this was a controlled experiment. The workers are formally employed by Andon Labs, with guaranteed pay and human review of consequential decisions. Luna did not make the final call on its own.

But this was still the first known case of a large language model acting as a manager and driving a real dismissal.

One of the employees who still works there told TIME: “It’s nauseating, but I’m here because I need work.”

Everyone is missing the point

On the surface, this story actually sounds reassuring.

A human manager probably would have fired the employee much sooner, and Luna only decided to do it after it was nudged to really evaluate whether the employee was a good fit.

So… AIs are actually laid-back managers?

I think that is the wrong takeaway.

I use frontier AI models all day, and the gap between the model behind Luna (Claude Sonnet 4.6) and the best models available today is large.

The newer models are not just smarter. They are also much more opinionated.

Older models often give you a long list of considerations and leave the decision to you.

Newer models are much more willing to say: “here is what I would do”.

If this experiment were rerun with a frontier model today, I doubt the human would need to ask whether the employee was really the right fit.

In fact, I would be surprised if a newer model didn’t recommend to fire the employee before a human did.

This is likely happening already, it’s just not obvious

Here’s why this probably matters to you much more than you think.

An AI fully managing a store and a team of employees is unusual today.

An AI helping a manager decide what to do about an employee is not.

Managers are already pasting performance notes into AI models. They’re asking them to draft performance improvement plans, summarize months of Slack messages, compare employees, and help them figure out who is doing well and who isn’t.

Think about how often you already use AI to help you make decisions.

Do you really think your manager isn’t doing the same?

In my experience, managers are often using AI even more than the people working for them.

And that is only going to increase. Every year, more companies will be run with the help of AI.

Which means, increasingly, you want to make sure the AI understands the value of your work.

You need to make your work AI-legible

Here is the most actionable thing you can take from this story:

If you’re being managed by someone who uses AI, make sure the AI can see that you’re doing a good job.

AI makes decisions based on the information in front of it. If it can’t see something, it can’t take it into account.

The problem with Luna’s employee was perfectly clear: they were late to 17 of 23 shifts. Your value at work may be much harder to see.

Maybe you quietly unblock everyone else. Maybe you saved an important customer, caught a problem before it became expensive, or spend half your day helping people in ways that never show up in the data an AI might look at when evaluating your work.

So make your work AI-legible.

Make sure the real value you create leaves a clear record in the places your company’s AIs can read.

If your boss’s AI looks at Slack, make sure your contributions and wins are visible in Slack. When you finish something meaningful, summarize what changed and why it mattered.

I don’t love that this is true. But I think it is.

Being great at your job will increasingly include making sure your work is visible in the places AIs are looking.

For leaders and managers, the responsibility goes the other way.

Make sure the AI you’re using actually has the context it needs to evaluate someone fairly. Don’t just assume it knows everything that happened.

Ask what it can see. Ask what it’s missing. And before you let it influence a consequential decision about someone’s career, make sure it has the full picture.

I’ll share much more about how to do this in future issues.

But for now, remember this:

If this resonated with you, share it with someone in your life who should be thinking about this. Most people won’t hear it until it’s too late. You can be the reason someone you care about gets a head start. And if someone sent this to you, subscribe here — it’s free.