There is a new AI model in town. And this one shows us where things are heading.

It is called Interaction Models. It comes from Thinking Machines Lab, the company founded by Mira Murati, who was CTO at OpenAI. It is in research preview right now.

It’s not in your tools yet, but let’s have a look so that we understand what’s coming.

We've all learned we have to verify everything that comes out of AI.

It hallucinates. Hallucination rates are coming down, but we still review everything, because it's our name on it.

But something else is starting to emerge. Quite the opposite.

Every AI conversation I have now starts from where the last one ended. That’s a massive leap in how AI works with me.

My AI knows my clients, my KPIs, my coaching patterns. It knows what we talked about last time. It updates itself as we go.

That's because I've given my AI a Second Brain.

And if you have’t already, I think that you should do it too.

Last Friday I spent four hours online with 50 accountants developing AI agents.

Here’s what’s real with agents, in accounting in May 2026, Australian and New Zealand.

Inter-entity loan reconciliations done in minutes, saving hours a quarter.

FBT calculations cut by 40 minutes per client.

A budget vs actual analysis that used to be skipped, now done in 90 seconds.

This is what’s here. Working in firms. Today.

And I want to tell you about how you can (and should) get it.

Microsoft just shipped AI agents in Excel, Word, and PowerPoint.

Until now, Copilot could suggest things or take small actions like add a row, make a pivot table or create conditional formatting.

Now it can take multi-step actions, think through a problem, develop entire workbooks with multi-step reasoning.

But hey, Claude has had this capability for months now.

And for all this time, I fielded questions from firms wondering if they should be on Claude instead of Copilot. These capabilities are so powerful, and it felt like we were missing out in very real (and painful) ways.

Is AI making us dumber?

We've got some official results on this.

It's a real concern. We're all shifting from doers to reviewers. In every part of our work, AI does something and we check it's right.

But how can junior people review work they've never done themselves? And how will they even learn the profession if AI does the work for them?

If you've heard me speak, you know I'm optimistic about this. I teach myself through personalised podcast episodes with expert knowledge applied to my own circumstance. What a life hack!

My 13-year-old son, this week, built himself apps with simple AI prompts. One to learn world flags. One to prepare for a French exam he doesn't enjoy. One to figure out how to design a 3D object he wants to print.

He chose those projects. He wanted to learn. AI just made it faster.

That's my optimism. But what does the data actually say?

Do you have an AI lab in your business?

If you don't, you should. Whether you're a one-person firm or a hundred-person firm.

Let me tell you what I mean, and why it matters right now.

What if every piece of work you produced got reviewed by a panel of experts before anyone else saw it?

A tax specialist. A grant assessor. A contract risk reviewer. A plain-language editor. All on demand. No billing rate. No waiting.

Last week I worked with an Australian research institute. We worked on AI strategy, tools, automations, and risk. But we also spent a lot of time with hundreds of people on prompting techniques that genuinely improve workflows.

This is one of them. And while the example comes from research, the principle applies to every profession. Including yours.

The idea is simple: give AI a specific identity.

Tell it who to be. What they know. How they respond. Then give it your work to review.

That's called a persona prompt. And what you get back is not a generic AI response. It's feedback from someone who actually knows what they're looking for.

Let me show you what I mean.

AI gets things wrong. We know that.

It makes things up. It hallucinates. It wants to please us, so it will answer a question even if it doesn't really know the answer.

You can tell it: don't make things up. Be accurate. Give me a confidence level. But that's still the AI telling you what it thinks. It doesn't actually check itself.

So here's what I want to explore with you: what kinds of problems come up, and what can we do to stay safe?

How do we make sure our team knows how to verify what AI gives them?

What do we do if someone shared the wrong thing with the wrong AI?

And how do we build a culture where people feel safe to speak up when something goes wrong?

Let me walk you through it.

We're all building AI agents.

There are different types of agents.

There are ones that just have a skill. They know how to do a certain task, and you can chat with them when you need help with that task.

There are ones that work in the background, with access to your systems, getting things done while you sleep.

And there are ones that work on your desktop or in your browser and can actually interact with the user interface of your apps.

What is it that makes some of them safer and others more risky?

That's an important question to sit with, so we know where to put our focus while this technology matures.

Claude is making a serious play.

Not just to be the AI you chat with. To be the interface where you work. Where you start a task, finish it, and never need to jump between tools.

That's a big claim. So let me show you what it actually looks like.

What’s my next meeting today?

Who’s the client?

Have they paid their invoices?

Three different systems or one AI to rule them all?

Well, it’s starting to be the latter.

Let me show you how.

My recommendation for the main AI tool you should use in your business has changed.

Not because of a new shiny feature.

Because two quiet things happened at the same time:

One: Copilot got smarter.

Two: Copilot became easier to roll out.

And when those two line up, the decision becomes simple.

This week I gave Claude the keys.

Not to my thinking. To my computer.

I've been experimenting with Claude Cowork, Anthropic's new desktop agent.

We've seen AI work in the browser before, but this is different. This is AI operating the whole computer, not just a tab.

If you've heard me talk about the Three Bridges: Playbooks, Context, and Hands, this is Hands. Properly, finally, Hands (for the newcomers: Hands means AI that acts, not just advises).

This year, AI is becoming part of our workflow. Not just a tool we chat with.

We are starting to see AI agents, AI flows that run in the background, AI chatbots that specialise in certain tasks.

We are really heading towards little AI employees that we can assign tasks to, or that can own tasks and workflows themselves.

And we need to learn how to make all of this happen.

So I prepared a curriculum for you. Two free webinars over the next two weeks. Two hands-on workshops in March and May.

Here's what's coming so that you can choose what you should attend:

Two AI stories have been everywhere this week.

One: the AIs have got themselves a social network called Moltbook, and they’re talking about their humans and conspiring.

The second: there’s a new website where AIs are hiring humans to do work for them in the real world. It’s called Rent-a-Human.

Is this it? Are they taking over?

When I hear big claims like these, I go and look at how it actually works, so I can understand what’s really happening.

And I did just that.

So let me tell you what these things actually are, what’s going on under the hood, and then what I think we should and shouldn’t do.

Everyone is talking about Clawdbot.

The whole Internet is on it. There are endless videos showing how it can do EVERYTHING!

Ready to jump in and be part of the revolution?

Well, I say: not yet!

This is very, very early days.

This tool is still in innovator territory. It is simply not safe.

Let me tell you exactly what it is so you're totally clued in.

Then I'll tell you why we shouldn't use it right now, and what we should do instead.

I love my meeting assistant. I don’t go anywhere without it! Tons of magic is happening now that I have a written repository of (almost) all my conversations from the past months and years.

And now, there’s a step jump. For good, and for bad. The kind that takes some deep breathing to get used to.

In this video, I show you:

1. How AI meeting assistants are becoming active, agentic participants in our meetings

2. How they can become risky, uninvited infiltrators too…

Are you prepared for AI in 2026? This week we are taking stock. We will look at the foundations firms laid in 2025, so you can see where you are solid, where you have gaps, and what needs attention before the next wave of AI lands.

In 2025, most of the work was about foundations:

• Aligning leaders so they pull in the same direction

• Selecting secure AI tools

• Creating and updating AI policies

Now, in 2026, those foundations meet the next phase: AI agents, smarter workflows, and tools that can act inside your systems.

Welcome to the new year!

I am so ready for AI in 2026, because this is the year AI stops sitting in a separate chat window and really takes over some tasks and does them for us.

We are this much closer to AI employees that can take over entire tasks.

In 2025 we laid the foundations. We selected our tools, created policies, trained our teams, and built an AI‑literate workforce.

Now those people are asking a new question:

When will it do my tax return for me? When will it annotate the contract for me? When will it prepare the case?

Why you need to understand AI Agents and AI Employees?

First, so you can implement what is ready.

Second, so that when people try to sell you AI agents or AI employees, you can tell whether they are offering something genuinely valuable or something you could build yourself in one prompt.

There are three gaps between today’s technology and AI Agents that can actually do the work for you.

We need to understand where each one is at, and what we can do today: