I’ve spent the past few years watching AI evolve at extraordinary speed, yet the conversation this week pulled me back to a simple question: what does intelligence look like outside a screen? LLMs can write, plan, analyse, and act across digital systems with reliability. They operate in environments designed for clear inputs and predictable outcomes. That is where today’s breakthroughs shine.

Last week, Disney made a decision that will ripple through every creative industry. The company agreed to a three-year licensing partnership with OpenAI and backed it with a $1 billion investment.

I’ve lived with emotional fog for most of my life. Sometimes it arrived like the morning mist that’s soft, easy to miss, then hard to shake. Other times, it moved in with force. There were moments in my teens when I couldn’t find a way through it. I became destructive. Eventually, I asked for help. I went to therapy, learned how to name what I was feeling, and over time, I found steadier ground.

The browser wars have returned in a completely new form.

But this time, the competition focuses on how we think and how we process information.

OpenAI’s Atlas and Perplexity’s Comet are evolving into thinking environments and are becoming spaces that interpret data, summarise insights, and remember what matters to you.

The line between AI helpers and AGI decision-makers won’t be announced

You won’t wake up to a headline that says, “AGI has arrived.”

You’ll notice it in smaller ways. The tools you lean on will stop waiting for you to push them. They’ll start moving work forward on their own.

Once upon a time, employees kept side hustles tucked away after work hours. Today, they keep side AIs secret. Workers have hidden tabs, personal logins, and unapproved tools quietly build an invisible layer of productivity.

There’s a gap forming within mid-sized businesses. The models keep accelerating while the organisations meant to use them are moving slowly. I work with teams that sit in this middle layer, and many feel caught between ambition and reality. They want to adopt AI, but their systems, processes, and culture were never built for this pace of change.

The psychoanalyst Jacques Lacan had a theory called the “Mirror Stage.” It is that moment in childhood when you first see your reflection and realise, “That’s me.” But it comes with a twist. You also realise you are a person who can be seen, judged, and defined by others. You begin performing for this “big Other” which the invisible system of family, culture, and social rules.

This morning my AI assistant told me to take the day off. To close the laptop. To step outside. To remember I’m human before I try to be superhuman.

My human friends would have said the same thing as well but coming from the machine I built to keep me productive, it landed differently.

Remember when “get a degree in computer science” was career advice you could set your watch by? For years, it was the safest bet. It was everyone’s ticket to job security in a world obsessed with disruption.

The machine is running at full speed. But, are we steering it or are we just keeping up?

We like to think we’re in charge. After all, we’re the ones giving instructions, coming up with the clever prompts, telling our AI what to do.

What if the choices you make every day aren’t really yours?

There are days when every decision feels borrowed. I catch myself moving through routines, following signposts someone else put up. The world offers options, sure, but they never quite feel like mine.

I grew up in a house of rules and routines, and movies were my way out. I’d watch them, replay the best scenes in my head, and sometimes imagine I was Steven Spielberg, building worlds bigger than the four walls around me.

I once asked my AI assistant (which I’d built to help me brainstorm, strategise, and think through decisions) what my biggest weaknesses were. Not as a test, but like you’d ask a friend who’s seen you on your best and worst days.

We used to figure things out.

For most of the internet’s history, that’s what it was for. It was a space where we figured things out. You'd go searching if you had a problem or even just a feeling that something wasn’t quite working.

The world’s most honest job interview question is finally on the table: “Are you sure we can’t get a machine to do this?”

Privacy once meant closing a door.

Today, it means defining which version of yourself a machine remembers.

These conversations are encrypted exchanges and it’s personal, custom, and revealing. Each message, correction, or late-night prompt adds another layer to how the machine understands you.