As we approach the end of the year, I want to talk to you about what I saw in 2025.

What made it a special year?

What are we learning about AI?

What surprised me?

And if you're lucky and stay to the end, you'll even get my seasonal film recommendation.

So what happened in AI this year that makes it different to previous years? Well, my favourite is

surely going to be nanobanana. That's Google's image generation service. First of all,

it's got a fantastic name. It's one of the few things as a Brit. I say less well than an American.

So if you're an American, say nanoobanana. And if you're not,

find an American and get them to say it to you because they say it so much better than we do.

It's kind of amazing. When you pair Nanobanana with Gemini 3 Pro and you present some complex idea, you can say to Gemini, listen, please you present some complex idea.

You can say to Gemini, listen, please use Nanobanana to turn this into an explanatory diagram,

and you get pretty phenomenal explanatory diagrams, little cheat sheets, if you will.

They could either be infographics or they could look like whiteboards.

I have used it so frequently to communicate with people I'm doing things with.

The other thing that happened in 2025 is that many of the models got good enough to do really long stretches of work.

Claude 4.5 from Anthropic is fantastic if you're working with long documents.

It's fantastic if you are coding. GPC5 from OpenAI is increasingly good when you think about

deep research. It's really good at certain classes of problem solving, and in the latest

version of 5.2, I've been using it to support some financial modeling. And I can't leave out

Google's Gemini 3 or 3 Pro. It's markedly better than the previous generation of models.

And it doesn't stop there. I've been using Manus, the research product,

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