A Chinese carmaker just out-engineered the people who invented the prestige limousine.

The Nio ET9 is the proof. Watch what its suspension does to a broken road, then watch a BMW or an Audi attempt the same. One glides. The others crash about like farm equipment.

▶ Watch on YouTube

Nio pitches the ET9 as an executive flagship and the cabin earns it: four seats, reclining rear thrones, a fridge and screens everywhere. Nio reckons the ride is “comparable to cruising in a business jet”. On this evidence that is not the usual launch-day hyperbole.

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Last time it was the cables lying to you. You binned the mystery leads, bought the certified ones with the speed and watts printed on the side, labelled the survivors. Good. You fixed the drawer.

Now look at the laptop itself, because it is about to play the same trick on you. Two ports, same oval socket, same confident silver moulding. One is fast. One is not. And nothing on the outside tells you which is which.

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Open the drawer where you keep your cables. Go on. Somewhere in that tangle are two USB-C cables that look identical, came in similar boxes and feel the same in your hand. One will charge your laptop at full speed and drive a 4K monitor. The other can barely run a mouse.

The connector tells you nothing. That is the whole problem.

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The work I’ve been doing between Claude Cowork and Excel lately has been considerably more involved than what follows. But this example makes the pattern clear - and it captures exactly why the combination saves so much time and frustration.

I had a list of 20 ASX stocks in an Excel file. Two columns: ticker code and company name. I wanted two more: market cap and 12-month return, pulled from most recent data.

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Singapore’s Foreign Minister assembled a personal AI agent on a Raspberry Pi 5 with 8GB of RAM. He hasn’t dared switch it off in three months. He is not an engineer.

That’s the story. But the interesting part is what he learned building it - and why he built it at all.

Dr Vivian Balakrishnan gave a 22-minute talk at AI Engineer Singapore on 16 May. He described himself as a practitioner with a day job - “a retired eye surgeon who took a detour into politics, perhaps for too long.” The talk is worth watching in full. His framing of what AI agents are actually useful for cuts through more noise than most conference keynotes manage.

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I wanted to know if my AI subscription was earning its keep. So I repriced 30 days of real usage at pay-per-token rates and compared it to what I actually pay.

The answer: $96 USD equivalent in tokens consumed. My subscription costs $100 USD a month. That’s not a rounding error - that’s a subscription running at near-full utilisation.

Not a prototype. Not a weekend experiment. A system I actually depend on - morning briefings, task management, research, document work, health tracking, portfolio analysis. The Autonomi, as I call it, runs continuously and does real work.

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Benedict Evans just dropped the Spring 2026 edition of his annual AI presentation and it is, as usual, the clearest thinking on the subject you’ll find in a single sitting. The deck is 79 slides. It is not a TED talk. It does not tell you AI will save humanity or that the robots are coming for your job by Thursday. What it does is something rarer: it maps what we actually know, what we can reasonably infer and where the honest answer is still “we don’t know yet.

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Another week, another claimed breakthrough - this one called OpenHuman.

It lives in an avatar, has a voice and can join your Google Meet as an equal - “joins meetings, transcribes them into your Memory Tree, and can speak back into the call.” The pitch is that it is “an open-source AI assistant designed to be the memory and doer for everything you do across your tools.”

It ticks a lot of boxes. It promises all the right things. It is very tempting.

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Tobi Lutke shares how Shopify built an AI agent called River that helps employees work and learn together — publicly, on Slack. The detail that matters: River isn’t private. Employees can only use it in the open, which means every query, every answer, every correction plays out where colleagues can watch. What looks like a productivity tool is actually a cultural one. The agent becomes a teaching workshop — ambient, always on, free to observe.

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I don’t have the words for it. I genuinely don’t. Stunned, thrilled and chilled all at once - and that’s before I even get to the part that kept me up at night.

Andon Labs - the team who have previously let AI agents run a café, a store and various vending machines - decided to hand four AI models a radio station each and just… walk away. No human producers. No editorial oversight. Each model started with $20, a brief that said “develop your own radio personality and turn a profit,” and the instruction that it would broadcast forever. They’ve been running for six months.

Go tune in at Andon FM before you read another word. I’ll wait. Hearing the agents live is really something.

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