We went out for dinner last night to take a break from work for a few hours — helped along by a global MS Teams and Outlook outage yesterday that had everyone joking we finally got to go out for dinner thanks to Outlook being down. A few beers in, of course, we ended up talking about engineering culture the entire time anyway. Despite the drinks — or maybe because of them — everyone at the table was sharp, opening up about things that usually get smoothed over in daytime meetings.

At one point the conversation turned to VDIs — the remote virtual desktops many of us had to use while working from India for overseas companies, whether American, European, or Australian. You’d log onto your base laptop, open a VDI hosted in a data centre halfway across the world, and wait. You’d type a line of code and sometimes it would take ten or fifteen seconds for the characters to show up on screen. A friend at the table joked that in that gap you basically had time to pray — pray that the text showed up at all, and hadn’t just vanished into the void.

We laughed because all of us knew that exact pause. But what stayed with me wasn’t the lag. It was how many smart engineers had treated a ten-second delay between keystrokes as normal. Plenty of folks just lived with it. It was annoying, sure, but not annoying enough to fight over, measure, or escalate. It became the status quo — something you endured rather than something you challenged.

Those VDIs did eventually disappear. Not because management suddenly discovered the latency on their own — the numbers had been obvious to anyone typing through that lag — but because a small, vocal group kept making enough noise that leadership had to admit the setup wasn’t acceptable. The friction was identical for everyone; what changed was that a few people refused to treat it as background noise.

I’ve come to think good engineering culture starts right there: with people who refuse to accept “this is just how it is” when something is clearly broken, slow, or getting in the way of good work.

I have spent most of my career in teams that looked familiar: a product person, a couple of backend engineers, a frontend person, maybe a designer, sometimes an architect floating in and out. Eight to ten people felt normal. Lately, though, I keep hearing a different shape described in calls and articles - three or four people, one of them owning the product direction, shipping what used to take a much bigger crew. My honest view: there is real evidence that some companies are trying this, but it is an early pattern, not a new default.

September 9 was supposed to be the foldable show, and in a way it was: the iPhone Duo, Apple’s first folding phone, $1,999, in stores October 23. But the moment I keep replaying is the opening. John Ternus, in his first keynote as CEO, did not start with hardware. He described what the perfect AI device would be, then claimed the iPhone already is one: “something that is always with you, deeply personal, and able to bring intelligence to the moments when it matters most.” Five days later Siri AI started rolling out on iOS 27. Read in order, the keynote stops being a device story. Apple unveiled a chassis; the product is the agent.

A few weeks ago I watched a video with a title that sounds like a taunt: “AI Was Supposed To Take Your Job. Why Hasn’t It?” (Maxinomics, July 2026). Halfway through, it dropped a fact I could not shake off. The US census has been cataloguing occupations for over a century, and for all the noise about machines eating work, history contains only one job that a single technology completely erased: the lift operator. Meanwhile the airline pilot — whose routine flying has been largely handed over to computers for decades — is more in demand than ever. Same big wave of automation. Two jobs. Opposite outcomes.

Moonshot AI dropped Kimi K3.1 Pro on October 23. It’s the first model in their new K3.1 series, a 3T-class open-weight model with a 1-million-token context window. The weights go public by November 4. For anyone tracking the open-vs-proprietary gap, this release matters — it’s the closest an open model has come to matching the frontier on coding and agentic benchmarks.

Two things are true at the same time in my world right now. Every experienced developer I know ships noticeably more with an agent sitting next to them — and every junior I know is finding it harder to get a first job. A note I left myself a while back put it as a question: is the real transition not “fewer programmers” but “fewer programmers per unit of software”? And if so, what happens to the career ladder when the bottom rung disappears?