Microsoft managed to make “Copilot” mean “AI slop” thanks shipping completely broken and forced Copilot features for years, so ppl hate it. Not too dissimilar to Google’s Gemini integrations that are just as unserious. Corporate incentives… (I am not talking about GH Copilot)

Grady has lived through seveal technology changes (microprocessors, the internet, mobile, now AI) and says that when it all changes, some things are the same in software engineering. He's also saying we're entering anoher "golden age of software engineering" thanks to AI!

"Application development did not change much for 20 years, but now, a new wave is crashing in. Most computers in the future must be put to work at least in part w/o programmers. Not surprisingly, programmers will instinctively resist methods described in this book." - 1982, James Martin, in the book Application Development Without Programmers

The more time I spend working with coding agents, the more convinced I am that they make software engineering even harder We can do amazing things with them, but unlocking their full potential requires extraordinary discipline and knowledge

Bury your head in the ground at your own risk. I aim to not jump on any hype trains, but since Opus 4.6 and GPT-5.2 + the harnesses it was clear that these things can write code nearly as good as I can in my best language; better in other languages. But we won't see non-devs push production code for a long time; possibly forever, if you ask me. Software still needs to be built in robust ways, and it's our profession to do this well, and use the new tools we have, which create new and interesting (+tough!) challenges

"You have to understand the materials you're building with in any design role. A table designer would not be oblivious to how oak performs in certain contexts or how pine dents in a certain way. If you're designing for the web and you don't understand performance or how your app is fetching data or what if there's race conditions, if you're oblivious to that, you'll end up with bad design solutions and then with really bad relationships to engineers." Maggie Appleton @Mappletons - Design Engineer at GitHub Next

What can us, engineers else learn from designers and design engineers? Turns out there’s lots, based on talking with one of the best design engineers in the industry, @Mappletons. Timestamps: 00:00 Intro 03:24 From anthropology to tech 10:18 What does a designer do? 18:23 How Maggie works 24:55 The case for planning with physical tools 31:53 Why Maggie is learning woodworking 33:13 Design engineers and engineering constraints 38:49 How Maggie uses Figma 40:30 Design at GitHub Next 45:12 How has AI changed design 50:37 When models design and why humans are still needed 53:30 UX and UI 58:29 Capability gaslighting 1:00:33 One Developer, Two Dozen Agents, Zero Alignment 1:07:21 Craft and AI tells 1:14:17 Visual gardens, home-cooked software, and barefoot developers 1:21:02 Advice for engineers and lessons from anthropology 1:25:34 Book recommendation Brought to you by: • @turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable. • @AntithesisHQ – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages. • @EntireHQ – every agent prompt, tool call, stored in your repo, and mirrored. Set up with one click: Hope you enjoy this unusually visual episode - thanks again, Maggie!

Notice how the AI labs who are the most “AI-pilled” and have unlimited AI tokens to use per employee keep hiring and hiring, and are not laying off? Heard from a company investing big on AI which did big layoffs due to wanting to have fewer engineers thanks to AI that… they realized they need more engineers, ASAP. Who would have predicted, huh?

A look into how the Windows team is integrating AI into their OS: eg they're adding agent identities, akin to that of a user. It's the first opinionated approach I see for AI agents at the OS level - and surely other OSes will do sg similar. Deepdive:

Feels like model providers do w model names like supermarkets with the essential groceries: Keep messing with their positions so you lose your sense of direction, and not know what is what beyond the latest Eg Opus: 3.5 -> 4 -> 4.1 -> 4.5 -> 4.6 -> 4.7 -> 4.8 -> 5 -> 5.5

I setup a “personal assistant” to help summarize all the things I needed to do the day. Day 1 was amazing, at least I thought From day 2 to day 10 ignored the whole thing lol Turns out I just don’t want to make a bunch of decisions, and an AI agent doesn’t change that. 👇

Pretty incredible how the skills repo by @mattpocockuk is only 6 months old, and has more stars than the React one. We had to sit down and talk. Timestamps: 00:00 Intro 05:48 How Matt got into tech 10:14 How Matt got into open source 12:58 Joining Vercel 18:39 Total TypeScript 23:21 AI’s impact on technical education 30:32 Building reusable skills for AI coding agents 40:46 The “smart zone” vs the “dumb zone” 45:02 The wayfinder skill 47:52 Why agents excel at software engineering 50:54 “Leading words” 1:01:10 Learning the fundamentals 1:09:17 Local vs. cloud agents 1:12:36 Planning vs. course-correcting 1:18:13 TDD and agents 1:23:06 Living in the UK 1:24:21 Teaching: the human part 1:28:36 Advice for junior engineers 1:31:07 Gardeners and great engineers 1:34:01 Book recommendation Brought to you by: • @turbopuffer – vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable. • @linear – the product development system trusted by 40,000+ teams to plan and ship. Get six months of Linear Business for free: • @WorkOS – The fastest AI-native teams have to slow down for the hard problems. WorkOS makes sure auth, for your app and your agents, is never one of them. Thanks for the convo @mattpocockuk!

Here's what OpenAI's agentic software factory looks like, today. Details: (thanks to all the OpenAI folks who explained how it works! And Perf Factory looks especially interesting to me)