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Maggie was already perhaps the best writer on the intersection of engineering and design, but now that she’s joined Github Next, she’s also extremely keyed in to where tools for coding are going. Her piece on Gas Town and orchestrating coding agents is sharp and worth reading in full.

As the pace of software development speeds up, we’ll feel the pressure intensify in other parts of the pipeline: thoughtful design, critical thinking, user research, planning and coordination within teams, deciding what to build, and whether it’s been built well.

The most valuable tools in this new world won’t be the ones that generate the most code fastest. They’ll be the ones that help us think more clearly, plan more carefully, and keep the quality bar high while everything accelerates around us.

We’ve known for a couple years now that faster coding will mean non-coding work will increasingly be a bottleneck, and now it’s happening. Deciding what to build – and whether it’s been built well – was already one of the most important tasks on a software team.

But in the face of tools that can add anything to your product, desirable or not, this judgement becomes the core of the work.

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Last week I wrote an exploration of Ben Thompson’s recent question, “Why is the ChatGPT Mac app so good?” A lot of people on the internet, it turns out, do not agree with this premise!

Many folks have been having problems with ⌘C not copying text. Hacker News sees the app as “not good at all”, to the point that my post about it being better than the alternatives was flagged off the site. X doesn’t like it either.

Beyond the bugs I mentioned in last week’s post, I’ve recently been plagued with a ChatGPT Mac bug of my own, where every time I start a new chat, it will pre-fill the text field with the first input I used last time I started a new chat on Mac.

All of this led me to an informative post by one of OpenAI’s Mac developers, Stephan Casas:

nearly everyone who works on the ChatGPT macOS app has been stretched thin, and hard at work building Atlas.

[…]

i’m thankful that our users appreciate our decision to develop a native app just as much as i’m thankful for the heightened expectations they hold because we did so

Apparently he merged a fix this week for the copy-paste bug that has been plaguing many folks, which is promising.

Something implied in last week’s article that’s worth saying explicitly: although many good Mac apps are native, being native is neither necessary nor sufficient for being a great app.

While OpenAI is investing more in desktop apps than any other model labs, they have much to do before they can transcend “better than the alternatives” and achieve “great.”

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