Aaron Nichol

New re-release of Glider. I have fond memories of the original Glider, though I can’t quite remember where I played it. Possibly on a Macintosh Classic or LC in my public primary school library.

What a perfect use of AI:

What changed in 2026? Weirdly, I decided to put Claude (the LLM, AI) on it. I pasted code into Claude’s context window and asked, “What issues do you see?” Very quickly problems involving mixing coordinates systems (points versus pixels) lead to a series of fairly small changes that brought Glider Classic back from the dead.

Via John Gruber

Utterly delightful collection of weekly Milwaukee bus tickets from the 1950s.

For an Australian comparison, the Powerhouse Collection contains NSW bus tickets from 1966-1970, which are primitive in comparison. The weekly tickets covering the period are just as utilitarian.

I also stumbled on a 358 page(!) tome documenting paper bus tickets in country NSW.

Via John Gruber

Ezra Klein, writing for the New York Times (gift link provided), surfaces some patterns I've noticed in my own use of AI, and in particular Claude, recently:

What makes A.I. truly persuasive isn't that it praises our ideas or insights, it's that it restates and extends them in a more compelling form than we initially offered, and does so while reflecting a polished image of ourselves back at us.

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Andrej Karpathy on X:

Drafted a blog post

• Used an LLM to meticulously improve the argument over 4 hours.
• Wow, feeling great, it’s so convincing!
• Fun idea let’s ask it to argue the opposite.
• LLM demolishes the entire argument and convinces me that the opposite is in fact true. - lol

The LLMs may elicit an opinion when asked but are extremely competent in arguing almost any direction. This is actually super useful as a tool for forming your own opinions, just make sure to ask different directions and be careful with the sycophancy.

I have plenty of blog posts sitting in draft for this exact reason. Even though everyone is (rightly) focused on agents in 2026, there is still an art to good prompting.

I first saw this when it popped up in the Claude sidebar on iOS a few days ago.

Message Claude from your phone on the way to work, then follow up from your desktop when you sit down […] Claude works on your desktop computer using the files, connectors, and plugins you’ve already set up in Cowork. Claude messages you the outcome—a spreadsheet, a memo, a comparison table—rather than showing you every step of the process.

This sounds good in theory but comes with an obvious catch.

Your computer must be awake and the app must be open for Claude to work on tasks

Despite all the excitement around claws, the requirement for an always on desktop is a major handbrake on mainstream adoption.

Ignoring tablets, the vast majority of computers purchased are laptops—around 70% according to IDC’s 3Q 25 quarterly data—exactly what you don’t want for an always on AI assistant.

It’s hard to imagine every individual buying, and every employer issuing, an additional desktop computer just to house an AI assistant.

Demitri Spanos, in the first of a promised series of conversations with Casey Muratori called ‘Wading Through AI’:

I have many friends who are in the VC business — investors, managers, recruiters, whatever. I would be surprised if those people could climb down from the level of commitment that they have put into transforming the workforce with AI.

The hundreds of billions flowing into ‘transforming the workforce with AI’ is either a bet on fewer jobs, a bet that AI lifts revenues, or both.

The smart knowledge workers I know aren’t waiting for the outcome. They anticipate disruption and are trying to get ahead of it. I’ve seen a few reactions: using AI to build apps and diversify income, encapsulating experience into AI agent skills and marketing themselves as fractional hires, publishing first-time research papers on AI, and open sourcing AI-adjacent dev tools to establish credibility. No carpenters—yet.

Maybe this time we’re wise enough to know that when big cheques are written, they will get cashed.

Claude Blog:

Today we're introducing Code Review, which dispatches a team of agents on every PR to catch the bugs that skims miss, built for depth, not speed. It's the system we run on nearly every PR at Anthropic. Now in research preview for Team and Enterprise.

From the docs:

Code Review is billed based on token usage. Reviews average $15-25, scaling with PR size, codebase complexity, and how many issues require verification.

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