August 2026

Another great app from Marco Arment. The introduction post tells the story behind it so well. I’ve been a fan of Overcast for well over a decade. When a developer cares about the problem they’re trying to solve and puts in the effort to solve it well, you can feel it in the finished product.

ShieldFont is an open-source creative technology project that offers a practical opt-out from unauthorized AI training and disrupts what is collected when that choice is ignored. It swaps 45.8% of content words (around 24.4% of all words) in a page’s source code for other (partially) random words, while the font restores the original text on screen. Readers see the work as intended; mass scrapers collect an altered version. In testing, shielding caused over 90% of pages that would otherwise pass the quality filter to be rejected, keeping them out of the training pipeline. Of those that still passed, 19.4% of all words conveyed false meaning, adding noise to unauthorized AI training datasets. This paper’s goal is to walk newcomers through the whole process, in plain language and in order: the project’s rationale, how it was built, the results, how to deploy it, and where to contribute.

This feels heavy-handed. I don’t like solutions to AI scraping that make the web worse. But ShieldFont is another signal of the growing sentiment against AI.

When it comes to wearables on the face, the job is going to be optics. When the Watch came out, they said: by the way, it’s a timepiece. It took a lot of cues from timepieces, a very old category. So if you study eyewear, you have to study deeply what people are using it for. It isn’t natural at all to use eyewear to take pictures. What’s natural is to see better. The whole objective of eyewear is to give you clarity, not to collect information and process it in the cloud. So you pivot away from what the early versions of the products are. You listen to what the early entrants did and you get confused, because they all had the wrong jobs, or the wrong approach, or the wrong processes, or their own priorities. And you assume that what they did is what Apple’s going to do. They’re going to come at it a whole different way. Of course it can see — but to the extent that it can see, it helps you see. I really think they’re going to position it as a great optical device, as they did with the Watch, saying it’s a great chronograph.

I could have fixed it, but it turned out to be important, because if you get two good players they could just volley and play the game forever. And the game has to end in about three or four minutes otherwise it’s a failure as a game. So that gap at the top, again – a feature. So that was sort of a happy accident.

“Happy” primarily in the context of the industry – the goal of an arcade game was, after all, to bring in quarters, and this here was the unexpected equivalent of the zero in a casino roulette game. But I wonder if some of this bugginess/randomness also helped the game feel challenging and surprising, even for skilled players.

Meta’s philosophy for how it intends to build and distribute superintelligence, at roughly 6,500 words. It rests on three principles: individual empowerment as the source of prosperity, invention as the purpose of superintelligence, and balance of power as the foundation of safety. Here’s the short version.

The first half describes what Meta plans to build. A personal agent for everyone, tools for creation, tools for starting businesses, a tutor and coach in every subject, and broader participation in scientific research. Access is meant to be free or affordable, with a compute auction for people who want more than the free tier.

The second half works through the risks: job displacement, data center impact on local communities, cybersecurity, biorisk, government overreach, American competitiveness, and keeping humanity in control of AI. Each is treated as a question of how power is distributed rather than a technical alignment problem, on the reasoning that no single system can align to values people hold in opposition. The proposed answer to each is wide distribution, so that many parties hold the same capability and check each other.

It closes with commitments: continued open source releases, a fully private mode for personal agents, closer collaboration with government including early access to training checkpoints, several policy recommendations on infrastructure and export controls, and a governance change giving Meta’s independent board approval over model release safety criteria.

An engineer putting a piece of work on their backlog is effectively deferring it to never. It’s important enough to write it down somewhere and document that it exists as a bug or a feature enhancement, but it’s not important enough to act.

Yes, sometimes we ambitiously carve out time to “burn down the backlog”, but do you know what we pick from that list? We pick the interesting work. Interesting to code or interesting because of the impact on the feature. Some kind of interesting briefly elevates this work to relevance. The boring backlog work? You couldn’t pay me.

I’ve avoided keeping backlogs for most of my career because they behave like debt. You put the task on the card, feel good about not losing it, then pay interest every day you don’t do it. Grooming, triage, scrolling past the same broken link for the ninth month: all payment, none of it touching the principal.

Handing the list to an agent changes what the list is for. A backlog became a graveyard because writing work down was cheap and doing it was expensive. Close that gap and it’s a queue again. I still don’t want to keep one, but I’m less sure what I hated was the list rather than the price of acting on it.