With last year’s release of MacOS 26 (Tahoe), Apple made a mess of app icons. In the first betas of MacOS 27 (Golden Gate), however, there are signs of a turnaround. We’re urging Apple to continue making improvements, by restoring the ability for MacOS app icons to have distinct shapes.

Apple’s Liquid Glass App Icons

In Tahoe, Apple modified the icons for dozens of their first-party apps to give them a “Liquid Glass” appearance. The changes were a substantial regression, leading to blurry, dumbed-down icons.

With the recently unveiled Golden Gate, Apple has again updated their MacOS app icons. This time, however, the changes are genuine improvements. Here’s the refined Automator icon, for example:

The newer icon is sharper, with superfluous Liquid Glass removed. Dozens of Apple’s apps have seen similar updates. The result is that Golden Gate’s icons are superior to Tahoe’s, as this comparison from Basic Apple Guy shows. Seeing these improvements led me to think about another fix Apple should make in MacOS.

The Problem of Tahoe’s Dictated Squircles

With the Tahoe release, Apple didn’t just mess with their own icons. They also dictated the shape of every third-party app icon, forcing them to adopt the same prescribed squircle. Any icon that failed to do so found itself shrunk down and imprisoned in an ugly gray background, in order to fit Apple’s desired aesthetic.

To avoid this icon jail, developers were forced to redesign their icons to match Apple’s preferred form. After decades of beautiful, memorable Mac icons in varying shapes, Tahoe flattened personality to obtain bland uniformity. The platform is worse for it.

Past icons weren’t just more expressive. They were also more usable. Having distinct shapes provided a useful way to tell icons apart. Tahoe eliminates that cue by forcing everything into the same squircle, leaving color as the primary way to tell icons apart at a glance.

That falls down if you’ve got color vision deficiency, or even just multiple icons with similar color schemes.¹ I’m looking at you, Slack and Photos. I have to look closely, because it’s so difficult to tell you apart now.

It Doesn’t Have to Be Like This

Apple’s prohibition on shapes is a step backward for both usability and creativity in app icons. Icons are now harder to distinguish because they’re no longer allowed to be distinctive. But there’s no technical reason for it. Apple could, and should, once again allow icons to take on a wide variety of shapes.

It’s clear that some people within Apple recognize that the transition to Liquid Glass introduced mistakes. They also appear to have the authority to fix those mistakes. Refinements to Apple’s own icons in Golden Gate are a welcome course correction, as is the much-celebrated Liquid Glass opacity slider. It’s time to correct the mistake of banning icon shapes as well.²

Apple should stop forcing every icon into the same squircle. Let’s return to a world of gorgeous app icons like these:

Free the icons.

Footnotes:

1. With color now so critical to tell icons apart, it should be no surprise that the new “Clear” and “Tinted” icon styles added in Tahoe are seeing so little uptake. As Adam Engst noted, “[I]t’s nearly impossible to identify a particular app when they’re all clear or tinted squircles, as you can see below. My brain just shuts down when it sees them.”

   

   I’m not sure this “Tinted” style would be a good idea even if these icons had distinct shapes, but I know it’s a very bad one given their uniformity. ↩︎

2. For folks within Apple, this was feedback filed as FB23388490 (“Third-Party App Icons Should Not Be Restricted to Apple’s Dictated Squircle Shape”). I imagine it is a duplicate many times over. ↩︎

We know that ICE wants to deploy eyeglasses with facial recognition that can identify people in real time.

Turns out Meta is prototyping the feature with a Pentagon supplier. (Alternate news story.)

It’s been more than two years since SanDisk announced plans to launch 4TB SD cards based on the SDUC standard. They haven’t actually arrived yet, so take this next part with a grain of salt, but during the Computex show in Taiwan earlier this month, SanDisk indicated that those 4TB SDUC cards really are coming […]

The post Lilbits: 8TB SD cards are coming soon (likely for a small fortune) appeared first on Liliputing.

In the last three months I’ve had people forward me four separate examples of a CEO losing his or her mind over AI. What’s been striking to me is the similarity in each case: It would be an “all hands” email in which the CEO talks up how amazing LLM tools are and saying that everyone in the company MUST start learning to use them immediately or they should look for a job elsewhere. Sometimes they talk about hiring “consultants” to come in and teach the team how to use the tools properly. Sometimes they are setting up “office hours” or internal “AI hackathons.”

But in every case the gist is the same “holy shit AI is amazing and you are expected to use it at your job all the time.” The worst case of these were the few companies that set up token leaderboards, which is perhaps the dumbest way possible to encourage learning how to use LLMs well. Good usage of AI includes learning how to view tokens as a scarce resource. Simply counting how much you use as a good thing is ridiculous because it’s incredibly easy to waste tokens on counterproductive uses.

As regular readers of Techdirt know, I actually do think that these tools are powerful and important, but I also think there are many problems with them and limitations to how useful they really are. I think when someone learns how to use them well and willingly chooses to use them as a tool to assist their work, they can be quite powerful. But the willingly choosing to use them part of that is important.

No one who is forced into using these tools will ever learn to use them well.

So CEOs losing their minds over the tech are not being helpful. Box CEO Aaron Levie — himself a genuine AI believer — puts his finger on exactly why.

CEOs are uniquely prone to AI psychosis because they’re sufficiently distant from the last mile of work that still has to happen to generate most value with AI.

So when they play with AI, they see the happy path results, often not considering the next 10 or 20 things that have to happen to get sustainable results from agents.

“Look I made this awesome product prototype”. Yes but you didn’t have to review the code before it went into production and fix a bunch of issues.

“Look I generated a contract”. Yes but you didn’t verify all the terms before it goes out to the counterparty and didn’t have to wire up all the past contracts to work with.

The best thing you can do as a CEO is to use AI a ton to figure out the real implications of agents in the enterprise, and come out the other side with an appreciation for both the upside and the real work that goes into them.

I will say that I hate the term “AI psychosis” because the term is extremely misleading, and many psychologists and psychiatrists have complained that it is inaccurate and may cause more problems itself. But the general sense that CEOs are going overboard with AI is definitely happening.

And I think Levie’s thinking as to why is also dead on.

Much of the issue may be in how disconnected the traditional CEO is from the people at a company actually getting stuff done. Normally, they have teams and layers and the actual work of getting things to work in a real way is so far removed from a CEO that they just get snippets of the details that filter back through the various org charts.

The problem tends to show up when a CEO is handed an agentic tool like Claude Code, and has it create something, which will work just fine, and thinks “oh, wait, why do we need so many people, when I can just sit here and make things work?”

This is a bad CEO.

Making things work is different than making things work well. Or well at scale. Or well at scale in a specific environment. Obviously, it depends on the kind of project and what it’s being designed to do, but oftentimes the reason a company has a bunch of employees is to fill in the seemingly small, but incredibly important details that CEOs might not ever get much visibility into: things like security or legal compliance or accessibility or who knows what else.

Using an agentic tool to build something that works is all well and good, but building a product for the mass market to use — and use well, and use safely — involves much, much more. Agentic coding tools can sometimes help with that too, but the leap from “I built a thing” to “therefore anyone can build a thing” misses the entire point of why you hire knowledgeable, experienced people in the first place. It’s also why I think the best case of these tools is building totally personalized tools to assist you in accomplishing a specific task, and not for building mass market tools.

This all reminds me of cargo cult thinking: The CEO knows that somewhere in the org, employees are pecking away at computers and work gets done. So they figure that themselves pecking away with Claude Code and seeing work get done is the same thing. It’s not. All those other steps those people are handling — the ones the CEO never sees — still need to happen.

That’s not to say employees wouldn’t benefit from a deeper understanding of both the power and the limits of these tools — they would. But there’s something darkly comical about watching a CEO go all in on the tech and then immediately conclude it means they can fire half the staff.

It seems pretty clear to me that companies that think they’ll be able to layoff huge swaths of workers because of LLM tools are going to find out they’re mistaken pretty quickly. The power of LLMs is that when used well and used willingly it can help employees to get more done, but that doesn’t mean you need fewer humans. You need more humans who know how to work productively.

Separately, companies pointing to LLMs as a reason for large layoffs are, in most cases, just using it as an excuse. They over-hired, and “AI efficiencies” is a much more palatable story for Wall Street than “we made bad headcount decisions.”

Levie’s prescription, though, is right: CEOs should learn how the tech works, but that includes the limitations of the technology. If a CEO thinks the prototype they vibe coded is production-ready, let them ship it and see what happens. If they think a vibe coded contract is as solid as one a lawyer reviewed, let them find out what the legal bills look like when it falls apart.

Yes, the tools are powerful, but a CEO who thinks they replace the work of employees is simply a bad CEO.

On Tuesday, Donald Trump finally signed his executive order expanding the government's efforts to conduct voluntary safety testing of frontier AI models. Now, critics are warning that the order may be short-sighted, offering only performative reassurances that the government is actively monitoring for AI risks, while changing very little about how and when models are deployed.

Last month, Trump abruptly canceled a signing event, where he had hoped to launch an earlier version of the EO with CEOs of leading AI firms in attendance. Invited at the last minute, several CEOs simply couldn't make the signing but still signaled support for the order. Officially, Trump claimed he postponed the event because he worried that the EO might have gone too far and had become a "blocker" impeding AI innovation. Reports indicated there was infighting in his administration as cybersecurity experts clashed with officials committed to deregulating AI.

The watered-down EO that Trump signed promises not "to stifle this innovation with overly burdensome regulation" and establishes no requirements for AI firms. Instead, it sets up a voluntary process for companies to collaborate with the government on safety reviews that Trump's EO claimed would "ensure that the best and most secure technology is deployed rapidly to confront any and all threats to our country."

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