Apple Just Laid the Groundwork to Change the Public Perception of AI
If youâre a software engineer who hasnât been living under a rock for the last six months, you already know AI is real. Not hype-real. Actually-real. It writes code, it refactors code, it explains code youâve never seen, and it does all of it well enough that a lot of us have quietly reorganized how we work.
And yet, talk to anyone who doesnât write software, and youâll hear the opposite. AI is a joke. AI is a scam. AI is the thing that ruined their search results and took their job. The gap between how engineers talk about this technology and how everyone else does is enormous.
I think that gap is about to close. And I think Apple just lit the fuse at WWDC last week.
Two small features with a big implication
There were the usual headline announcements this year, but the two that stuck with me were small, almost throwaway:
- Safari can now generate extensions from a prompt. You describe what you want the browser to do, and it builds you an extension to do it.
- Shortcuts can now be created from a prompt. Same idea. Describe the automation, get the automation.
Thatâs it. No keynote fireworks. But what Apple actually did here is ship vibe-coding to a few hundred million people who have never opened a terminal and never will.
These arenât AI features in the way people have been trained to roll their eyes at. Thereâs no chatbot bolted onto a fridge. Thereâs no summary nobody asked for. The user states intent, and a working artifact comes out the other side. That distinction is the whole ballgame.
Why AI is genuinely good at code
Hereâs the thing most of the public hasnât been told, because it doesnât fit either the hype or the backlash: AI is good at writing code for a specific, structural reason. And that reason doesnât transfer to most of the places AI has been marketed.
Code is verifiable. You can run it. You can test it. You can review it. You can write a unit test that passes or fails with no opinion about how it feels. The output is reproducible â same input, same behavior, every time. When a model writes code, it can check its own work against a ground truth that actually exists: does it compile, do the tests pass, does it do what itâs supposed to.
That feedback loop is everything. Itâs why an AI can write a function, run it, see it fail, and fix it â converging on something correct without a human in the loop for every step. The model isnât trusted to be right. It actually checks that what it did works.
Now look at where AI has actually been sold to consumers. Summarizing your email. Answering questions about the news. Giving medical-ish advice. Chatbots that send you in loops. None of these have a compiler. None of them have a test suite. Thereâs no assert that the summary is faithful, no green checkmark that the answer is true. The output is plausible, and thatâs just about it.
Hallucination is the wrong word
We call it hallucination, and that word does a lot of quiet damage. Hallucination implies a malfunction: the system glitched, made a mistake, will be patched.
Itâs not a malfunction. A language model making something up because it sounds right is the model functioning exactly as designed. These things are built to produce the most probable continuation of text. Truth is not a parameter. When the most plausible-sounding answer happens to be true, great. When it doesnât, you get the same confident sentence, equally fluent, but completely wrong. The model has no idea which one it just did. It canât, because nothing in it is checking against reality.
This is why AI feels like a scam to so many people. Theyâve only ever met it in the contexts where it canât verify itself, where âsounds rightâ is the ceiling. Theyâve been shown the one version of this technology that has no ground truth to stand on, and told itâs the future.
Code is the opposite. Code has ground truth baked in. Thatâs not a small advantage. Thatâs the entire reason it works.
What Apple actually changed
So back to those two boring little features.
When a non-technical person asks Safari to build an extension that hides every âpeople also viewedâ section on a shopping site, something different happens than when they ask a chatbot to summarize an article. The extension either works or it doesnât. They watch it run. They see the sections disappear, or they donât, and they tweak the prompt and try again. Thereâs a verifiable artifact sitting right in front of them.
For the first time, regular people are going to experience AI in the mode where itâs actually good: intent in, working a problem out, and a result you can actually check with your own eyes. Not a summary they have to trust. Not an answer they have to fact-check. A thing that does what they asked, or visibly doesnât.
Thatâs the moment the public perception flips. Not because the marketing got better, but because the use case finally matches what the technology is good at.
Bespoke software, on demand
I think this is the front edge of something much bigger.
For the entire history of software, the economics have forced one program to serve millions of people. The interface is a committee compromise. Every button is there because someone needed it, which means itâs cluttered for everyone. Weâve all learned to mold ourselves around software built for an average user who doesnât exist.
LLMs break that constraint. When generating a working interface costs almost nothing, thereâs no reason the software has to be generic anymore. The natural endpoint is bespoke software for one person, for one task, generated on the spot.
You open your laptop. You say what youâre trying to do. It designs and builds an interface optimized for that â your data, your workflow, your one weird task â and throws it away when youâre done. No download. No settings menu with four hundred options youâll never touch. No learning someone elseâs idea of how the task should go. The software conforms to you instead of the other way around.
Apple didnât ship that this week. They shipped a prompt box in Safari and a prompt box in Shortcuts. But thatâs the same idea in its smallest possible form, handed to the largest possible audience. And once people feel what itâs like to say a thing and get a working thing, theyâre not going back to molding themselves around someone elseâs software.
The engineers already know AI works. The rest of the world is about to find out, not from a keynote, but the first time the browser does exactly what they asked.
Iâd love to be wrong about the timeline, but I donât think I am. Reach out on Mastodon at @evan@coleman.social or Bluesky at @edc.me if you want to argue about it.