Nobody starts in the right place. You don’t begin with the correct tool and work sensibly within its constraints until you organically graduate to a more capable one. That is not how obsession works. Obsession works by taking whatever is available and pressing on it until it either breaks or reveals something. The machine’s limits become a map of the territory. You learn what computing actually costs by paying too much of it on hardware that can barely afford it.

I know this because I was running Final Cut Pro X on a 2006 Core 2 Duo iMac with 3GB RAM and 120GB of spinning rust. I was nine. I had no business doing this. I did it every day after school until my parents made me go to bed.

I find this to be the defining difference between the “devices” (the phone, the tablet, the watch, etc.) and a computer: the computer is a blank slate, it is what you want it to be. It’s a portal to possibilities. The limit is how far you’re willing to tinker with it. The new devices — they’re more usable? Easier? Accessible to everyone? Harder to fuck up? — they have always felt optimised for consumption.

What if all of that immense bureaucracy, the endless processes, the mind-boggling range of costs that you need to make the computer compute, just goes poof? That doesn’t mean that the software will be good. But most software today is not good. It simply means that products could go to market very quickly.

And for lots of users, that’s going to be fine. People don’t judge A.I. code the same way they judge slop articles or glazed videos. They’re not looking for the human connection of art. They’re looking to achieve a goal. Code just has to work.

Andy Coenen:

Up to this point, writing software has been an arcane craft practiced by highly specialized artisans. Very few people can do it, and even fewer people can do it well. […]

Before the Industrial Revolution, the average person owned only a few pairs of clothes, and many people spent the majority of their lives making those clothes by hand. Today, very few people actually make clothes but there are thousands of apparel companies for every type of activity – from skiing to nursing to firefighting – that would have been unimaginable before. Similarly, the Software Industrial Revolution will lead to an explosion of new bespoke software across every industry and niche, and the fact that we’ll no longer build the software by hand means that we’ll build and use much more of it.

Matt Shumer:

I am no longer needed for the actual technical work of my job. I describe what I want built, in plain English, and it just… appears. Not a rough draft I need to fix. The finished thing. I tell the AI what I want, walk away from my computer for four hours, and come back to find the work done. Done well, done better than I would have done it myself, with no corrections needed. A couple of months ago, I was going back and forth with the AI, guiding it, making edits. Now I just describe the outcome and leave.

Nolan Lawson:

Someday years from now we will look back on the era when we were the last generation to code by hand. We’ll laugh and explain to our grandkids how silly it was that we typed out JavaScript syntax with our fingers. But secretly we’ll miss it.

Greg Knauss:

There are a thousand factors at play here (most of which are still in motion) but for plenty of small-scale, snap-together projects, something like Anthropic’s Claude Code or OpenAI’s Codex will be good enough, for economically-viable values of both “good” and “enough.” They’ll either burp up scripts that simply wouldn’t exist otherwise, or do (some of) the work of (some) junior or mid-level coders (somewhat) faster and cheaper. But the direction things are headed seems pretty clear.

Is the code any good? I don’t know. Who cares? Nobody looks at it anyway. AI produces a result, and results are what matter, and if you’re waiting for quality to factor significantly into that equation, I’ve got some bad news about the last 40 years of professional software development for you.

Tom Blomfield (Monzo’s founder):

I think we’re going to have a lot more software in the future. Normal, non-technical people will be able to summon up a new custom-written software program to solve a trivial daily task much the same way they might use a spreadsheet to make a list or do simple sums today.

Here’s the problem. That increased demand will be met with increased supply – from rapidly scaling AI. I just don’t think there will be any point in a human writing code for very much longer. My guess is that AI will soon be provably and obviously better at basically every facet of it. We will still have senior software engineers supervising the AI for many years because it makes humans feel safer. But they will eventually be like the conductors on self-driving trams; they are mainly there to make people feel better. This is the point that makes software engineers really angry, I think.

Steven Sinofsky:

There will be more software than ever before. This is not just because of AI coding or agents building products or whatever. It is because we are nowhere near meeting the demand for what software can do. This holds for software I use on my own, software a business needs, software an organization needs, or software to control the explosion of devices that replace every analog device with an automated one.

The animation was designed to mimic human breathing at 12 breaths per minute, and feel comforting and soothing.

I understand why it’s gone — our devices are always on, it’s not as much of a concern anymore — but it was the kind of nice little detail that set Apple apart, and made it more human. Everything looks so serious now.

Authority used to be the organizing principle of information, and thus the media. You earned attention by being right, by being first in discovery, or by being big enough to be the default. That world is gone. The new and current organizing principle of information is velocity.

What matters now is how fast something moves through the network: how quickly it is clicked, shared, quoted, replied to, remixed, and replaced. In a system tuned for speed, authority is ornamental. The network rewards motion first and judgment later, if ever. Perhaps that’s why you feel you can’t discern between truths, half-truths, and lies.

The network rewards reactions. Reacting precludes thinking: few people have the wit or knowledge to share something valuable on the spot, the rest sound like an indistinct, self-pleasing noise that contributes nothing.

This goes beyond media. People are getting sloppier at work, with Slack encouraging fast replies at any moment. They’re getting sloppier in their personal lives, where the expectation is to be reachable and ready at all times.

The network behaves like a gobbling No-Face because the network is designed to behave as such. All of the new popular social media platforms offer more of the same. What’s the point?

For forty years, Excel was the undisputed king of general-purpose knowledge work. It separated the savvy from the rest in every white-collar function on the planet. It became the lingua franca of finance and accounting, and then quietly colonized every domain. Entire businesses still run on spreadsheets attached to emails. […]

It will be harder to differentiate from Claude Code than it ever was to differentiate from Excel, because Claude Code is more general-purpose, more composable, more scalable, and improving every day, not at some release cycle cadence. UX is less meaningful when agent delivers outcomes. Thus, recent UX innovations are happening mostly for alleviating the pain of managing agent swarms, etc.

I recently found myself making the same comparison in a discussion with a friend who is skeptical most will have the patience to learn how to build apps with AI, or have the need to.

I’m always amazed by how much and how well the average person knows Excel — the extent they’re willing to suffer to bend the tool to their will. So many companies run on spreadsheets cobbled together in a fashion not dissimilar to vibe coding. Quite a few even use them for their personal lives (nuts, if you ask me)!

I find it funny that AIs have inherited this hallucination from us. I’m reminded of this surreal clip from “How to with John Wilson” on the Mandela effect. Our AIs are like the guy in that clip.

This is the next step in responsive design and the blueprints are lurking all around us. The coding agents now let you add skills — simple descriptions of how to accomplish a task written in natural language. You might explain to your agent how to get data from an internal API to help you create your quarterly update, for example. But if you really want a great look at what the future may hold, try this: on an iPhone or Mac, open the Shortcuts app and start searching through the available commands exposed by each app you have installed. There, you’ll find a remarkably clear visualization of all the atomic components of an app’s capabilities. All the nouns and verbs.

Imagine where software could go if something like this gets built into the OS — an evolved Shortcuts, with a smarter Siri (lol) able to build the app that you need exactly how you need it.

I’m not sure what that means for apps as they are now, built by professionals. Will we have more software, but fewer developers? Will apps as prepackaged products lose importance over what they enable — the skills or data sources they add?

The AI chat interface is proliferating across apps, but it seems more likely we will be bringing our own favourite assistant to them, pulling and accessing specific capabilities. The acronym AX, standing for agent experience, started appearing in the past year to describe how an agent interacts with a product as a user. The question is: will they be the primary user?

Mathias Biilmann (Netlify CEO), clarifying what AX can stand for:

Is it simple for an agent to get access to operating a platform on behalf of a user? Are there clean, well described APIs that agents can operate? Are there machine-ready documentation and context for LLMs and agents to properly use the available platform and SDKs? Addressing the distinct needs of agents through better AX, will improve their usefulness for the benefit of the human user. Too many companies are focusing on adding shallow AI features all over their products or building yet another AI agent. The real breakthrough will be thinking about how your customers’ favorite agents can help them derive more value from your product. This requires thinking deeply about agents as a persona your team is building and developing for.

When an article says “some scientists think” then remember this: I, a scientist, once thought I could fit a whole orange in my mouth. I could, it turns out, get it in there, but I hadn’t given sufficient thought to the reverse operation.

You can’t make everything obvious because you have limited resources. I’m not talking money—although that may be part of it too. I’m primarily talking screen real estate, attention span, comprehension, etc.

Making something obvious is expensive because it often means you have to make a whole bunch of other things less obvious. Obvious dominates and only one thing can truly dominate at a time. It may be worth it to make that one thing completely obvious, but it’s still expensive.