One thing I really agree with dhh on (and something I’m genuinely looking forward to!) is the resurgence of native apps.
Cross-platform became so dominant because the same small dev teams had to support users across multiple platforms. Practically they either had to build ONLY for the web or use some kind of web-tech-based framework like Electron.
Agentic coding changes that constraint at a very low level. Teams are no longer limited by whether they have someone who knows how to build for iOS, Android, macOS, etc., or whether they have the bandwidth to maintain multiple native codebases. The cost of supporting multiple platforms starts to fall dramatically.
And I think this is closely related to the thesis behind Omarchy also. Setting up and customizing Linux is historically a lot of friction. If you wanted a system that was personal i.e. NOT (Mac OR PC) you often had to be comfortable troubleshooting obscure issues and spending hours getting everything just right. Don't get me wrong: a lot of people enjoy that friction. But it sucks at so many levels.
Agents lower that barrier. You can want a highly customized system without necessarily becoming an expert in every layer of the stack. If there’s some tweak or workflow that isn’t exposed through a settings menu, you can increasingly just describe what you want and have the system help you build it.
So I think the interesting shift is that software becomes less constrained by what the average team or individual programmer has the bandwidth to build and maintain. That could make both native apps and highly personalized computing environments much more viable again instead of the web-slop that we've become accustomed to over the past 20 years. I really see parallels between how the Mac empowered creatives in the 80s and agentic coding today.
As much as i'd love for this to be true, it is not. Teams need to support their native apps, just because you prompted your way into some code doesn't mean your team is able to support it. The constraints are the same, if no one in your team knows how to build an maintain a native iOS app and their core knowledge is TypeScript and web, vibing it with agents won't get you past your first release (and not even that)
I don't really mean “give a team of TypeScript devs an agent and suddenly they can ship and maintain a production iOS app.” Expertise and ownership still matter, especially for something you have to support for years.
I'm talking more about agents as a force multiplier for teams who do have engineering experience. They reduce the amount of specialized knowledge, time, and coordination required to get something built and maintained. The constraint gets meaningfully weaker.
An experienced engineer who understands software architecture, debugging, product constraints, etc. but isn't an expert in every native platform can increasingly use an agent to bridge some of those gaps. That's very different from vibecoding your way into production.
fwiw I think we're still very early in the process of re-thinking about how teams are organized and what skill sets they need.
Really interesting experiments that are actually geared towards how these models interact with the "real" world.
It seems to me that we are on the fast ramp to making the paperclip maximizer a reality. imo the most likely "dystopian" future that we'll get to see. These models have no concept of their RL env sandboxes and the real world. Extremely interesting to see how they compete in trying to get finite resources and work with constrained supply chains.
I feel like the two companion pages - AI agents explained [0] and Agentic AI examples [1] - are kinda more telling than the Muse personal agent itself? I don't quite get why we have these two posts at all. A personal agent is more show than tell. Live demos with an actual agent doing day to day things would have been the ideal thing to show off. A version of the infamous Apple Intelligence ad but live.
At any rate, it would be interesting to see what the actual capabilities would be. The Meta AI integration with WhatsApp actually sucks so bad. Hope it's better than that.
This reminds of when I was in school and we had 3 categories of notebooks.
1. A "rough" notebook to jot down notes
2. A "classwork" notebook to present those notes properly to the teacher and get them corrected and
3. A "homework" notebook to finish homework assignments that used to be given
It's quite a discipline to jot things down in the rough work book and then write out a "neat" version in the class work book.
I stopped doing it once I finished school and realized I didn't really need to do it anymore once I understood what I was writing out. But maybe it’s a habit worth returning to.
> Apple’s always done their best work when they’re the second mover.
People say Apple does its best work as a “second mover,” but that misses the actual pattern: Apple builds great products when leadership is solving their own problems.
The Mac, iPod, iPhone, and iPad weren’t just refinements of existing products. They were devices Steve Jobs personally wanted to use and couldn’t find elsewhere. The man saw the GUI at Xerox and saw how anyone could use a computer without remembering arcane commands. So he drove the development of the Mac. He was using a shitty mobile phone, saw the opportunity and had the iPhone developed. Same with the early Apple Watch (first post-Jobs new product line), which reflected Jony Ive’s fashion ambitions; once he left, it evolved into what current leadership actually uses: a high-end fitness tracker.
The stagnation we're seeing now isn’t about Apple losing its “second-mover magic.” It’s that leadership doesn’t feel an unmet need that demands a new device. None of Vision Pro, Siri, Apple Intelligence or even macOS itself anymore appear to be products the execs themselves rely on deeply, and it shows. Apple excels when it scratches its own itch and right now, it doesn’t seem to have one.
I think this is an interesting take that really reflects the saturation of the wider problem space of society. Much of the stuff that we could potentially need, we already have. It will be interesting to see what new products are released to the market in the next ten or so years which substantially change the way that we use technology.
I understand the feeling. There is a huge asymmetry between individual contributors and huge profitable companies.
But I think a frame shift that might help is that you're not actually donating your time to LMAX (or whoever). You're instead contributing to make software that you've already benefited from become better. Any open source library represents many multiple developer-years that you've benefited from and are using for free. When you contribute back, you're participating in an exchange that started when you first used their library, not making a one-way donation.
> They wouldn't have merged my code in if they didn't think it had some amount of value, and if they think it has value then they should pay me.
This can easily be flipped: you wouldn't have contributed if their software didn't add value to your life first and so you should pay them to use Disruptor.
Neither framing quite captures what's happening. You're not in an exchange with LMAX but maintaining a commons you're already part of. You wouldn't feel taken advantage of when you reshelve a book properly at a public library so why feel bad about this?
Like Alan Kay said about software: Simple things should be simple, complex things should be possible.
The thing is this takes a lot of resources to get right. FOSS developers simply don't have the wherewithal - money, inclination or taste - to do this. So, by default, there are no simple things. Everything's complex, everything needs training. And this is okay because the main users of FOSS software is others of a similar bend as the developers themselves.
I think we're returning to CLIs mostly because typing remains one of the fastest ways we can communicate with our computers. The traditional limitation was that CLIs required users to know exactly what they wanted the computer to do. This meant learning all commands, flags etc.
GUIs emerged to make things easier for users to tell their computers what to do. You could just look at the screen and know that File > Save would save the file instead of remembering :w or :wq. They minimized friction and were polished to no end by companies like MSFT and AAPL.
Now that technology has got to a point where our computers now can bridge the gap between what we said and what we meant reasonably well, we can go back to CLIs. We keep the speed and expressiveness of typing but without the old rigidity. I honestly can't wait for the future where we evolve interfaces to things we previously only dreamt of before.
It’s less rigid than a command line but much less predictable than either a CLI or a GUI, with the slightest variation in phrasing sometimes producing very different results even on the same model.
Particularly when you throw in agentic capabilities where it can feel like a roll of the dice if the LLM decides to use a special purpose tool or just wings it and spits out its probabilistic best guess.
True the unpredictability sucks right now. We're in a transition stage where the models can understand intent but cannot constrain the output within some executable space reliably.
The bridge would come from layering natural languages interfaces on top of deterministic backends that actually do the tool calling. We already have models fine-tuned to generate JSON schemas. MCP is a good example of this kind of stuff. It discovers tools and how to use them.
Of course, the real bottle neck would be running a model capable of this locally. I can't run any of models actually capable of this on a typical machine. Till then, we're effectively digital serfs.
I think this piece makes a fair and important point about LLM hype and the need to treat it as a normal technology rather than a cult movement. The over-the-top marketing and constant “AI will change everything” drumbeat can definitely obscures the more grounded, practical ways it can be used day-to-day.
That said, every major technology wave has needed a similar level of push, hype, and momentum to reach mass adoption. The Internet existed for decades before the public knew what to do with it. AOL gave such a huge push with the “You’ve got mail”, endless free trial CDs and an almost manic push to bring it into homes for it to become the foundation of modern life. The same was true of personal computers: early machines like the Apple II or IBM PC were expensive, clunky, and had little practical software. But without the evangelism, marketing, and cultural hype that surrounded them, the entire ecosystem might never have matured. So while the AI frenzy can feel excessive, some level of over-excitement may be what turns the technology from niche tools into something broadly accessible and transformative — just as it did for the web and the PC before it.
> every major technology wave has needed a similar level of push, hype, and momentum to reach mass adoption
People were standing in line for the first iPhone. Gmail had a waiting list. Tesla sold EVs far faster than they could make them.
On the other hand, I now literally have AI icons blinking in several apps, begging to be used. This isn't a regular marketing push of a brand-new product, it is companies desperately trying to justify their billions of dollars of sunk costs by bolting AI onto their existing products.
Part of the reason for the blinking icon begging to be used is because AI chat is a new interface being grafted onto existing products. It's difficult to get people to make the habit of using a different interface to a familiar product. That's why google can get people to use AI by injecting the response above the results. But facebook messenger for example throws a metaai icon in the lower right corner because they cant figure out a natural way to create discovery that isnt intrusive, and is able to silently hijack some existing muscle memory.
That mass adoption has brought in the normalisation of automated surveillance, attention farming and arguably lowered peoples’ tolerance to “the other”. I’m currently not convinced it’s a net positive. Perhaps things would have gone better if the adoption had been slower.
I think this is exactly the right intuition. I think people hopelessly underestimate the human tendency to do nothing. We have this idea that if an innovation is good enough it should “sell itself”, and that’s almost never true because across all organizations, it’s almost always safer to do nothing, adopt nothing, keep doing what you’re doing.
No one gets fired for suggesting no change.
It takes a special level of hype where “doing nothing” is no longer the sensible choice.
Do I wish this hype was spread around to other technologies that are also awesome, of course. I’d love to help someone figure out a way to do that but as of now, we don’t know how to do that. Humans are very bad at holding two different ideas in their head.
But we don't need to do anything. We don't need AI and so we don't need a push for it. If AI is just a "normal" technology that has some legitimate uses, it doesn't need a huge boost, it doesn't need any hype at all. It can just be slowly discovered and used by the people who have a legitimate use for it. Doing nothing is often a good move.
“ technology that has some legitimate uses, it doesn't need a huge boost”
That’s what I’m disagreeing with. “Legitimate uses” isn’t something just hanging out in the ether to attach itself to useful technology it happens via a grinding sales process and big industry wide cultural changes.
People don’t like change.
I think AI and its knock-on effects in robotics will have massive productivity boosts in industries where productivity has been lagging for years. It will take decades and multiple boom-busts to happen to drag the population into change but it’ll happen.
I guess what I'd say is that if that grinding sales process and those industry-wide cultural changes have all the negative effects we're seeing with AI, then we shouldn't make that trade. There is simply no urgent need to adopt AI, and the frenzied push to adopt it anyway is actively harmful.
Cross-platform became so dominant because the same small dev teams had to support users across multiple platforms. Practically they either had to build ONLY for the web or use some kind of web-tech-based framework like Electron.
Agentic coding changes that constraint at a very low level. Teams are no longer limited by whether they have someone who knows how to build for iOS, Android, macOS, etc., or whether they have the bandwidth to maintain multiple native codebases. The cost of supporting multiple platforms starts to fall dramatically.
And I think this is closely related to the thesis behind Omarchy also. Setting up and customizing Linux is historically a lot of friction. If you wanted a system that was personal i.e. NOT (Mac OR PC) you often had to be comfortable troubleshooting obscure issues and spending hours getting everything just right. Don't get me wrong: a lot of people enjoy that friction. But it sucks at so many levels.
Agents lower that barrier. You can want a highly customized system without necessarily becoming an expert in every layer of the stack. If there’s some tweak or workflow that isn’t exposed through a settings menu, you can increasingly just describe what you want and have the system help you build it.
So I think the interesting shift is that software becomes less constrained by what the average team or individual programmer has the bandwidth to build and maintain. That could make both native apps and highly personalized computing environments much more viable again instead of the web-slop that we've become accustomed to over the past 20 years. I really see parallels between how the Mac empowered creatives in the 80s and agentic coding today.
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