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The the part that's really nice about it is because I do a lot of Mac software, agents love to take over my screen and click around and if you put that in their own if you give them their own machine, it will not bother you. Otherwise, you'll fight with the agent for the mouse cursor.
Every lab will sell you an agent. Open claw is the alternative. Open source runs everywhere, works with any model. And if you run local models, your data never has to leave your device.
Second of all is I hope you worked on your personal brand and on visibility because in this day and age there's so much noise out there that your hardest problem is not the tech, it's not the software, not even the people. The hardest problem now is like getting eyeballs.
If you count all the permutations, you can write all the tests you want. It is impossible to cover all of these and not break things from time to time. It is infinitely harder to evolve software that has users.
And most of them really sent reports that their agent produced without actually even testing it. I would I would take a stronger sense of explaining what are the parts that we guarantee and what are the parts that will not be fixed because that that's not our security boundary.
In addition to reliability issues, it often engenders a mind-numbing workflow and an environment where junior developers will never acquire the expertise to become senior developers capable of designing complex systems.
Given the high cost of errors, you need to have a very high level of safety and a very high level of confidence on day one before you deploy your first robot, before you drive your your first autonomous mile.
So, a deployment of your agent uh in the real world generates data. That data then grounds the simulator and makes it more realistic. The simulator generates harder edge cases for the critic to score and for the agent to learn from.
absolutely agree that product skills are probably the most durable. My build would just be there's a lot of people who have the title PM who haven't spent a lot of time building those skills in the last 5 years, but have gotten really good at communicating frameworks to leadership.
Technologies from our community - CRDTs, sync engines, universal version control, and good old-fashioned open protocols and file formats - can give a nation more independence and control over its own critical software infrastructure.
So we've always told computer scientists from the very beginning that really it's really important to specify what it is, what's the software that you're writing is trying to accomplish before then going and writing it. And so now we actually have agent-based systems that can do the writing, but the importance of specifying what what it is you want has actually gone up because before you'd be handing it off to a very intelligent human who maybe has context or can ask you follow-up questions.
Um, and to give you an example of a a a use of a coding agent that works extremely well is you can ask today's models to translate software from one computer language to another very effectively because in that case you actually have a incredibly detailed specification.
I predict that in the next 10 years software development will survive, but it will become like any other white-collar professional work. No more $200,000 salaries, unlimited vacation, or incredible employee bargaining power.
But I think it is more useful for most developers to have an exposure to like what math has in the various fields versus just going all in every single field when they see them, right? You've got to know what's available to know what's most useful for you. And most math will not be useful for you.
while we are a lot better at iterating than other fields, we're worse at the planning part. Like we still need to do some kind of planning before we iterate and we just aren't as good as those other fields.
Software is kind of unique in having the third kind of the practitioner conference where we are just meeting to get better at what we do. We also are really the only kind to really focus heavily on like open source in making our knowledge freely available.
we don't believe in a world where these models are so expensive that, you know, they get rationed only for the most wealthy of developers and and companies.
Superlogical will begin by shipping a terminal multiplexer. I'm pouring my years of experience building a terminal and studying the potential and limitations of other multiplexers into something new, powerful, and, of course, fast.
At boom we need far more software engineers in a postAI world than we need in a pre-AI world. Why? Because the cost of software development has dropped. anybody including hardware engineers can now become a coder and we need software engineers to make sure the architectures are right and make sense and are coherent.
The key thing is to make hardware development look more like software development to reduce the cost of iteration both in the world of bits and in the world of atoms.
But great airplanes are incredibly integrated and everything affects everything else. uh the the best airplane design is interplay of propulsion, of aerodynamics, of structures, of all kinds of optimizations, how you fit the systems into it.
We said all of this engineering that historically exists in spreadsheets really should exist in software. The spreadsheet engineering is like it's like baby software.
we're on the path to fully automating the maintenance of our apps by doing this. And this is again hundreds of agents running every day, sometimes thousands of agents every day. It's doing the work of you know, dozens or hundreds of engineers.
I I think this is sort of the crazy thing about building on models. It's just so different than all the engineering that I've ever done. Like in the past when you built on systems, you built these like big beautiful systems and you really think about the system design up front. You have like a big suite of unit tests. You think about everything and you know, like a re-architecture is a big project.
we want we want to encourage everybody and every company to build their own AIs. And and and who knows what innovation will come from the fact that it's open source.
LG makes the best TVs, end of story, but their software is shit and spies on you, NEVER connect them to the internet/WiFi, instead buy an Apple TV box and connect that, that doesn't spy on you and has no ads, then connect it with HDMI and you're good, also no annoying LG TV updates
LG makes the best TVs, end of story, but their software is shit and spies on you, NEVER connect them to the internet/WiFi, instead buy an Apple TV box and connect that, that doesn't spy on you and has no ads, then connect it with HDMI and you're good, also no annoying LG TV updates
So AI has made everybody just as capable as everyone else, it equalized everyone in the world, as in everyone can make everything (software, music, images, art etc) now and everyone is equal, at least in the digital realm now
I read a bunch of blog posts about how it is totally fine to use SQLite in production for a small site and I think it is totally fine, but what I did not fully appreciate is that SQLite is still a database, databases are complicated, and I do not know a lot about operating databases.
So I think the the thing I'm most excited is actually like what we call like iterated loops or like slow loops where we basically have a cron job. We have the loop the the the structure of the loop is really easy. It's like run this llinter fix one thing commit and push and then we run that every night in our GitHub actions and we wake up every morning to one PR that makes the codebase a little bit better.
yes it will catch things and it will raise your floor but I don't believe like the model writing the code is the same model reading the code and if you ask a model hey is this code good it's going to be like oh yeah it's great comprehensive it's got unit tests
We tried this. We built a lights off software factory in July of 2025 and by November we had shut it down. I think it takes about three to six months of you shipping all the time with nobody reading the code before you realize like, wow, this is getting way worse and it's easier to start over than it is to fix it.
there's a different kind of intuition that you that you develop over years as a software engineer and uh there's many categories of it but the one I'll I'll call attention to that is like a thing that you cannot teach you cannot do you cannot learn in a textbook. The only way to learn it is like I know bad patterns in software because I have debugged them at three in the morning.
And at the end of the day, they're all like different ways to pass tokens into a model and ask it to produce usually some structured output. And understanding that is a lot more powerful than trying to learn memory and trying to pick some agent framework off the shelf and some memory framework off the shelf.
All you really need today to build a business is 100% free open source software that charges you $0/mo a VPS server an API to do some required AI stuff some R2/S3 file hosting
I did try Dell's laptops a few years back, didn't like what I saw, and ended up spending a few years using Framework computers instead (they're still great too).
So beforehand because of this social divide between programmers and testers. There was a lot of incentive for the testers to have their own language. This is my tool. I know how to run it. I'm going to run it.
The agile manifesto is the intersection of the ideas of the people in the room. I think there's a lot more to software development than is contained in the manifesto. And I've written books and books and books about what I think those things are.
what I don't like about it I didn't like about it then and still don't like about it is it's not defensible. Nobody's going to say I'm not agile. Oh no, I prefer rigid development. Oh, I prefer inflexible development. No, everybody's going to say that they're agile, which extreme doesn't have that problem.
which is why when I see manifestos today I'm just like too soon. Not a bad idea. Would love to have one just too soon. It took 15 years for the technical change of object-oriented programming to come before we could say here are the consequences of it. Here's how in a simple way we can express how to effectively use this technology that we've been using day in and day out for 15 years. The genie comes along. People are like, "Well, what's the new manifesto? It's just not manifesto time yet.
And then there were people who used it as a moral cudgel. Like you should be if you're not using TDD, you're not professional. And that's just such People can write very good software with a wide variety of workflows.
I agree with @theo completely, it's clear to me this is where it's going, also seeing @karpathy with Claude moving to the cloud (via Slack etc), I think AI "agents" and AI coding will operate on servers / from the cloud first
I am not affiliated with any of the tools mentioned in this article, but one nice thing about Ollama is that they also optionally support open-weight models hosted in the cloud
Yeah, so I would say over the last 6 months actually we've been cranking a lot of features out a lot of code out. Most of it has been written by AI at this point. And before that really wasn't the case. I was actually a really big AI hater for a long time
And even the cost issue with AI is probably going to be like once the subsidies start running out, which we're starting to see, I think that's going to be a really big issue where maybe all these companies that embraced AI programming are now going to like cut back on it.
I think a lot of people, especially students, are unfortunately learning everything through LLMs. So a lot of that isn't really learning, they're just kind of cheating and they're just doing everything like that. And then they lose a lot of their skills
Like every single time there's just like the big innovation like cloud computing, like higher level programming languages, for whatever reason things do not like it doesn't lead to fewer programmers. And I would have expected it would have.
Zig is exceptional software: ambitious, practical, independent, and unusually serious about quality. Ghostty exists in large part because Zig made it possible for me to build the kind of software I wanted to build. This is why I support Zig.
And eventually, you have to really move into a full stack. So, not just a silicon, you need to have a software, and some of the customer asked me, "Give me the whole rack." So, there's a system that you have to build.
there there's a one question we got to back up and really explore which is is AI a new platform and I would argue that it is not yet a new platform. It is an important technology.
Users can't see the code, so UI is the only way for them to judge the quality of the app. If UI looks good, that means developers had time to polish it, which means that they probably spent a comparable amount of time to iron out the code.
In terms of science, I think it really makes sense and we're deeply committed to open source. Um, there are obviously interesting considerations on this that are important too because there's a lot of considerations around biosafety and things like that that we're going to need to balance and think through how to how to handle.
the competitive dynamic in China is more intense because it's more intense. Everyone's chosen to go open source and that creates a system that in my mind is capable of innovating far faster than the competitive system we have here. All the models learn from one another.
My Dad and I tested all the PiKVM models, and I like everything but the price. I 100% recommend them, especially since you're directly supporting the folks who wrote the software.
They just recently released a report, and I think like you really have to squint to see anything happening. Like basically, if you want to take kind of like uh an an approach across the entire economy and looking at even looking at like software engineering, like the most exposed sort of sectors, there's just like not really anything going on. There might be a little bit of a signal about like junior developers getting jobs less than before, and that but that's like a less than before rather than a level shift.
And so you have been part of the change to other industries and other people yourself. What did you think about that? Did you even think about it at all? So let's not be surprised if you find no sympathy from all the other professions that you've helped force change upon.
It's like maybe you don't understand what the job has always been. We are trying to solve human problems and we use whatever technology is required. In some cases, the technology happens to be software and software ain't required for every human endeavor.
I'm watching people write these huge markdown files to give the agent context. How about you write documentation to give me context so I can have fully working examples.
and it turns out people kind of over glorify entrepreneurship. I think a lot of people believe there is tremendous upside, right? the type of entrepreneurship we talk about with software companies, the the upside is crazy. But when you're doing like selling parts or service business, unless you plan to open lots of stores and you know grow a larger employee base, it's not the same growth trajectory as software companies.
The thing that makes Kubernetes powerful, there's a data model. We gave infrastructure a type system. So instead of imperative shell scripts, you finally had types.
So often with new software paradigms, what looks like inevitability turns out to be just design failure that can be solved with the right guardrails or affordances or system instructions.
But you if you also become an expert in a specific industry, that's like a deadly combo. Um if you are like just pick any industry, let's say let's say farming, let's say you understand that farming industry really well and you're also a decent software engineer, you're probably like the top 10 people in the world for that combination that the whole industry will want to hire.
The the biggest advantage to in DevTools is the fact that everyone working at DevTools is a programmer and programmers are horrible at B2C products. They don't realize DevTools are B2C products.
The thing that I find interesting is that's not novel. This has been the thing we've always been trying to do forever. How do we get a junior engineer to ship code safely without breaking stuff? Right? How do we make patterns in the codebase? How do we make tests? Like it's it's all the old stuff that we've always wanted to do.
The second is that most of the work that you do is actually going to happen on your computer in an environment like Codex or Cloud Co-work that becomes the sort of operating system for it becomes the sort of operating system for how how you do all of your work, whether that's your email, the documents you create, like all that kind of stuff.
And what you see when we work with them internally is now they're just like they're just making pull pull requests. Like they don't they don't need to hand it off as much. Sometimes they do but like a lot of times they just make pull requests and it's like the thing is built and that's it and I think that's incredible for the way that companies work
And I think that Cursor has at least so far more distinctly chosen a lane. Like they're more distinctly choosing to be a for programmers. And that may limit how far they get in here.
And what this is is that in the guide level explanation, you explain your feature as if you were writing a guide as if the feature already existed. And in the reference level explanation, you explain your feature again as if it already existed, but as if it would be in the language reference instead of a tutorial.
My opinion is that the least mature area is front end. There have been some attempts to compile Rust to Web Assembly and then run it on the web as a front end as a replacement for TypeScript. But if I was writing a web server, I would totally use Rust for the back end and TypeScript for the front end. I would not really go the web assembly route.
I think where Rust is really unique is in the combination of things. So on one hand, it it doesn't have a garbage collector and it it's usable in low-level context like the Linux kernel or firmware or whatever.
I think this is kind of leads to another way that Rust really helps with reliability, which is that if you're refactoring, I think Rust is really good at telling you all the places you need to update. I've done this sometimes where I would refactor something. I change the code. I change the return type or whatever it is, and then I just fix the compiler errors and until the compiler stops shouting. And then once I've done that, I've updated every place I need to update.
As reasoning models and agent workflows keep more tokens around (for longer), KV-cache size, memory traffic, and attention cost quickly become the main constraints, and LLM developers are adding a growing number of architecture tricks to reduce those costs.
unless the code is completely out of your control, the need for mocking often indicates a design problem-consider refactoring to make the code easier to test directly.
I ended up making this site with Tailwind CSS, and it helped me make a site I felt pretty happy with my minimal CSS skills and just 2 evenings of work!
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I’m a lot better at CSS than I was when I started using Tailwind
Ultimately Tailwind is limiting: if you want to do Weird Stuff in your CSS, it’s not always possible with Tailwind. Those limits can be extremely useful (a lot of this post is about me reimplementing some of Tailwind’s limits!) but at this point I’d like to be able to pick and choose.
And quite honestly, language design is 90% the same and 10% new for for pretty much every language. Every language you build still has to have a compiler. Compiler is still built in a pretty much the same way.
You know, there's open source and there's open development. And and and we were technically open source in the beginning, but it was not open development. We would sort of lob the source code out in this repository and scrape the issues off of that and put it into our internal issue tracker.
So, if we're checking 99% instead of 100%, well, heck, that's better than the 0% that JavaScript checked, right? And it gives you like language features that no other languages can provide because they can't get to 100%.
And so everything is lazy and deferred and functional and reusable inside the compiler. And it's a very different way of writing compilers than than what the textbooks will traditionally teach you.
At even $500/kg, launch cost is only 5% of the total satellite deployment cost, so a lunar mass driver is unlikely to drastically improve the economics of space-based AI, by reducing launch costs.
Going forward, I think the future will be filled with software abundance, or, more accurately, I'd call it "software proliferation". That is, centralized development will be history. Software will be highly personalized, especially for open source software.
the more that we could build a platform uh around our business, the more that we could build an ecosystem with creators and developers, the harder it would be for folks uh to to just copy that.
network effects are certainly an important piece of the puzzle for sure, um but I don't think they're enough when it comes to these sorts of software uh you know, software cloning.
As the software industry is largely driven by trends and fashion, React's "cool factor" led to a mass amnesia regarding how to make normal, well-designed web apps made of HTML with a sprinkling of scripting on top and everything became one big tangled, brittle mass of Javascript that completely keeled over when scripting wasn't available.
local-first software, which is this idea that we want to take away a bit of the power from cloud operators and give it back to end users. So, end users should be more in control of their own data and less dependent on cloud services for providing the applications and the data that that the users need.
software as a service businesses, for example the whole reason why they can charge a subscription is because they are able to essentially hold a gun to the customer's head and say, "Pay us at your subscription, otherwise we will delete all your data."
And now suddenly people are building databases on top of object stores, for example. And now the replication happens at the object store level, no longer at the database level.
Maybe as AI writes more and more code of our code, it's less about like the details of how you express logic in a particular programming language and much more about those kinds of high-level trade-offs.
Ensuring that moving, borrowing, and sharing don't break the illusion is surprisingly easy to do with a static type system, and surprisingly hard to do with a dynamic type system, or at least hard to do cheaply.
I actually see the opposite of what people see I think the number of agents are going to grow exponentially. The number of tool users are going to grow exponentially and it's very likely that the number of instances of all these tools are going to skyrocket.
We have got to acknowledge that most of the advanc advances in AI came out of algorithm advances not just the raw hardware. Now if most advances came from algorithms and computer science and programming tell me that their army of AI researchers is not their fundamental advantage.
But I have come to realize that as a web developer, Linux is just better. Linux is just better. It's closer to what I deploy on. The tooling is actually phenomenal.
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anyone who's working with the web, who's working with Ruby, who's doing DevOps, they should be on Linux because first of all, that's closer to what we deploy.
I love chiseling my code and the way I use AI is in a separate window. I don't let it drive my code. I've tried that. I've tried the cursors and the wind surfaces and I don't enjoy that way of writing. And one of the reasons I don't enjoy that way of writing is I can literally feel competence draining out of my fingers.
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I will now start any project I'm starting with. I'm starting agent first and that's a massive shift
Where I get fired up, and this ties back to the AI discussion, is when that's turned into this meme, that programmers no longer have to be competent. I mean the AI is gonna figure it out. The generators is gonna figure it out. I don't need to know SQL, active record is gonna abstract it away from me. No, no, no dude, hold up. The path here is competence.
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really good programmers are currently more valuable than ever because they're the ones who are able to get the most out of the AI acceleration.
The joy of a programmer, of me as a programmer, is to type the code myself. If I elevate myself, if I promote myself out of programming, I turn myself into a project manager. A project manager of a murder of AI crows as I wrote the other day.
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I have been hyper accelerated as a programmer. It's a different kind of programmer, but it still has the same affinity to aesthetics, at least when I'm producing Ruby code.
So certainly one thing that a lot of them seem to be bottlenecked on is now having interesting ideas and in particular having interesting design ideas.
which is that the the Venn diagram of developer experience and agent experience is a circle. And the point here is that, you know, what we do that that's good for the agents is good for the humans and vice versa. I'm hearing a lot of feedback saying, "Yeah, actually, if you have well-modularized code, that actually makes it easy for the agents to work with."
Um I think another similarity is I mean, the core notions uh behind Agile and extreme programming are solid and good, but a huge snake oil industry appeared around it, the Agile industrial complex as I like to refer to it. Um and that will happen. That is happening with AI right now, and it's often hard to see the difference between where is the snake oil and where is the real stuff.
My bet is on the more effective two pizza teams. Um and it it's also some interesting, you know, feedback we're beginning to get in terms of pair programming. I mean, with pair programming, do you say pair programming is the human and the genie? Or is it two humans and and genies? Because if it's two of us, we can control the genies perhaps a little bit better.
For years, it was faster to mock up software than to ship it. Designers stayed "ahead" of engineering with prototypes. Now AI coding agents make development so much faster that the loop has flipped.
none of us wanted to go through that extreme but lots of time when you are under a lot of pressure and no time to react other than just to survive that scale that keep on coming at you, you have to make uh decision that increase uh speed and velocity because speed and velocity allow us to build quick enough to survive
we're trying to crack the next frontier which is how we get that level of productivity increase and output building new features on top of a code base that are older,
But in Vietnam and also in a lot of other Asian countries, people are on the move all the time. Like people are on the motorbike all the time. So, they actually really don't like typing. So, the voice like a lot of the companies in Vietnam actually deploy voice bots before they do uh do chatbot.
I feel like now I can build anything I want. But at the same time, anyone can build anything I want. So, what is the incentive structure for me to do anything?
And organizations have super high pain tolerance. But human-made enterprise codebases take years to get there. The organization slowly evolves along with the complexity in a demented kind of synergy and learns how to deal with it. With agents and a team of 2 humans, you can get to that complexity within weeks.
With an orchestrated army of agents, there is no bottleneck, no human pain. These tiny little harmless booboos suddenly compound at a rate that's unsustainable. You have removed yourself from the loop, so you don't even know that all the innocent booboos have formed a monster of a codebase. You only feel the pain when it's too late.
You can give it a Bash tool so it can ripgrep its way through the codebase. You can give it some queryable codebase index, an LSP server, a vector database. In the end it doesn't matter much. The bigger the codebase, the lower the recall. Low recall means that your agent will, in fact, not find all the code it needs to do a good job.
Worse, you realize that the gazillions of unit, snapshot, and e2e tests you had your clankers write are equally untrustworthy. The only thing that's still a reliable measure of "does this work" is manually testing the product.
And if everything is proprietary, it's hard to do research and it's hard to innovate on top of, around, with. And so… Open source is fundamentally necessary for many industries to join the AI revolution.
right now, that whole front end has been like kind of smooshed because many times we can just like prototype really really rapidly and kind of solidify some of what we're thinking in terms of like ideas and coding. So I fully expect that part of the outer loop is just going to be collapsed as well, right?
There were a handful of people probably managing a security review process or a launch process or a deployment process or, you know, sometimes reviews were a little slow and they got backed up. Well, now we just threw gas on the fire and so all of that is a problem.
And so, like in the immediate term, yeah, we were getting more out, but now our systems, whether technology systems or human systems or processes, are really kind of getting overwhelmed.
I'm going to sound old when I say this, but like I one time had a company tell me, "Oh, well, they have to use that CI/CD system." I'm like 20 bucks, they're just spinning up Jenkins. And they were, right?
I kind of went from 80/20 of like, you know, uh to like 20/80 of writing code by myself versus just delegating to agents. And I don't even think it's 20/80 by now. I think it's a lot more than that. I don't think I've typed like a line of code probably since December basically.
these apps that are on the app store for using these smart home devices, etc. Uh, these shouldn't even exist kind of in a certain sense. Like shouldn't it just be APIs and shouldn't agents be just using it directly?
I do have like cautiously optimistic view of this in software engineering where I do think um it does seem to me like the demand for software will be extremely large. Um and it's just become a lot cheaper.
I simultaneously feel like I'm talking to an extremely brilliant PhD student who's been like a systems programmer for their entire life and a 10-year-old.
So I think the industry just has to reconfigure in so many ways that's like the customer is not the human anymore. It's like agents who are acting on behalf of humans and this refactoring will be will probably be substantial in a certain sense.
OpenAI and Anthropic have both realized that code is the most important thing to optimize the models for, cuz that's where the money is. Like coders will spend $200 a month on a plan if it's good enough, it turns out.
one of the magic tricks about these things is that they they're incredibly consistent. If you've got a code base with a bunch of patterns in, they will follow those patterns almost to a T.
just cuz the test suite passes doesn't mean that the web server will boot. You know, there's there's always a chance that when you actually try in the real world, something's not going to work.
projects are flooded with junk contributions at the moment to the point that people are trying to convince GitHub to disable pull requests, which is something GitHub have never done.
Um, and then you stack on 70 this year, 80 next year, growing to 100 by 2030. You're at like 700 EV tools by the end of the decade. Um, 700 EV tools, three and a half tools per gigawatt. um assuming it's all allocated to AI which it's not but three and a half tools per gigawatt gets you to 200 gigawatts worth of AI chips for the data centers to deploy
As we move from, you know, hey, [clears throat] these companies are selling tokens where they provide the entire uh reasoning chain and all that to uh selling automated, you know, white collar work, right? Automated software engineer, send them the request, they give you the result back and there's a bunch of thinking on the back end that they don't show you. The ability to distill out of American models into Chinese models will be harder.
I believe that data - real-world data, mostly human-generated, validated, and cleaned - is the only reliable moat we have as software founders in the near and mid-term future.
If you run a software business that is purely transformative - that takes incoming data, does something to it, and turns the data back out - that will be a problem.
I think that by the end of this year and we'll see demos of it like right away, but by the end of this year most people will be programming by talking to a face. A face as in a face on the screen.
My my feeling is that probably people have a low tolerance for non-determinism. And these things are fundamentally non-deterministic. So, they can't just go replace customer call center software because they they could be wrong.
If you're a monolith, you're kind of hosed because I told you the ceiling's going up for what they can do, but it ain't ever going to hit your monolith. They will never fit in the context window and you're never going to be able to never in the next 18 months be able to tell a model go fix my monolith. You have to break it up.
I had a lot of my own ego and identity wrapped up in my sort of compiler background. It's all It's interesting, right? But it's it's not useful in any meaningful sense anymore.
But right now I think it's sitting somewhere between half million and five million lines of code, somewhere in there. Probably more on the half million side right now and with the next drop of an Anthropic model, we're probably going to see it jump up to a few million lines.
Polyvagal theory provided me with a coherent framework for understanding why cognitive insight alone often fails when a nervous system is in defensive dominance. In such states, higher-order cortical processes are functionally constrained.
I've always been opinionated about how software should work. Mainly, it should be fast. The bounds of it should be "knowable." The contract you have with it should be "sane" (i.e., you just own it).
With Claude, I've built a host of software like this. Mostly small tools for myself — programs that instantly append copy buffers to text files (I keep a running file of nice things people write to me called notapieceofshit.txt) or quickly perform live currency conversions.
But but that's actually a very weak criterion, right? People thought I was saying like we won't need 90% of the software engineers. Those things are worlds apart, right?
But the quality of these systems isn't just in the code they write. It's also in the code I don't have to write. And maybe more importantly, their actual value is in the code I would never have written, or could never have written, or never would have wanted to write.
It’s actually how good they are at programming is almost a burden in their ability to empathize with the system that’s starting from scratch. It’s a totally new paradigm of, like, how to program. You really, really have to empathize.
building a third-party client to read and route messages is a gray area in their terms of service, and perhaps only partially supported in their API surfaces.
I think that there will be lots of work for us cleaning up after the slop, but if you know what you're doing AI augmented development is going to get you some amazing results
As high-level programming cedes way to the prose compiler, making your goals and specs well understood to the ambiguity loop and showing good judgment is going to matter more than ever.
The Moonlight client is available for virtually every platform: Mac, iOS, Android, and of course Linux. That means no need to dual boot to enjoy the best games at the highest fidelity.
there should be no way to get a big company like a public SAS company Unless NR is greater than 100, like otherwise cancellation should just win. And that is in fact the case.
But with today's AI coding agents, building software is remarkably easy. So instead of handing over static assets and static guidelines, designers can deliver custom software. Tools that let clients create their own on-brand assets whenever they need them.
Local-first is not going to win, but that's okay We'll explore the complexities of traditional stack (db-server-frontend), develop a theory of software evolution: which systems succeed and why.
I don’t think this is very productive (expert users of a piece of software are notoriously bad at being able to tell if an explanation will be clear to non-experts), so I needed to find a way to identify problems with the man pages that was a little more evidence-based.
. Understanding how we grow and develop will help you become a better leader and a more empathetic colleague. More accessible than his academic work, this book also provides a framework for understanding underlying beliefs and motivations that might be holding you back.
go fire up your browser. Do it in incognito. Go to your app and do everything with a fresh Gmail address. Try support. See how your support is. Try to contact sales.
To be clear, speed in itself does not mean labor markets and employment won’t eventually recover, it just implies the short-term transition will be unusually painful compared to past technologies, since humans and labor markets are slow to react and to equilibrate.
My go-to languages are TypeScript for web stuff, Go for CLIs and Swift if it needs to use macOS stuff or has UI. Go wasn’t something I gave even the slightest thought even a few months ago, but eventually I played around and found that agents are really great at writing it, and its simple type system makes linting fast.
Zen: I'm also a fan of Brave, but Zen is a great browser because it's open-source and firefox-based, but with all the customization and utilization I need.
elements, JavaScript reigns supreme. SvelteKit's efficiency and reactivity make it my framework of choice, and TypeScript's type annotations bring a welcome layer of confidence to my codebase.
Not every plank in his argument is convincing, and the research has evolved since the book first came out a decade ago, but the ambition is impressive and the framework holds up.
The only highly populated industrial country unable to trivially meet its electricity and synthetic fuel needs with solar alone is the United Kingdom, due primarily to a high population density and high latitude. The Nordic and Baltic countries are tiny by comparison. Among other problems, the UK needs to decide if it wants the future where energy is cheap and it is rich, or the future where energy is expensive and it is poor. If the former, it is time to get serious about large scale deployment of wind power, using home-grown vertically integrated technology at prices as low as $10/MWh.
I’ve got a GitHub actions thing that runs a piece of software I wrote called shot-scraper that runs Playwright, that loads up a browser in GitHub actions to scrape that webpage and turn the results into JSON, which then get turned into an atom feed, which I subscribe to in NetNewsWire.
I’ve got a GitHub actions thing that runs a piece of software I wrote called shot-scraper that runs Playwright, that loads up a browser in GitHub actions to scrape that webpage and turn the results into JSON, which then get turned into an atom feed, which I subscribe to in NetNewsWire.
The models are much more like the first student but even more because then we say okay so the model should be good at competitive programming so let's get every single competitive programming problem ever and then let's do some data augmentation so we have even more competitive programming problems
Thus my personal prediction is that in domains that are already largely under the powers of modern AI, such as languages, programming or chess, we’re going to see a divergence in human abilities.
It significantly lowered the bar to production. It is how we got the whole
society to run on software. If you make it harder for hobbyists maintainers, you
are going to crash society.
FOSS solve that problem far more than it solves “we don’t want to pay”. Most
corporations would be surprised by how cheap it would cost them to pay
for the FOSS software they use.
the improvement software improvements of really throughput in terms of tokens per dollar per watt that we're able to get uh you know quarter over quarter year over year is massive uh right so it's 5x 10x maybe 40x in some of these cases
it's kind of like databases right it's always the thing it's like hey can one database be the one that just is used everywhere except it's not uh there are multiple types of databases that are getting deployed uh for different use cases.
So this AI thing will be that right. So if you take coding um what we built with GitHub and VS code in over whatever decades uh suddenly the coding assistant is that big in one year and so that I think is what's going to happen as well which is the market expands massively.
this fundamentally this category of coding and AI is probably going to be one of the biggest categories right it is a software factory category in fact it may be bigger than knowledge work
which I think is going to just keep growing because guess what it's going to grow faster than the number of users. So in fact that's kind of one of the other questions people ask me is hey what happens to the per user business at least the early signs may be the way to think about the per user business is not just per user it's per agent
I had typed "Taylor Swift" in a browser, and the response had literally zero links to Taylor Swift's actual website. If you stayed within what Atlas generated, you would have no way of knowing that Taylor Swift has a website at all.
I think that for those who can create and then articulate a framework around what is taste for us that is really a important skill and uh then I think people can a lot of people can basically match a framework not many people can create the framework.
I think in this world where software can be created more easily, design matters so much and designers matter so much. I think designers are going to be the leaders of the future and I think that more designers need to speak step into that leadership role
if you want to win in the game of software, you need to differentiate through design. Like that's again how you win or lose. Craft matters. And so we're no longer in this era of good enough is fine. It's like good enough is not enough.
Cursor… it’s tab completion model is industry leading, if you still write code yourself. I use VS Code mostly, I do like them pushing things like browser automation and plan mode tho.
Roon is software to control your home stereo. I have a lifetime subscription, and the link gets you thirty days for free. If you love music, you'll get a lot out of this.
Good software requires maintenance and ongoing attention, which is why most people will still prefer to pay to use something someone else is maintaining.
As for me personally, I tend to use these tools as a backend data store and use Jupyter notebooks as well as my own custom built annotation interfaces for most of my needs.
The panel had a generally positive view of Phoenix, with one panelist calling it one of his “favorite open source eval tools.” The tool is positioned as a developer-first, notebook-centric platform.
Yeah. I still think math is essential. It's something that shapes your brain, it teaches you to rely on your logical thinking to split big problems into smaller parts, put them in the right sequence, solve them patiently, trying again if it doesn't work.
You need reproducible builds in order to verify that the app really does what it claims, really encrypts data in a way that it is described on its website. For that you need to make your apps open source for any researchers to have a look at it.
Just imagine you use very bad software and um the team that started the project decided early to use Xamarin and then they never had a chance of making this as good as all the other things you really appreciate on your phone due to this decision no matter how good they are.
However, we are actually absolutely doing this. It's just the great works are kernels of operating systems, the browser, the um lots of the software platforms, the phones, the um the incredible advances in uh silicon lithography
So, I think it'll be the same thing that that we'll see an increase in the scope that we're giving that we're willing to give to the robots as they get better and better where initially the scope might be like there is a particular thing you do like you're making the coffee or something. Uh whereas as they get more capable, as their ability to have common sense and a broader repertoire of tasks increases, then we'll give them greater scope. Now you're running the whole coffee shop.
Like if you answer a question, you just like answered it wrong. It's like well it's not like you can just like go back and like tweak a few things like the person you told the answer to might not even know that it's wrong. Whereas if you're like folding the t-shirt and you messed up a little bit like it's pretty obvious like you can reflect on that, figure out what happened and do it better next time.
With Web forms, the burden is on people to adapt to databases. Today's AI models, however, can flip this requirement. That is, they allow people to provide information in whatever form they like and use AI do the work necessary to put that information into the right structure for a database.
I started using PHPStorm last year and I love it. I honestly don't know how I managed to live without it. It makes it a breeze to refactor a large codebase or source dive some vendor code.
I think regulation of AI is sort of the wrong level of abstraction. Talking about regulating AI as AI is the wrong level of abstraction. And it's like saying we're going to regulate databases or regulate spreadsheets or regulate cars. Well, we do, but not like that.
It wasn't clear that the browser wasn't where the value capture was cuz Microsoft crowbarred its way into dominance in browsers but that turned out not to matter and then all the value is in search advertising and social which were 5 years later and 10 years later and so like you can be very very clear that this is the thing and then still be completely unclear how it's going to work.
so it's not a simple matter of programming it's not you know typing into a keyboard until or or I guess asking cursor to do something until a piece of software emerges, it's exploration, it's discovery, it's posing hypotheses and validating or invalidating those again and again and again.
We can have a breakthrough in our agent architecture on Monday implemented on Tuesday and have it deployed with hundreds of our customers on Wednesday and directly see the impact of of that work.
And in contrast to software as a service or software you'd buy off a shelf at, you know, Fry Electronics, you know, decades ago, which might help you be marginally more productive, help you get a job done. Agents, in contrast, are actually getting the job done for you. And so you're in essence hiring software to accomplish a task and get it done well.
it's like if you're a software engineer and you're not using something like cursor to do your job, you're probably being half as productive or even worse than you could be.
And actually the reason I think it's exciting is if you look at like the database space right now there's not one database. If you want to do largecale data analytics you'll choose one thing. If you want to do a transactional data store you'll do another. I think we're moving to that area of models
if you tell what what jobs are most likely to be automated with the current generation of technology, you would probably put software engineering right at the top. The people building this technology or building the technology that is disrupting their own profession.
And the impact of solar array on desert is arguably positive because it shades the ground and improves like soil moisture retention. Um there like if you wanted to reverse desertification, you would basically just deploy solar panels on it and that would pay for the process.
Ellen Ullman's Close to the Machine is a memoir I couldn't believe I hadn't read earlier. Many of her observations about engineering culture feel as relevant today as when she was a programmer in the 1980s
So the great programmers will be even better, but there'll be even 10X even what they are today. And because there, you'll be able to use their skills to utilize the tools to the maximum, exploit them to the maximum.
governing frontier AI requires standards for safety and security, incentives for the leading AI developers to follow those standards, and evidence that the standards are being followed.
I think the platform that Lean and other software tools, so GitHub and things like that will allow experimental mathematics to scale up to a much greater degree than we can do now.
I do. If you have a passion for computer science, I would. Computer science is obviously a lot more than programming alone, so I would. I still don't think I would change what you pursue. I think AI will horizontally allow impact every field.
Opaque, inert and obstructive elements might occupy the same place as full-screen command line interfaces — a powerful niche UI that was a marker in history, passed on by the windowed environment of the multi-tasking, graphical user interface revolution.
LLMs can write a large fraction of all the tedious code you’ll ever need to write. And most code on most projects is tedious. LLMs drastically reduce the number of things you’ll ever need to Google.
The code in an agent that actually “does stuff” with code is not, itself, AI. This should reassure you. It’s surprisingly simple systems code, wired to ground truth about programming in the same way a Makefile is.
That’s because most clean energy jobs are in deployment and maintenance rather than manufacturing, and since higher costs slow down the rollout of renewables, increasing prices reduces the total number of people working in clean energy (even if the number working in manufacturing increases).
CCS can never be competitive in the sense of working economically in the absence of a policy framework to price in the cost of carbon, unlike clean electricity.
I think the big thing to realize for indie developers right now is there's massive, massive competition in every major genre, and it's very unlikely that unless you just happen to be the world's best at a particular thing that you're going to release a game in an existing highly competitive genre and win.
But the metaverse and 3D gaming in general needs something that's rather more powerful, more safe, more scalable, and more capable than JavaScript because the metaverse is actually a more difficult technical problem than a webpage.
The biggest limitation that's built up over time is the single-threaded nature of game simulation in Unreal Engine. We run a single-threaded simulation. If you have a 16 core CPU, we're using one core for game simulation and running with the complicated game logic because single-threaded programming is orders of magnitude easier than multi-threaded programming.
But there are other parts of programming languages that are not subjective but should be fundamental. And when you look at type systems, there is a way to do type systems that gives you mathematical proofs. And every other way of type systems that doesn't give you mathematical proofs is just worse and should ultimately be rejected.
This is getting easier in the lastest versions of Fedora and Ubuntu (e.g., Ubuntu 24.04 LTS) which are shipping system libraries with frame pointers by default.
Everyone’s software is good enough these days. The barriers to entry are low. To stand out, you need to make your product feel great. One way of doing that is through animations.
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