What public figures publish and believe, in their own words.
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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.
They come to a computing platform because the install base is large. Because a developer, like anybody else, wants to develop software that reaches a lot of people. So, the install base is, in fact, the single most important part of an architecture.
So you get this rapid, incredible great talent, rapid innovation because of open source and just, you know, the nature of friends, and, and insane competition. Among the company, what emerges is incredible stuff. And so this is the fastest innovating country in the world today
You know, a lot of people would say, "You know AI is gonna completely destroy software. We don't need software anymore. We don't even need tools anymore." That's ridiculous.
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.
Yes, I could totally see how OpenClaw could become a huge company. And no, it’s not really exciting for me. I’m a builder at heart. I did the whole creating-a-company game already, poured 13 years of my life into it and learned a lot. What I want is to change the world, not build a large company and teaming up with OpenAI is the fastest way to bring this to everyone.
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.
That's why I warn in my security documentation, don't use cheap models. Don't use Haiku or a local model. Even though I, I very much love the idea that this thing could completely run local. If you use a, a very weak local model, they are very gullible. It's very easy to, to prompt inject them.
That, that gets into the whole arch of every app is just a very slow API now, if they want or not. And that through personal agents a lot of apps will disappear.
But I don't want to, like, pull that down because every time someone made the first pull request is a win for our society, you know? Like, it… Like, it doesn't matter how, how shitty it is, y- you gotta start somewhere.
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.
Компьютеры стали бытовым прибором, начать программировать легче, чем когда-либо, сложнейшие вещи делаются просто и даже тривиально, написаны горы готового кода. К сожалению, у этого есть и обратная сторона - программы становятся большими, медленными, неуправляемыми, непонимаемыми.
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.
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.
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.
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.
It's also worth noting that chat isn't the only way to integrate AI in software products and increasingly agent-based applications outperform chat-only solutions. So expect things to keep changing.
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.
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.
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.
it's a luxury good like you're not paying the penalty for that the people who embrace it and think that they can just ask AI for everything or they can just look everything up but they don't have to understand the copy pasta that they slam into their project they're the ones who going to suffer
Their words now
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.
I enjoy it even almost like as a sort of pair programmer AI pair programmer who doesn't drive who's just there to give suggestions to know the API to do all these other things but the second it starts wanting to autocomplete my code I'm like yeah I'm out bro
Their words now
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.
I used to think it required more churn to get progress to stay on the leading edge of new stuff. And I wrote this before I experienced the indignity of the 2010s in the JavaScript community.
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.
GPUs are not nearly as restricted in their future progress as CPUs which are far more constrained in how they can physically improve (compiler-driven ILP only goes so far).
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.
These systems will be absolutely central to the economy, technology, and national security, and will be capable of so much autonomy that I consider it basically unacceptable for humanity to be totally ignorant of how they work.
I then asked myself, is the position of speed unique? and is it available? And the answer was overwhelmingly yes because almost no software was being sold or has ever been sold on the value proposition of speed.
Well, I strongly believe that we should make business software like we make games because when we make products like we make games, people find them fun. They tell their friends. They fall in love with them.
And that's why when you have a missionritical product like email where you are interfacing with customers with candidates with investors it turns out to really matter. Email is mission critical. So it's not something where you can simply launch with a halfbaked product.
Sometimes you have to move fast at the sacrifice of knowledge, and I'm totally on board for that, but I worry that what we'll create is an entire generation of incompetent programmers who can do some amount of things well, but anything that is unique, bespoke, or requires some extra like little elbow grease, might become very difficult. It might cause a whole chasm where juniors remain juniors forever.
And so we often talk about programming in perspective of web, or something that's pretty narrow, and I think that's just a social construct of Twitter more than anything else, that actually I don't believe it's that representative of the entire programming world out there.
Most of the time I'm not thinking, I'm programming. I know what I want to do, I want to go as fast as possible because I've been just doing it for so long and I'm so familiar with the general space that it becomes a huge problem for me. I cannot tell you how many times that I've been purely bottlenecked by the fact that I just can't type fast enough and I just need to get it out of my head onto the text editor.
The editor obviously does not make the programmer, but I think it says a lot about your character as a programmer if you don't know how to use your editor well.
The new trend toward vibe coding and vibe design may be upending the user-centered design paradigm that has remained based on the same ideology since the first UX design projects at Bell Labs, starting in 1947.
However, with so many different software projects out there, each moving so rapidly and depending on and being used by so many other projects, it becomes practically-inevitable that some regressions "like that one" happen, almost constantly.
I'm hopeful this framework will turn out to be a much more robust style for writing performance-sensitive code, especially over time and as compilers evolve.
Vibe coding can execute instructions, but deciding what the software should do and why is not automated. Product managers and designers must still do user research, market analysis, and creative brainstorming. In that sense, vibe coding changes the implementation phase more than the planning phase of the product lifecycle.
As a Python and JavaScript programmer my favorite models right now are Claude 3.7 Sonnet with thinking turned on, OpenAI’s o3-mini-high and GPT-4o with Code Interpreter (for Python).
This is what leads to slop JS/TS software. Treating errors generically like this is a mistake. It leads to fragile software, poor telemetry/observability/debugging, and as a result worse experiences
You Need a Budget (YNAB) is a simple to use (but sophisticated under the hood) bit of budgeting software that uses the principles of human habits and behavioral finance to make you more conscious and efficient in your spending.
But really the software engineering agents I think can be done faster sooner than any other agent because it is a verifiable domain. You can always unit test or compile, and there's many different regions of it can inspect the whole code base at once, which no engineer really can.
But what happens when every company can just invent their own business logic really cheaply and quickly? You stop using platform SaaS, you start building custom tailored solutions, you change them really quickly.
And they're decent, their hardware is better in many ways than in NVIDIA's. The problem is their software is really bad and I think they're getting better, right? They're getting better, faster, but the gulf is so large and they don't spend enough resources on it or haven't historically, right?
The big picture is that I don't think it's going to be a cliff. I think a really good example of how growth changes is when Meta added stories. So Snapchat was on an exponential, they added stories, it flatlined.
I think that they're trying to shift the narrative. They're trying to protect themselves. We saw this years ago when ByteDance was actually banned from some OpenAI APIs for training on outputs. There's other AI startups that most people, if you're in the AI culture, were like they just told us they trained on OpenAI outputs and they never got banned.
until there are feedback loops of open source AI, it seems like mostly an ideological mission. People like Mark Zuckerberg, which is like America needs this and I agree with him, but in the time where the motivation ideologically is high, we need to capitalize and build this ecosystem around, what benefits do you get from seeing the language model data?
This is a command line tool with plenty of plugins that lets you prompt different models. Think of it as a command-line version of Open WebUI. It’s particularly useful for quick scripting and basic automation.
I mean, I've been doing this for over 15 years. If there were any shortcuts, I'd be all over them. There are patterns and there are frameworks, but there's no shortcuts.
A fresh take on navigating the tech the interview process, tailored for frontend engineers. She wrote the book after she found Cracking the Coding Interview to be too Java/backend-focused. The book comes with 1, 2 and 4-week learning plans as well. A great book to start with.
"Tidy First? is the first in a series of books about software design. Kent has been coming back to the topic of “taming” software design in a digestible format."
I think it’s fantastic when businesses are built on open source, the WordPress ecosystem is at least 10B+ a year; Automattic and WP Engine are less than 5% of that.
Many software investors eschew hard tech startups because of their capital intensity, but it’s hard to deny that huge returns are possible in hard tech: just consider SpaceX.
This isn’t a money grab: it’s an expectation that any business making hundreds of millions of dollars off of an open source project ought to give back, and if they don’t, then they can’t use its trademarks.
If WP Engine wants to find another open source project with a more permissive license and no trademarks, they are free to do so; if they want to benefit from the WordPress community, then they need to respect WordPress trademark and IP.
when you send someone a link to a post, they can't read it without loading the entire Mastodon frontend app into their browser, which will is a monster React codebase that will break if they have scripting disabled and also can take up to 30 seconds on older hardware.
I use MAMP for WordPress development, Postman for API testing, Notion for notes and task management, Slack and Discord for communication and Keynote for course presentations.
I’m also still not sure how much I like nix – it’s very confusing! But it’s helped me compile some software that I was struggling to compile otherwise, and in general it seems to install things faster than homebrew.
Their words now
I’ve mostly switched back to Homebrew, nix was interesting but overall I think it’s not worth the complexity for me
In my approach, I resist using any external value framework as an ultimate set of criteria against which to measure games’ worth - not purpose, not pleasure, not politics.
Clients still pay a fixed monthly retainer to ensure the professional maintenance of the whole portfolio, and to get access to the expertise of all of Geomys’ maintainers.
From the onset, I envisioned small firms of professional maintainers with thematic portfolios, accommodating diverse maintainers and project sizes, just like the specialized firms of other professionals.
I started with a rather non-consensus hypothesis: companies want to pay for their critical open source dependencies, but most projects are not selling them a legible way to do so.
At current deployment rates it will take Waymo about 20 years with ZERO fatalities to show they are net as safe as average human driver fatality rates (including the old cars, impaired drivers, etc. in that comparison baseline).
I think life obeys universal principles. I think there is some deep underlying explanatory framework that will tell us about the nature of life in the universe and will allow us to identify life that we can’t yet recognize because it’s too different.
My hot take is that JS has the lowest bar of entry to building and being productive (a good thing) but one of the highest bars of any language and stack to building high quality, stable, and reliable software. Very few devs have the expertise to pull off the latter
And for a long time, I thought that's what had worked. That this was why Ruby on Rails took off, became one of the most popular full-stack web frameworks of all time, inspired countless clones, and created hundreds of billions in enterprise value for companies built on it. But I was wrong. It wasn't the crusade that did it.
Side note for CSS, I'm cool to use what ever tech available out there that makes my task done quickly & well, I have personally used Bootstrap 3 & 4, Bulma, Lostgrid, Materliaze, Skeleton, Tailwindcss, Styled-components, emotion, CSS modules, Tachyons & made my own micro CSS framework called Unnamed that has over 200 stars on GitHub. Still I prefer using Tailwindcss.
By all accounts, from people who become memory athletes, they weren’t born with some extraordinary memory, but they practice strategies over and over and over again. The strategy that they use for memorizing a particular thing, it can become automatic, and you can just deploy it in an instant.
The best tooling in the world will struggle to make up for "regularly losing a day debugging your environment," and so getting that aspect right can easily outweigh almost any other decisions you make.
It is almost inevitable that per-engineer productivity drops to some extent as an organization and codebase grows, even though it's also nearly-impossible to quantify that effect.
That is, labs should make sure that the safety measures they apply to their powerful models prevent unacceptably bad outcomes, even if the AIs are misaligned and intentionally try to subvert those safety measures.
Yeah, it is interesting because, when people react against you by saying you are being arrogant about this, 99.999% of the time, all they mean is I disagree. That’s all they really mean, right?
Copyleft does not impose restrictions, but it does impose obligations. The obligations exist to guarantee rights to the users of the software – in other words, to ensure freedoms.
No such restrictions are found in free or open source software licenses, be they permissive or copyleft – all FOSS licenses permit the use of the software for any purpose without restriction.
I'm excited about what this means for the open-source community and research, with the gap between closed-source and open-weight models closing and SOTA-level conversational models being more easily accessible.
This is not the same
world that you were part of. The complexity is off the chart; we are hidden
layers and layers under the scaffolding. And we are used everywhere.
Based on public commercial data that tells a lot about the military potential of these dual-use robotic spacecraft, we have shown that China can manufacture and deploy 200 such spacecraft as early as 2026, enough to cripple critical US satellites in geosynchronous, highly elliptical, and other orbits, and thus severely degrading space support to wartime operations.
I think that was an unfortunate move because their goal is mainly to extract profit from the software project rather than to uphold the ideals of Free and Open Source Software.
In short summary, the licenses limit the freedoms of what one can do with the software in order for Redis Labs to be solely enriched, while asking for volunteer labor, and having already
So part of the reason that we deploy the way we do, we call it iterative deployment, rather than go build in secret until we got all the way to GPT-5, we decided to talk about GPT-1, 2, 3, and 4. And part of the reason there is I think AI and surprise don’t go together. And also the world, people, institutions, whatever you want to call it, need time to adapt and think about these things.
I think that the enshittification framework goes a long way to explaining it, moving us out of the mysterious realm of the 'great forces of history,' and into the material world of specific decisions made by named people – decisions we can reverse and people whose addresses and pitchfork sizes we can learn.
Because patents have fixed term lengths, with small extensions to compensate for the year or so when the drug is under regulatory review, drug developers are incentivized to go after conditions where clinical trials can be completed quickly, all else being equal.
In light of the increasing number of closed-source LLMs, it is important to continue to promote an open culture of sharing knowledge, data, and software, from which the NLP community has benefited greatly.
One thing that drives me crazy about the React ecosystem, and more specifically "tech influencers" and "thought leaders" in the space, is the infantilization of the developers using and working in it. I’m tired of reading takes like TypeScript generics, mapped types, etc should only be needed and used by library authors for most use cases. Or today’s discourse; Don’t use `useCallback’, ‘useMemo’, and React.memo. If you’re building anything beyond a simple CRUD app or a an incredibly focused app with few features, you _will_ need these features.
Despite evaluations, we cannot consider coming powerful frontier AI systems "safe unless proven unsafe". With current testing methodologies, issues can easily be missed. Additionally, it is unclear if governments can quickly build the immense expertise needed for reliable technical evaluations of AI capabilities and societal-scale risks. Given this, developers of frontier AI should carry the burden of proof to demonstrate that their plans keep risks within acceptable limits.
A number of commentators have consistently predicted that solar cost improvements will level out “this year” since about 1990, and yet if anything deployment, cost decline, and the learning rate have only improved.
What we don't want to happen with AGI, we want to happen with synthetic biology. What we don't want to happen online and software with language, we want for it to happen with bio-based materials.
It’s always harder to write software for more specialized hardware. A GPU is pretty generic. If you can’t write an in Nvidia stack, there’s no way you can write a stack for your chip. My approach with Tinygrad is first write a performant NVIDIA stack.
Of course, when you talk to an AI that’s made by a big company in the cloud, the AI fundamentally is aligned to them, not to you. And that’s why you have to buy a tiny box. So you make sure the AI stays aligned to you.
So almost if Codex or copilot are helping you, that actually probably means that your framework or library is bad and there’s too much boilerplate in it.
But the real thing that I want is not something that like tab completes my code and gives me ideas. The real thing that I want is a very intelligent pair programmer that comes up with a little popup saying, “Hey, you wrote a bug on line 14 and here’s what it is.”
I think driving is not tool complete and programming is. Meaning you don’t use the best possible tools to drive. Cars have basically the same interface for the last 50 years. Computers have a radically different interface.
At the same time, in order to reduce the probability of someone intentionally or unintentionally bringing about a rogue AI, we need to increase governance and we should consider limiting access to the large-scale generalist AI systems that could be weaponized, which would mean that the code and neural net parameters would not be shared in open-source and some of the important engineering tricks to make them work would not be shared either.
While we love GraphQL for many use cases, implementing a secure and performant GraphQL API can be tricky and there is a definite cost to requiring it during early prototyping of your app.
RSC is the future of React. The React team has made this very clear and we are lucky to be in touch with their amazing team members to help us along this path.
The app costs a few dollars up front and then has an optional subscription for unlimited requests, but I would recommend going directly to OpenAI’s developer dashboard, creating your own account, and copy/pasting your own API key into Petey.
It simply cannot be the case that we're willing to give up a decade or more of hardware performance just to make programmers’ lives a little bit easier.
This experiment started from the observation that despite being critical for the functioning of the Internet—and, by extension, the economy—the role of open-source maintainer has not yet found a sustainable manifestation.
The temptation to enshittify is magnified by the blocks on interoperability: when Twitter bans interoperable clients, nerfs its APIs, and periodically terrorizes its users by suspending them for including their Mastodon handles in their bios, it makes it harder to leave Twitter, and thus increases the amount of enshittification users can be force-fed without risking their departure.
The Linux Programming Interface by Michael Kerrisk – an exhaustive reference on how Linux works. There are about a million chapters, but every individual chapter is pretty short and I find it quite readable.
I spent the last few weeks reading Template Metaprogramming with C++ by Marius Băncilă. It is currently 50$ on Amazon. Though, technically, the book is about advanced 'template' techniques, it is much more broad and practical. It is one of the 'good programming books'. If you are an experienced C++ programmer, you should give it a peek
Our Tendency shapes every aspect of our behavior, so understanding this framework lets us make better decisions, meet deadlines, suffer less stress and burnout, and engage more effectively.
Sure, electric bikes aren't cheap. But I believe they're a rare object to be well worth the cost. This in spite of their annoying flaws, their often bad software, their defective geometries. Because they open the world.
The Vanmoof is much smarter — the brain and software within it are refined, the app good, the acceleration curves smooth — but the bike is all custom components, and they aren't the highest quality at that.
Programming, of course, is forgetting, but we need to at least try to be aware of the costs of the abstractions we choose and consider who it is that ends up being forgotten.
In my opinion the root cause of this bug is that when a white american developer sees a terminal they immediately interpret it as this idealized cartesian plane where they can lay out any writing they want in neatly-spaced characters that behave in "predictable" ways (in other words, behave exactly like English).
I have argued that the probability of a bad equilibrium is only marginally influenced by the level of debt, but can be much reduced by a contingent rule making the primary balance react to an increase in debt service.
Multipliers are likely to vary a lot over time and space, but the bulk of the evidence is that they are different from zero, positive for spending, negative for taxes, and that they are stronger when monetary policy does not or cannot react to fiscal policy.
Modern browser with split-screen functionality. Helps organize different work contexts more efficiently. Yeah I know, I know. It's a Microsoft product.
Code has mass. Every additional line of code you don't need is ballast. It weighs your codebase down, making it harder to steer and change direction if you need to.
Climate change is the existential crisis of our time. We need more ideas and progress in every sector, including software-based approaches to preventing emissions and sequestering carbon.
Free software is designed to be used commercially, but you have to do it correctly. This is a resource which is made available to companies who want to exploit it, but they must do so according to the terms of the licenses.
I used to think that this was unequivocally a win for open source. That to fight for attention with the commercial alternatives, we had to adopt the commercial playbook. Now I think it’s at the very least a mixed blessing.
WinMerge just gets better and better. It's free, it's open source and it'll compare files and folders and help you merge your conflicted source code files like a champ.
Other software I use to build stuff includes Netlify for hosting, GitHub for version control and collaboration, SVGO and TinyPNG for optimization, Kap for screen recording, GoatCounter for analytics, and Chrome and Firefox dev tools.
Other software I use to build stuff includes Netlify for hosting, GitHub for version control and collaboration, SVGO and TinyPNG for optimization, Kap for screen recording, GoatCounter for analytics, and Chrome and Firefox dev tools.
But nobody will ever get to the billions of representative miles necessary to say anything compelling about expected safety until after they actually deploy their fleet.
The fast route — venture capital funded — is going to impose constraints on your business that will ultimately make it difficult to remain true to your open-source mission.
Selling is hard. Building a repeatable model with a team that you attempt to rapidly scale is even harder. Fortunately, Mark Roberge, who was one of the very first employees at HubSpot shares the processes and frameworks he used to build a sales machine. If you like the principles behind Lean Startups, then his data- and experiment-driven approach to sales will be very appealing.
Want to know the story behind how Salesforce was built? This is that story in founder Marc Benioff's own words. At times I found him overly prescriptive without an appreciation for his unfair advantages he had (getting to start it while having a big salary at Oracle, having $6Mn in "bootstrapped funding", etc). However, he also helped pioneer the cloud and SaaS as a business model, so there are many great lessons to glean if you're building a high-growth SaaS business.
Breville Bambino Plus Espresso Machine and Baratza Encore ESP Pro Coffee Grinder - Developers need coffee, and I like mine HOT. The integrated milk steamer is a must-have, and since this machine takes freshly ground beans, the grinder allows me to tweak the grind size for perfect single dose espresso shots.
To read papers, I use Adobe Acrobat Reader and sync them in the cloud. This lets me read, highlight, and sync my papers across devices (work laptop, personal laptop, iPad). Instapaper does the same for online articles.
To read papers, I use Adobe Acrobat Reader and sync them in the cloud. This lets me read, highlight, and sync my papers across devices (work laptop, personal laptop, iPad). Instapaper does the same for online articles.
The data paint an incredible picture: One that shows the price of solar electricity from utility-scale systems dropping by anywhere from 30-40% with each doubling of cumulative solar deployment.
Because arguably the majority of our time working on software is not spent writing it: we're reading code, trying to understand it, slightly tweaking and editing it.
A korrent is a belief a person has stated in their own words: one
sentence stating the claim, backed by a quote and a source, kept at
korrents.com.
Under a name here, the quoted block is what they actually said.
The korrent beneath it is the claim those words support, in
korrents' wording — tap it to see the record, its source, and who
else holds it.
Nobody here wrote their own korrents. They are compiled from public
statements, and a person can change their mind, which is recorded too.
About the English under a post
Some people here publish in a language other than English. Where they
do, this site shows a machine translation beneath the post, in
this typeface — the site's own, not theirs.
The post itself is never changed, moved or hidden: what is set in the
serif above is exactly what the person published, and it is what to
quote them on. A translation can be wrong in ways that matter,
especially about tone.
Only the post's own words are translated. A quoted post, a linked
article and a belief on korrents.com
are left in their original language.